3. Biodiversity impacts of solar power, wind power and power lines

Understanding and mitigating the impacts of renewable energy infrastructure on biodiversity is fundamental to ensuring electricity expansion is not just low-emissions, but also biodiversity-aligned. Renewable energy and power lines can impact biodiversity at various stages of the infrastructure life cycle, from the mining and processing of minerals required for infrastructure components through to the construction, operation, maintenance and eventual decommissioning or repowering of energy facilities (Figure 3.1).

These impacts on biodiversity can be positive or negative, direct or indirect. Direct impacts refer here to those impacts resulting directly from renewable power and grid infrastructure projects, or the mining of resources necessary for their construction. Examples include habitat loss and fragmentation from mining or the construction of a renewable power facility, direct species mortality from collision with infrastructure, habitat creation and changes to ecosystem service provision or access (e.g., recreational or aesthetic values of a landscape; food provisioning services). Direct impacts tend to be easier to account for in decision-making than indirect and cumulative impacts. This is because direct impacts tend to be predictable, occur during the lifetime of an infrastructure project and usually occur at or close to the site where renewable power infrastructure is deployed (Bennun et al., 2021[1]).

Indirect impacts are the by-products or induced effects of renewable power deployment. A positive indirect impact on biodiversity may arise where renewable power expansion displaces fossil fuels, thereby helping to mitigate climate change. Another example of a positive indirect impact is where improving rural access to renewably sourced electricity decreases reliance on forests for fuel, thereby reducing deforestation (Tanner and Johnston, 2017[2]). Adverse indirect impacts may occur when the development of access roads for mining or renewable power projects facilitate (illegal) logging and other natural resource extraction, or economic opportunities surrounding mining and renewable power development lead to in-migration and subsequent increases in pressure on local biodiversity. Indirect impacts may occur far from the site where renewable power is deployed (e.g., from displacement of agriculture or other human activities). They are influenced by multiple factors external to a specific project or programme and are less predictable than direct impacts (Bennun et al., 2021[1]).

The various direct and indirect impacts can combine to cause cumulative impacts. Cumulative impacts include the combined impacts of a single renewable power facility (e.g., habitat fragmentation and direct mortality), the combined impacts of multiple projects, either from the same sector or multiple sectors across an ecosystem, landscape or migratory route, and the combined effects of pressures over time. Cumulative impacts may be additive (i.e. the impact is equal to the sum of individual impacts), synergistic (i.e. the cumulative impact is greater than the sum of the individual impacts), or antagonistic (i.e. the cumulative impact is less than the sum of its individual impacts) (Whitehead, Kujala and Wintle, 2017[3]; IFC, 2013[4]; Goodale and Milman, 2019[5]).

This chapter examines the direct, indirect and cumulative impacts of solar energy photovoltaics (PV), concentrated solar power (CSP), wind energy (onshore and offshore) and electricity networks (transmission and distribution lines). It first synthesises the evidence for biodiversity impacts arising during their construction, operation, maintenance and decommissioning. It then discusses the importance of considering the upstream impacts of renewable power infrastructure that result from the extraction and processing of minerals required for infrastructure components.

Renewable power infrastructure can affect biodiversity in various ways during its construction, operation and maintenance, and decommissioning or repowering (Table 3.1). The type and magnitude of impacts depend on the renewable power technology. For example, bird and bat collision are a particular concern for power lines and wind turbines, whereas habitat loss is a greater concern for solar energy. Impacts also depend heavily on site-specific variables (i.e., location), and the practices employed to design, construct, operate, maintain and decommission renewable power infrastructure. As discussed throughout this report, opportunities exist to scale up wind and solar power without compromising biodiversity goals provided biodiversity is effectively mainstreamed throughout planning, policy and project processes.

The body of evidence for renewable power impacts on biodiversity has developed considerably in recent years, and is helping to inform efforts by governments, energy developers and investors to mitigate negative biodiversity impacts. However, data and knowledge of biodiversity impacts are uneven across technologies, taxa and geographies. Specifically, the evidence base for onshore wind is more established than for offshore wind and solar energy. Whereas impacts on avian species (e.g., collision mortality) have been extensively studied (particularly for wind), few studies examine impacts on other taxa. Most of the evidence for biodiversity impacts comes from parts of Europe and North America; the evidence base is less developed in regions where significant expansion of renewable power infrastructure is expected (e.g., Africa, Latin America, Southeast Asia).

For solar PV and CSP, onshore and offshore wind and electricity networks, key knowledge gaps remain concerning population-level and cumulative impacts (e.g., for migratory species), knock-on effects on ecological communities, ecosystems and ecosystem services, indirect impacts and the effectiveness of mitigation measures. Focused research efforts, long-term systematic monitoring and standardised data collection will be important for addressing knowledge gaps and understanding how impacts may scale with the global expansion in renewable power (see 5.1.4).

The two main types of solar energy technologies are PV and CSP. Solar PV is much more geographically widespread than CSP, and accounts for most solar capacity and projected growth in solar capacity. Solar PV cells are assembled in solar panels (modules) to convert sunlight into direct electric current, using the photoelectric effect. Multiple solar panels can be connected to form solar arrays. Solar modules can be mounted on the ground, on existing infrastructure, such as individual residential and commercial buildings, or on purpose-built floating structures.

Solar modules may be fixed-mount or automated tracking systems that follow the sun’s path. Solar tracking systems optimise electricity production but tend to have higher capital costs. While they generally require more land surface than fixed-mount systems to avoid shading, the higher output of solar tracking systems means that fewer panels are need for the same energy outputs (Campbell et al., 2009[6]; Dunlop, 2010[7]).

PV facilities vary in size from small schemes of <1 megawatt (MW), which provide energy to a single consumer or a small group of consumers, to large utility-scale facilities with a capacity of more than 1 MW and as much as 2 gigawatts (GW) (e.g. Huanghe Hydropower Hainan Solar Park China, which spans 564 hectares) (Murray, 2021[8]; Hernandez et al., 2014[9]). Small schemes are often incorporated into existing infrastructure, such as rooftop solar schemes (see 4.3.1).

While the majority of PV capacity is land-based, the installed capacity of floating solar photovoltaic facilities is increasing. Floating PV facilities are typically installed on freshwater lakes, fabricated reservoirs and canals but may also be installed in various marine ecosystems. For example, marine solar PV demonstration projects have been established in the Persian Gulf (coastal waters of Dubai in the United Arab Emirates), in the North Sea (The Netherlands), deep fjords (Norway), and shallow tropical lagoons (Maldives) (Hooper, Armstrong and Vlaswinkel, 2021[10]). Floating solar could help reduce land-use pressure while increasing solar panel efficiency due to the cooling effect of water on PV modules, but it too can generate risks to biodiversity that need to be assessed and managed (Armstrong et al., 2020[11]; Dörenkämper et al., 2021[12]; Sacramento et al., 2015[13]; Choi, 2014[14]).

The other solar energy technology, CSP, uses mirrors to concentrate the sun’s energy onto a receiver that converts it to heat. The heat can then be used to create steam, which drives a turbine to generate electricity. Several CSP technologies exist, including arrays of mirrors (heliostats) that track the sun and concentrate light on a fixed centralised receiver (solar power tower), arrays of linear mirrors (Fresnel reflectors) laid flat on the ground that focus light on liquid-filled pipes, parabolic solar troughs that focus light on a receiver running along their focal point, and parabolic dish systems comprising standalone parabolic reflectors that concentrate light on a receiver at the focal point (SolarPACES, 2018[15]; Brunel, 2021[16]). Unlike PV facilities, CSP plants can store thermal energy that can then be converted into electricity and dispatched in response to demand, even during the night or cloudy periods. CSP facilities can provide baseload power around the clock and be ramped up quickly in response to grid requirements (IBRD, 2020[17]).

Utility-scale PV and CSP facilities have similar infrastructure requirements. Requirements include module mounting infrastructure and associated solar tracking systems, solar panels or mirrors (reflectors), electricity infrastructure such as cabling, inverters, transformers, and on-site sub-station and transmission lines to connect to the power grid, access roads and security perimeter fences. In addition to these common components, CSP facilities require a concentrating solar collector such as solar power towers (Bennun et al., 2021[1]). Floating PV facilities need a floating support structure for solar arrays and a mooring and anchoring system (Exley et al., 2021[18]).

Ground-mounted solar facilities require large areas of land to accommodate infrastructure such as solar panels (PV) or mirrors and towers (CSP). Lovering et al. (2022[19]) find that on average ground-mounted utility scale CSP require 2 000 hectares per terawatt hour per year (TWh/y) and utility scale PV requires 2 100 hectares per TWh/y. Owing to their relatively large land requirements, ground-mounted utility scale facilities are sometimes sited far from end-users. Their remoteness increases the requirement for additional infrastructure such as power line corridors, roads and substations, which can increase the overall physical footprint of solar energy. Increasing improvements in solar energy efficiency could help to reduce the amount of area required per unit of energy produced. PV technologies that are integrated into the built environment are among the most land-use efficient source of renewable power (Fthenakis and Kim, 2009[20]).

Potential impacts of solar power facilities on biodiversity include direct wildlife morbidity and mortality, habitat loss and degradation, habitat fragmentation and barrier effects, habitat alteration or creation, behavioural changes, physiological changes and displacement, IAS impacts, ecosystem service impacts, indirect impacts and cumulative population-level impacts. Peer-reviewed empirical evidence for these impacts is scarce, however, and reviews of impacts have often inferred impacts. While ground-mounted solar energy development can negatively impact biodiversity, studies suggest that in certain contexts (e.g., when installed in degraded lands and with biodiversity-specific management practices), solar facilities can be deployed with minimal or potentially even positive impacts on biodiversity. The impacts of solar energy on biodiversity are discussed in detail below.

The presence and operation of solar energy facilities can lead to direct wildlife morbidity and mortality. The nature and magnitude of impacts depend on the technology (e.g., PV or CSP), and a project’s location, size and design (Walston et al., 2016[21]). The two primary causes of direct mortality in solar energy facilities are collision and burning. Drowning of species in solar evaporation ponds of CSP have also been documented (Jeal et al., 2019[22]). Avian mortality from collision with solar facility infrastructure has been documented for both PV and CSP sites of all technology types. In addition, several studies indicate that bats and insects may also collide with solar infrastructure, particularly fans of air-cooled condensers of CSP sites (Murphy-Mariscal, Grodsky and Hernandez, 2018[23]). Collision risk is likely to be higher when surfaces are oriented vertically and reflecting light (Bennun et al., 2021[1]).

Given the sparseness of data in peer-reviewed literature, generalisations of collision risk are limited for solar facilities. Unlike for wind energy and other energy infrastructure (e.g., power lines), it is unclear which bird species are at higher risk of collision. However, mortality from collision has been documented in a wide range of avian species. For example, Kosciuch et al. (2020[24]) documented avian mortality across nine taxonomic orders. In the grey literature, Kagan et al. (2014[25]) found that mortality at three solar facilities in California (a CSP tower facility (Ivanpah), CSP trough (Genesis) and PV (Desert Sunlight)), occurred in species of different body sizes (e.g. hummingbirds and pelicans), and with markedly different ecology (e.g. aerial feeders, aquatic feeders, ground feeders and raptors; nocturnal and diurnal species; and resident and non-resident species). Solar facilities may pose a risk to all birds flying over or using a solar energy facility, but the level of risk likely depends on biological, topographical, meteorological and technical factors (Visser et al., 2019[26]).

The extent or significance of collision mortality for solar energy is poorly understood but is likely to be lower than mortality from fossil fuel facilities (Walston et al., 2016[21]), wind turbines, power lines and other human activities at the current capacity. Extrapolating findings from a three-month study at the largest solar PV facility in South Africa, Visser et al. (2019[26]) estimated a mortality rate of 4.5 birds/MW/year, although the cause of mortality could not be established. A study of carcasses across 10 PV plants in California and Nevada, US, spanning 13 site-years,1 found collision was the primary determinable2 cause of mortality, but was unable to identify the cause of mortality for 61% of carcasses. Estimates of avian mortality within the solar field (i.e. excluding fences and power lines) of these facilities ranged from 0.08 birds/MW/year (0.03 birds/hectare/year) to 9.26 birds/MW/year (5.17 birds/hectare/year), with a mean of 2.49 birds/MW/year (1.09 birds/hectare/year) (Kosciuch et al., 2020[24]).

Walston et al (2016[21]) provided a significantly higher estimate of avian mortality from solar facilities in the US, of 9.9 birds per MW per year. Three factors partly explain the higher estimate (Kosciuch et al., 2020[24]). First, the study covered different solar technologies, one PV facility (California Valley Solar Ranch) and two CSP tower facilities (California Solar One and Ivanpah). CSP tower facilities pose not only a collision risk, but also a risk of burning from solar flux (discussed below) and were found to have a mortality rate 7-21 times higher than at the PV site. Second, the study included all infrastructure monitored (e.g., power lines and fences). Third, the PV facility included had significantly higher annual mortality rate than the other 12 site-years included in the study by Kosciuch et al. (2020[24]). While these three studies provide an indication of the magnitude of collision mortality risk, it is important to note that their sample size is small and geographic scope limited. Mortality risk is not well understood in different habitat contexts, so attempts to extrapolate mortality rates to other projects may be misleading (Kosciuch et al., 2020[24]).

Another cause of morbidity and mortality, which is limited to CSP facilities, is burning. Birds and insects can be burned when they cross the concentrated solar light reflected to the central receiver in CSP facilities. When birds’ flight feathers are singed from solar flux, their flight can be impaired, increasing the risk of collision with the ground or other objects and reducing their capacity to feed and avoid predators (Kagan et al., 2014[25]; Walston et al., 2016[27]). Each of these effects can lead to mortality. Avian morbidity and mortality from burning has been documented at CSP facilities in Israel, Spain and the US (Ho, 2016[28]; Kagan et al., 2014[25]). Fatal burning of insects such as dragonflies and butterflies has also been observed (Kagan et al., 2014[25]), but has not been addressed in peer-reviewed literature.

Evaporation ponds at solar facilities, used to store wastewater and concentrate chemicals before disposal, can also pose a risk to wildlife from drowning or poisoning. A four-month study of a CSP plan in South Africa, for example, identified 37 carcasses in evaporation ponds, including four species of birds, one species of reptile and seven species of mammals (Jeal et al., 2019[22]).

Given the scarcity of peer-reviewed data and limited understanding of the mechanisms leading to wildlife morbidity and mortality at solar facilities, further empirical research would be beneficial. Such research could help to ensure solar facilities are located, constructed and operated in a way that is consistent with biodiversity objectives. Systematic, repeatable and standardised sampling protocols could help to build the evidence base while promoting accuracy, precision and comparability (Huso, Dietsch and Nicolai, 2016[29]; Visser et al., 2019[26]). In addition, behavioural studies could help improve understanding of species risk factors and identify mitigation strategies. Priority research areas relate to species’ perception of solar facilities (attraction/deterrence), movement, habitat use and interspecific interactions to inform mitigation measures (Chock et al., 2020[30]).

Habitat loss and degradation can occur at the construction, operation and decommissioning phases of solar energy facilities. The construction of ground-mounted solar PV and CSP facilities may involve vegetation removal and surface grading to facilitate installation, prevent shading of solar panels by vegetation or undulating land and reduce on-site risk of wildfire. During the operation phase, some solar facilities apply herbicides, cover the land with gravel and mow frequently to manage the vegetation around solar panels (Turney and Fthenakis, 2011[31]).

These construction and operation practices can drive habitat loss and degradation, resulting in species mortality or displacement, which in turn can lead to declines in species richness and density (Murphy-Mariscal, Grodsky and Hernandez, 2018[32]). In addition to removal of plant species, clearance and grading can increase soil erosion and reduce the amount of organic carbon and nitrogen, which in turn can affect primary production by plants and food availability for wildlife (Antonio Sánchez-Zapata et al., 2016[33]). In the French Mediterranean, Lambert et al. (2021[34]) surveyed soil temperature and moisture, CO2 effluxes, and vegetation below and outside solar panels of three solar parks. Physical, chemical and general soil quality indexes were lower in a solar park than in semi-natural land cover types (pinewood and shrubland). Clearing and grading the soil surface during solar park construction resulted in a strong degradation of soil physical quality, especially of soil structure.

Whether habitat loss and degradation from a solar facility is significant depends on the intactness and ecological value of the habitat prior to construction (i.e., the baseline), the location of the solar facility and how it is constructed and operated. PV or CSP solar facility deployment is more likely to result in biodiversity loss if it occurs in relatively undeveloped areas. In the US, for example, the perennial plant cover and structure at a CSP facility in California was found to be less than surrounding areas of relatively undeveloped desert (Grodsky and Hernandez, 2020[35]).

In contrast, solar facilities installed in degraded lands and actively managed for biodiversity may have a positive impact on habitat. For example, a study of eleven solar farms in the UK found that, overall, the facilities supported a higher diversity and abundance of broad leaved plants, grasses, birds and invertebrates than the agricultural or brownfield land where they were sited (Montag, Parker and Clarkson, 2016[36]). The degree to which these eleven solar facilities were beneficial to biodiversity was highly dependent on the site management approach: solar farms with the highest wildlife value were seeded with diverse seed mix after construction, limited the use of herbicides, provided marginal habitat for wildlife and adopted biodiversity-minded livestock grazing or mowing regimes.

The deployment of PV and CSP solar facilities may also degrade habitats by altering water quality and quantity. Surface-water flows are sometimes deliberately modified at solar farms to reduce soil erosion around solar infrastructure. This may affect downstream aquatic ecosystems and habitats by changing the flow of organic matter, nutrients, minerals, and sediments. Dust suppressants and herbicides used to maximise exposure of panels to sun can increase run-off and affect the chemical composition of waterways (Cameron, Cohen and Morrison, 2012[37]; Grippo, Hayse and O’Connor, 2014[38]). Cooling water released from CSP facilities could affect the temperature of water bodies and contaminate them with hazardous chemicals, such as cooling system toxicants, antifreeze agents, heavy metals and rust inhibitors (Hernandez et al., 2014[9]). This could be harmful to freshwater species (Bennun et al., 2021[1]).

In addition, utility scale solar may lead to water withdrawal and consumption. CSP facilities with wet-cooling systems require vast quantities of water: around 3 500 litres/MWh of electricity generated, compared to 1 000 litres/MWh in natural gas-fired power plants (EC, 2019[39]). Such facilities could place stress on water resources and affect riparian habitats particularly in water-scarce areas, which tend to be where CSP are located (Lovich and Ennen, 2011[40]). Dry-cooling or hybrid-cooling systems significantly reduce CSP water consumption (Hernandez et al., 2014[9]), but can reduce the efficiency of solar plants. Radiative cooling technologies are emerging that may help reduce water use of wet-cooling systems without compromising efficiency (Aili et al., 2022[41]). Both PV and CSP may use water for cleaning panels and mirrors or for dust suppression, although cleaning requires relatively small amounts of water and emerging technologies and practices are increasing the efficiency of cleaning (Hernandez et al., 2014[9]; EC, 2019[42]).

Generally, water withdrawal and consumption from solar PV entails relatively low risks and is much lower than alternative energy systems. For example, solar PV and wind turbines, across their life cycle, consume about 0.1–14% and withdraw about 2–15% of the water typically used by thermo-electric power plants (coal or nuclear) to generate 1 MWh of electricity (Roehrkasten, Schaeuble and Helgenberger, 2015[43]).

At a landscape level, the deployment of solar energy facilities may fragment habitat and create barriers to species movement. Habitat fragmentation is when a continuous habitat is divided into isolated patches of remnant habitat because of conversion or disturbance (Wilson et al., 2015[44]). It results in both a smaller total amount of habitat area and changes to a habitat’s spatial configuration (Berger-Tal and Saltz, 2019[45]). Habitat fragmentation has been linked to declines in species richness, edge effects, compromised ecosystem function, and isolation of populations and reduced genetic exchange (Haddad et al., 2015[46]) (Fahrig, 2003[47]).

While the impacts of infrastructure-induced habitat fragmentation are relatively well-documented (e.g., for linear transport infrastructure), there is a dearth of studies focussing on the effects of solar infrastructure. Several studies, however, suggest that habitat fragmentation is an important consideration for solar energy expansion. One study, for example, found that over 70% of PV and 90% of CSP utility-scale installations planned and under construction in California, US, were within 10 km of a protected area (Hernandez et al., 2015[48]). The authors warned that the facilities could increase edge effects and undermine the effectiveness of the protected areas as wildlife corridors.

Another study found that the deployment of solar facilities in Florida, US, may undermine efforts to save the endangered Florida panther (Concolor coryi) (Leskova, Frakes and Markwith, 2022[49]). The only wild breeding population of the Florida panther is restricted to <5% of its historic range in South Florida, and the area may be close to carrying capacity. Three viable populations within the historic range are needed for species recovery. A comparison of Florida panther habitat suitability and connectivity pre- and post-installation of 45 utility scale solar energy facilities found that nine facilities were located within major corridors connecting the only breeding population with other areas that could support populations of Florida panther, 26 facilities were located within other areas that could facilitate some dispersal of the panther.

Such studies underscore the importance of considering landscape-level connectivity in strategic planning and siting decisions, in addition to environmental impacts within facility boundaries (see Chapter 3). Careful siting and design of solar facilities can reduce the extent of habitat fragmentation. For example, in a large solar power facility in central Australia, a vegetation strip was left as a north-south corridor through flour blocks of arrays, dividing the 250-ha block in two. This strip has reportedly enabled the movement of wildlife through the facility (Guerin, 2017[50]). In the light of climate-induced changes to species distribution and corridors, it is prudent to consider both current and future distribution and dispersal patterns of species when siting infrastructure.

Solar facilities tend to be secured by fences, which may provide a physical barrier to dispersal for non-volant animals, in addition to posing a collision risk for volant animals. Dispersal barriers can affect migration patterns, feeding and gene flow (McInturff et al., 2020[51]). The impact of solar facility fences on wildlife has not been quantified, but literature on fences used for other purposes provide an indication of the potential impacts and mitigation measures (Buton, 2023[52]), such as permeable fences to facilitate dispersal of kit foxes Vulpes macrotis in San Joaquin Valley, California (Cypher et al., 2021[53]).

Solar panels or mirrors may also influence soil and microclimate conditions by catching precipitation and atmospheric deposition, changing surface albedo, increasing ground shading and affecting wind speed (Hernandez et al., 2014[9]). Owing to the albedo effect, for example, night temperatures at a solar PV installation in a rural area were found to be 3-4 degrees Celsius (°C) higher than wildlands (Barron-Gafford et al., 2016[54]). Conversely, in city environments where albedo is lower, modelling for the cities of Los Angeles (Taha, 2013[55]) and Paris (Masson et al., 2014[56]) suggested that PV deployment could have a net cooling effect. Owing to the insulation effect due to shading and airflow, spring and summer soil temperatures at a CSP plant were 0.5-4 °C lower in summer and higher in the winter compared to control sites with no collectors (Wu et al., 2014[57]). Similarly, a study at a UK PV facility observed cooling in the summer of up to 5.2 °C, and drying under the PV arrays, compared with gaps between PV arrays and control areas (Armstrong, Ostle and Whitaker, 2016[58]).

The impact of solar facilities on microclimates depends not only on their location but also the technology. For example, solar PV fixed-mount and tracking systems effect microclimatic conditions differently. A study of the two technologies in Chile determined that fixed-mount solar modules provide shade where the temperature is cooler and humidity is higher throughout the day, while solar tracking systems create temporally varying shading conditions (Suuronen et al., 2017[59]).

Changes to soil and microclimate conditions may lead to changes in species composition, richness and diversity (Tanner, Moore and Pavlik, 2014[60]). For example, a study of a UK solar PV facility found that species diversity and plant biomass under PV arrays were lower owing in part to differences in soil and air temperature (Armstrong, Ostle and Whitaker, 2016[58]). In some contexts, the shadow effect of solar panels could be beneficial, for example, when used to preserve crops during heatwaves and drought (Barron-Gafford et al., 2016[54]) or by providing shade and shelter for some arthropods (Suuronen et al., 2017[59]) and avian species (Visser et al., 2019[26]). If vegetation is allowed to regrow between panels, solar facilities could also provide nesting opportunities (Visser et al., 2019[26]). Further evidence of the microclimatic changes associated with solar facilities in different contexts, and the resulting impact on species and ecosystem services, could help to optimise solar facility design for biodiversity.

The construction and operation of solar energy facilities could elicit behavioural responses for certain species. Potential responses include avoidance of (or attraction to) noise, light and physical structures, and changes to feeding patterns, competition and reproduction. Such responses, which may be temporary or permanent, can affect energy expenditure and predation risk, potentially reducing fecundity and increasing mortality in wildlife (Murphy-Mariscal, Grodsky and Hernandez, 2018[61]). Behavioural changes induced by solar energy facilities could, therefore, negatively affect populations and ecological communities.

Few studies have examined behavioural changes and species displacement induced by solar facilities. However, evidence suggests that solar energy facilities can displace species both through habitat destruction and avoidance behaviour (effective habitat loss). For example, a study of a CSP facility in South Africa found that birds were much more abundant (141.9 birds/km) and species rich (51 species) in the surrounding rangeland than in the solar field (1.27 birds/km; 22 species) (Jeal et al., 2019[22]). Another study found bird species richness (and to a lesser extent density) at South Africa’s largest solar PV facility to be lower than the boundary zone and adjacent untransformed land (Visser et al., 2019[26]).

In some circumstances, species may be moved deliberately from a solar facility site prior to construction to avoid negative impacts on biodiversity. While this may reduce the risk to some species, mitigation-driven species translocation is not always successful and may put physiological stress on wildlife (Germano et al., 2015[62]). For example, desert tortoises (Gopherus agassizii) translocated to mitigate the impacts of a solar development in Mojave Desert in California, US, experienced higher body temperatures and increased energy expenditure during first year following displacement, particularly in the first month. However, translocation did not appear to affect the growth and body condition of the tortoises (Brand et al., 2016[63]). More recently, it was reported that 30 out of 139 tortoises relocated for the Yellow Pine Solar Energy project in Nevada died within a few weeks of their relocation (Castillo, 2021[64]).

While some species avoid solar energy facilities, others may be attracted to them. For example, preliminary research and anecdotal evidence suggests that solar PV can be “ecological traps” for insects. Aquatic insects may be attracted to the polarised light reflected by PV panels, mistaking the panels for water surfaces. The increased concentration of insects may then attract insectivorous birds and bats to the panels (Kagan et al., 2014[25]). The attraction of insects to solar PV could have knock-on effects on ecological communities, particularly where solar facilities are close to water bodies (Horváth et al., 2009[65]; Horváth, 2010[66]).

Unexpected findings of stranded, injured and deceased water-associated birds (i.e. species that rely on water for foraging, reproduction, and/or roosting, such as herons and egrets) and water-obligate birds (i.e. species that cannot take flight from land, such as loons and grebes) at a PV facility in California led scientists to propose that some birds mistake solar arrays for water (i.e. the Lake Effect Hypothesis) (Kagan et al., 2014[25]) (Kosciuch et al., 2020[24]). Little empirical evidence exists to support or disprove the hypothesis. A recent study exploring the hypothesis concluded that some species of aquatic birds could be attracted to solar PV facilities in certain contexts, but that a PV solar facility is “unlikely to provide a signal of a lake to all aquatic habitat birds at all times” (Kosciuch et al., 2021[67]).

Solar energy facilities could facilitate the introduction or spread of invasive alien species (IAS) through two general pathways, the first direct and the second indirect. First, the construction and maintenance of solar facilities involves the movement of solar energy infrastructure components, equipment and people, each of which provides a potential vector for species. For example, soil on machinery could introduce IAS to the facility. Second, the degradation or loss of habitat during construction or operation could reduce ecosystem resilience and thereby facilitate the colonisation or spread of IAS. In California, for example, invasive grasses have been found to take hold after blading (removal of above-ground vegetation) (Grodsky and Hernandez, 2020[35]). Data and literature on the colonisation or spread of IAS resulting from solar energy development (and the impact this has on ecological communities) are scarce.

Solar energy deployment may affect ecosystem service supply and access. Potentially affected services include supporting services such as soil formation and nutrient cycles, regulating services such as climate and hydrology, provisioning services such as water and food supply, and cultural services such as recreational activities, aesthetic and spiritual values (Antonio Sánchez-Zapata et al., 2016[33]).

Quantification of solar energy impacts on ecosystem services is all but absent in the primary literature. However, some studies shine a light on the potential tensions between solar energy deployment and ecosystem service provision (Murphy-Mariscal, Grodsky and Hernandez, 2018[32]; Exley et al., 2021[68]; van de Ven et al., 2021[69]; Bevk and Golobič, 2020[70]; Hastik et al., 2015[71]). For example, De Marco et al. (2014[72]) deemed 42 of the 82 permitting requests for new utility scale solar energy sites in Lecce, Italy (equating to 18 563 ha of land-cover change), to be in ecologically unsuitable areas, owing to the ecosystem service values they put at risk. The 42 sites included century-old olive groves notable for their high cultural value and areas that provide a relatively large contribution to carbon sequestration, relative to other land-cover types evaluated. A study of Ivanpah Solar Electric Generating System in the Mojave Desert, California, found that non-bee insect flower visitors were negatively affected by the facility. The authors warned that solar energy disruption of non-bee insect flowers visitor communities in deserts could lead to cascading effects on biodiversity, including globally threatened pollinator-dependent cacti (Grodsky, Campbell and Hernandez, 2021[73]).

The impact of solar energy on ecosystem services depends on a facility’s location and how it is developed and operated. For example, floating photovoltaics may affect nine ecosystem services linked to eight SDGs, however, whether the impact is positive or negative likely depends on the water body type and design of the system (Exley et al., 2021[68]). A study of the Ivanpah CSP facility in the Mojave Desert, California, showed ecosystem service values from desert plants differ among solar energy development decisions (Grodsky and Hernandez, 2020[35]). Provisioning, regulating, habitat and cultural ecosystem service values are lower in bladed treatments than mowed or halo3 treatments, and highest at control sites. Bladed treatments result in ecosystem “disservices”, by facilitating the colonisation of invasive grasses.

In some contexts, through proper siting, design and management, solar facilities could enhance several ecosystem services, while helping to combat climate change and meet energy demands (Randle-Boggis et al., 2020[74]; Walston et al., 2021[75]). For example, compared to pre-solar agricultural land uses, solar facilities in Midwest United States that restore and manage native grassland can increase pollinator supply by 300%, carbon storage potential by 65%, sediment retention by more than 95% and water retention by 19% (Walston et al., 2021[75]).

In theory, land take for solar facilities could displace other land uses. In some countries, solar energy has been deployed in agricultural or forestry land. For example, about 28% of utility scale solar energy in California is in agriculture land (cropland and pasture), equivalent to about 150 km2 (Hernandez et al., 2015[48]). In some cases, solar and agriculture production may be co-located (4.3.1), thereby reducing land-use pressure. However, in other cases, solar energy deployed in agricultural land may come at the expense of agricultural production. This may shift agricultural activities to other locations to meet growing demand, thereby contributing to land-use change or pollution far from the solar project site.

When solar energy facilities are in remote, previously inaccessible locations, the construction of service roads could induce further road construction and facilitate access for other human activities. This could result in increased pressure on natural resources in the area, for example though legal and illegal logging, harvesting and hunting, and pollution. Increased movement of people facilitated by new transport routes could also facilitate the spread of invasive alien species. While such indirect impacts of road construction have been examined, particularly for tropical forest systems (Laurance, Goosem and Laurance, 2009[76]), they have not been well-studied in the context of solar energy.

Little is known about how various impacts of a single solar energy facility (e.g., the combination of collision risk, habitat loss, displacement) accumulate, or the combined spatial and temporal impacts of multiple facilities on species and ecosystems. Concentrating solar energy facilities in landscapes or habitats with high irradiance could lead to significant cumulative habitat loss and collision mortality. For example, in California, US, the plurality of developments are sited in shrubland and scrublands, which are often fragile habitats with high endemism (Hernandez, Hoffacker and Field, 2014[77]). Across the US, deserts and xeric shrubland habitats are expected to be most affected by land-use change from PV and CSP deployment by 2030 (McDonald et al., 2009[78]).

Much of the literature has focused on the impacts of large utility-scale solar facilities on biodiversity, however, the cumulative impacts of multiple, smaller facilities could also pose a threat to biodiversity. In Japan and Korea, for example, medium-size solar facilities have collectively driven greater amounts of natural and semi-natural habitat loss than large-scale solar PV (approximately 66% and 86% of the overall loss in Japan and Korea, respectively) (Kim et al., 2021[79]).

In addition to the cumulative impacts across solar energy facilities, a concern is how solar impacts may accumulate with impacts from other infrastructure or human activities. A study of the combined impacts of wind and solar developments in the US, for example, indicate that these could have a significant impact on the demographics of various bird species (Conkling et al., 2022[80]) (discussed further below in 3.1.2).

Wind energy developments may consist of utility-scale turbines (>100 kilowatt [kW]) that deliver their energy to the national electricity transmission network, or small (<100kW) to medium-scale (100-500 kW) turbines that produce electricity for on-site use. Utility-scale developments involve multiple turbines connected in a wind farm, while small and medium-scale turbines for on-site use are typically installed as single units.

Wind power is produced both by onshore and offshore wind facilities. Onshore wind represents the vast majority of wind power production, with capacity growth led by China and the USA (IEA, 2020[81]). Offshore wind represents only 7% (57 GW) of total wind power capacity, with most capacity found in Europe and China (Lee and Zhao, 2022[82]). However, offshore wind is rapidly maturing and set to expand in the coming decades owing to performance and cost improvements. In 2021, 22.1 GW of new offshore installations were commissioned, representing 22.5% of all new wind installations (GWEC, 2022[83]). The expansion of bottom-fixed and floating offshore wind energy presents new risks to marine biodiversity, which remain only partially understood; however, it also presents an opportunity to reduce pressure on scare land resources and terrestrial biodiversity.

Offshore wind turbines are either bottom-fixed or floating. While bottom-fixed accounts for most offshore capacity, significant developments have been made in floating offshore in recent years. The UK, for example, installed 57 MW in 2021 (Lee and Zhao, 2022[82]). Floating offshore wind allows wind resources to be tapped in areas where water depths exceed 50-60 metres and traditional fixed-bottoms offshore installations are not viable (IEA, 2019[84]). The technology also increases the potential to harness wind energy in areas where conflicts with biodiversity and other economic activities is relatively low.

Infrastructure components of wind energy facilities include a collection of turbines (each comprising a nacelle, rotor, blades and tower), a collector sub-station, cabling that run between the substation and each turbine, and a high voltage power line connecting the substation to the power grid. In addition, fixed offshore wind facilities also have underwater components securing the turbine to the seabed (e.g., monopoles, tripods, jackets, suction caisson or gravity base) (IPCC, 2011[85]). Floating offshore wind facilities have a floating structure, typically spar buoys, spar-submersibles or tension-leg platforms (Maxwell et al., 2022[86]; SEER, 2022[87]). The structure is moored with a catenary (in the case of spar buoys and spar-submersibles) or taut-leg (for tension-leg platforms). Whilst simpler to install, catenary systems have a larger spatial footprint than taut-leg systems. Catenary mooring configurations may be anchored by drag-embedded, piled or gravity anchors. Taut-leg configurations tend to use driven or suction piles or gravity anchors. In addition to the export cable and transmission lines, other onshore infrastructure required for offshore wind facilities includes a construction port and an onshore substation (Bennun et al., 2021[1]).

Onshore wind turbines in 2019 ranged in size from 1.5-4.8 MW (IRENA, 2019[88]), however larger turbines are entering the market. Global average rotor diameter for onshore wind has increased from 82 metres (m) in 2010 to nearly 120 meters (Lee and Zhao, 2022[82]), with maximum rotor diameter of over 160 m (European Commission, 2020[89]). Average hub height has increased from 81 to 103 m during the same period (Lee and Zhao, 2022[82]). Offshore wind turbines are typically larger, with an average capacity of 8 MW and turbines as large as 15 MW now on the market. Average rotor diameter for offshore wind was 163 m in 2020 (Lee and Zhao, 2022[82]). Increases in rotor diameter and hub height enable wind farms to harness power from higher and more consistent wind speeds, increasing their efficiency. Furthermore, increased height has allowed siting of turbines in forest areas as the tree canopy has less influence on wind speed and turbulence on the higher turbines (European Commission, 2020[89]). These technological developments have potentially mixed implications for biodiversity. For example, larger more efficient wind turbines can reduce number of required turbines but increase the potential collision zone for volant species (discussed further below). Large turbines make it possible to co-locate wind turbines with forestry activities (European Commission, 2020[89]), which on the one hand could reduce land-use pressure and on the other hand make it technically possible to locate wind turbines in ecologically important forests, posing a risk to biodiversity.

Wind turbine facilities occupy a large area to allow sufficient space between turbines to reduce turbulence, follow topography and avoid obstacles. However, the area between turbines can be used for other economic or environmental purposes (see 4.3.1). When accounting for the required spacing between wind turbines, wind power is one of the most land-use intensive sources of electricity (second only to dedicated biomass), requiring on average 15 000 hectares per TWh/y. However, when accounting only for the direct footprint of wind energy infrastructure (turbine pads and access road), wind power is among the least land-use intensive of electricity sources, requiring 170 hectares per TWh/y; only nuclear and geothermal have lower land-use intensity (Lovering et al., 2022[19]).

A growing body of literature indicates that wind energy facilities can affect biodiversity in various ways, especially birds and bats for onshore wind, and birds, fish and marine mammals for offshore wind. Studies have focused primarily on the impacts of utility-scale wind developments on volant species and open habitats; less is known about impacts on other taxa. Onshore wind impacts have been better studied than offshore wind, reflecting onshore wind’s longer history, wider-distribution and greater accessibility for assessment, monitoring and evaluation. For offshore wind, data and information vary considerably across geographies. For example, within Europe the knowledge base necessary for managing offshore wind and biodiversity interactions is much greater for the North and Baltic Seas than for the Mediterranean and Black Seas (European Commission, 2020[89]). The available scientific literature agrees that the key risks wind turbines pose to biodiversity are from collision mortality, habitat loss, displacement due to disturbance, barrier effects, and indirect ecosystem-level effects.

One of the most evident and measurable impacts of wind energy facilities on biodiversity is direct mortality of birds and bats, during the operation of wind energy facilities. Direct mortality or morbidity is primarily caused by collision with wind turbines. While some evidence indicates that barotrauma (tissue damage to air-containing structures caused by rapid or excessive pressure change) may also be a source of bat mortality (Baerwald et al., 2008[90]), further studies suggest it is unlikely to be significant (Rollins et al., 2012[91]; Lawson et al., 2020[92]). The data and understanding of collision risk is greater for onshore wind facilities given the technical and logistical constraints associated with assessing actual numbers of bird and bat collisions with offshore wind turbines (Hüppop, 2019[93]). Few studies show which species or species groups may be particularly vulnerable to offshore wind, and under which conditions.

Widely-cited estimates of annual bird mortality from collision in the US range from 140 000 to 679 000, based on studies from onshore wind facilities (Loss, Will and Marra, 2013[94]; Erickson et al., 2014[95]; Smallwood, 2013[96]). However, these estimates date to 2012 and wind energy capacity in the US has since increased by over 100%, and wind turbine design has changed. Mean adjusted mortality rates4 for most US-based studies have more recently been pegged at 3-6 birds/MW/year (American Wind and Wildlife Institute, 2021[97]). With 2023 capacity in the US reaching 145 569 MW (DoE, 2023[98]), annual mortality from turbine collision in the US may be between 436 700 and 873 400 birds. (Zimmerling et al., 2013[99]) estimated average avian mortality to be 8.2 birds per wind turbine in Canada, based on observations at 43 wind farms.

Estimates in South Africa of avian mortality are slightly lower than in the US and Canada, at 2 birds/MW/year (Perold, Ralston-Paton and Ryan, 2020[100]). Collision rates with wind turbines in the Isthmus of Tehuantepec, Mexico, are higher, conservatively estimated at 9.06-12.85 birds/MW/year (although this may not be representative of national mortality rates) (Cabrera-Cruz et al., 2020[101]). Estimates of total bird mortality from wind turbine collision are orders of magnitude lower than from collisions with some other infrastructure such as building windows (Sovacool, 2009[102]; Loss et al., 2014[103]), however, mortality could have cumulative, population-level effects for certain sensitive species (see Cumulative impacts and population-level effects).

Unlike for birds, wind turbine collision is the primary source of collision mortality in bats. Bat mortality rate from collision is also higher than for birds. Hayes (2013[104]), for example, estimated that over 600 000 bats were killed in the US by wind turbines in 2012, while Smallwood (2013[105]) estimated 888 000 bat mortalities for the same period. Estimates of bat mortality tend to range from 4-7 bats/MW/year in the US (American Wind and Wildlife Institute, 2021[97]), which would correspond to ~580 000 – 1 018 983 bats per year at 2023 wind power capacity (DoE, 2023[98]). However, some estimates put average mortality much higher at around 11.6 bats/MW/year (in Canada and US) and 17.2 bats/MW/year (US only) (Smallwood, 2013[105]). In Germany, an estimated 10-12 bats are killed per turbine per year (Voigt et al., 2015[106]), equivalent to 4-4.6 bats/MW/year assuming wind turbine capacity of 2.5 MW. Mortality rates much higher than national averages have been recorded at some facilities, underscoring the importance of appropriate siting and operational practices. For example, mortality rates of 40 bats/MW/year or more have been documented at wind energy facilities in the US and Mexico (American Wind and Wildlife Institute, 2021[97]; Cabrera-Cruz et al., 2020[101]) and at old wind energy facilities in Germany, which tend to be poorly-sited and operate without curtailment (Voigt et al., 2022[107]).

Mortality from wind turbine collision has been documented in a diversity of resident and migratory bird and bat species. A global meta-study found documentation of collision mortality in 362 avian species (data covered 16 countries) and 31 bat species (data covered 12 countries) (Thaxter et al., 2017[108]). A study of 20 facilities in South Africa documented collision mortality in 130 avian species from 46 families, equivalent to 30% of the bird species identified in and around the facilities (Perold, Ralston-Paton and Ryan, 2020[100]).

While collision mortality affects a wide range of species, some species are more vulnerable to collision. Among avian species, Accipitriformes (birds of prey), Bucerotiformes (hornbills and hoopoes), Ciconiformes (storks and herons) and some Charadriiformes (shorebirds) have relatively high levels of vulnerability (Thaxter et al., 2017[108]). Small passerines tend to account for most observed mortality, but this likely reflects their greater abundance (AWWI, 2019[109]). For offshore wind facilities, modelling and empirical evidence suggests that gulls, pelicans, terns and cormorants are of greatest risk of collision (Adams et al., 2016[110]; Everaert and Stienen, 2006[111]; Skov et al., 2018[112]).

Among bat species, Nyctalus, Pipistrellus, Vespertilio and Eptesicus spp. account for the majority of mortalities in Europe (Rydell et al., 2010[113]), while in North America, the majority of bat mortalities are of hoary bat (Lasiurus cinereus), eastern red bat (Lasiurus borealis) and silver-haired bat (Lasionycteris noctivagans) (American Wind and Wildlife Institute, 2021[97]). Because studies have largely focused on temperate areas (Europe and North America in particular), understanding of collision-risk for insectivorous bats is better developed than for fruit bats, which tend to live in tropical and sub-tropical zones.

Various species-specific, location-specific and facility-specific factors may contribute to a species’ vulnerability. A global trait-based assessment of collision vulnerability identified migratory status, dispersal distance and habitat associations as important species-specific factors for avian vulnerability to collision (Thaxter et al., 2017[108]). The related factors of morphology (e.g. size and wing loading) (Barrios and Rodríguez, 2004[114]; de Lucas et al., 2008[115]), and flight behaviour (e.g. flight height) (Poessel et al., 2018[116]; Roemer et al., 2017[117]; McClure et al., 2021[118]) may also affect avian vulnerability (see (Marques et al., 2014[119]) for an overview). Among bat species, those adapted for open-air foraging, migratory species and tree-roosting species appear to be most vulnerable. Several studies suggest that some bat species may be attracted to turbines, although different hypotheses exist over the cause of the attraction (e.g. turbine noise, insect concentrations around turbines, or bat mating behaviour) (Richardson et al., 2021[120]; Cryan, 2014[121]; Cryan, 2008[122]). Dispersal distance has also been identified as the key species-specific factor for bat vulnerability (Thaxter et al., 2017[108]). Being nocturnal, and often high flying, bat interactions with turbines are more difficult to study; relatively little is known about why some species tend to be more vulnerable than others (Thompson et al., 2017[123]; Cryan, 2014[121]).

In addition to species-specific factors, location-specific factors and the design of wind energy facilities can affect collision risk. Location-specific factors include topography (Rydell et al., 2010[124]), overlap with migratory routes (Drewitt and Langston, 2008[125]) and other flight paths (e.g. to foraging and roosting sites) (Everaert and Stienen, 2006[126]), habitat type and quality (Heuck et al., 2019[127]) and weather conditions (Rydell et al., 2010[113]; Schmuecker et al., 2020[128]). For example, wind turbines located at avian migratory bottlenecks tend to experience particularly high rates of collision (Thaxter et al., 2017[108]), and collision risk to migratory soaring birds may increase when turbines are located along ridges that overlap with orographic lift (Marques et al., 2014[119]). Studies of bat collision mortality at North American wind facilities found that collision rates increased on nights with low wind speed, and before and after the passage of storm fronts (Arnett et al., 2008[129]).

Facility-specific factors include the configuration and scale of the wind energy facility, turbine design (e.g. size, type, and visibility), cut-in speed and hours of operation (Marques et al., 2014[119]). The impact of turbine size on collision rates is uncertain. Several studies have shown collision rates tend to be higher at larger turbines (Thaxter et al., 2017[108]; Rydell et al., 2010[124]), which could be due to the larger rotor-swept area or because the taller turbines increase the overlap with the flight heights of nocturnal, migrating songbirds and bats (American Wind and Wildlife Institute, 2021[97]; Matthew et al., 2016[130]). However, deploying fewer but larger wind turbines with greater energy output could reduce total collision risk per unit energy output (American Wind and Wildlife Institute, 2021[97]; Thaxter et al., 2017[108]). Raptor mortality on a per MW basis declined by 67%-96% (depending on the species) at the Altamont Pass Wind Resource Area after replacing smaller, low-capacity turbines with taller, higher-capacity turbines (Smallwood and Karas, 2009[131]). However, several factors could explain this decline, including the reduction in the total number of turbines, the relatively slower rotation of larger turbines, and the shift from lattice-tower turbines, which may attract raptors by providing perching sites, to modern monopole turbines (American Wind and Wildlife Institute, 2021[97]). The increasing understanding of collision risk factors is helping industry to design effective mitigation measures (Box 3.1).

While collision mortality has been most studied for birds and bats, it has also been observed for insects. One study estimates annual insect mortality from onshore wind turbines in Germany to be 1.2 trillion, equivalent to 40 million insects per turbine per year (Voigt, 2021[132]). Given documented declines in insect biomass (Hallmann et al., 2017[133]; Sánchez-Bayo and Wyckhuys, 2019[134]), further study to better understand how and to what extent wind turbines impact insect species would be justified.

For marine life, the risk of collision with offshore wind turbine foundations is likely low (Inger et al., 2009[135]). The greater risk of collision may arise from increased boat activity during surveying, construction, servicing or decommissioning of facilities. Marine mammals and turtles are at particular risk of boat collision (Maxwell et al., 2022[86]). Boat collision is a known cause of mortality and injury; it may lead to population-level effects in areas where vessel activity is already high (Rockwood, Calambokidis and Jahncke, 2017[136]). Vessel activity, and therefore collision risk, may be lower for floating offshore than for fixed offshore, as most of the construction can occur onshore (Maxwell et al., 2022[86]).

While vessel-collision risk may be lower at floating offshore wind facilities than fixed-bottom facilities, the risk of entanglement with underwater cables and mooring lines is higher (Wilson, 2006[137]; Maxwell et al., 2022[86]). Primary entanglement, where a species is entangled directly in the cables or lines themselves, has not been observed to date. The risk of primary entanglement is likely highest where catenary moorings are used because they have more slack than other mooring approaches. Secondary entanglement, where an animal gets entangled in fishing gear or other marine debris caught on cables or mooring lines, is likely to represent a greater risk than primary entanglement. Vulnerable species include those with large appendages such as humpback whales (Megaptera novaeangliae) and leatherback sea turtles (Dermochelys coriacea), diving sea birds, elasmobranchs and fish (Maxwell et al., 2022[86]). While no evidence exists of secondary entanglement at offshore wind facilities, entanglement particularly with ghost fishing gear, is widely documented and poses a significant threat to cetaceans and other marine life (OECD, 2021[138]). Monitoring and mitigating secondary entanglement could be important as offshore wind facilities develop, as it may have a population-level impact for some species (Maxwell et al., 2022[86]).

In addition to direct mortality, wind energy deployment can lead to habitat loss, species displacement and barrier effects on species. As discussed above, wind turbine facilities tend to be extensive but their direct physical footprint from the construction of permanent infrastructure (e.g., wind turbine pads, power substations and access roads) is relatively small.

Nonetheless, the construction of wind energy facilities can contribute to direct habitat loss and degradation as a result of vegetation removal (including deforestation), soil erosion and compactness, and changes in hydrology (Dhar et al., 2020[150]; Dai et al., 2015[151]; Tabassum-Abbasi et al., 2014[152]). In Scotland for example, 6 994 hectares of public forestry, amounting to 1.7% of national forests, have been cleared for wind farm development between 2000 and 2019. This figure does not account for the additional privately-owned forests cleared for wind farms (Scottish Government, 2020[153]). A study of wind turbines in Romania found a significant difference between the diversity of rare, endemic and threatened plants inhabiting areas disturbed by the turbines and surrounding undisturbed areas. The study demonstrated that plant recovery after wind energy farm construction was incomplete after ten years of low-intensity plant restoration and conservation activities (Urziceanu et al., 2021[154]).

The foundations, anchors and electrical cables of offshore wind farms alter benthic habitat, affecting primarily benthic species, but also coastal and pelagic species that depend on benthic habitat for part of their lifecycle (e.g. egg-laying) (Maxwell et al., 2022[86]; SEER, 2022[87]). Habitat loss occurs at the interface of wind energy infrastructure and the sea floor. This is a small area, but the impact could cumulate across turbines and wind energy facilities. The extent of habitat loss depends on the technology. For example, fixed-bottom turbines have a larger physical footprint on the seabed than floating wind turbines. Gravity foundations have a base up to 30 m in diameter, while jacket foundations have three cylindrical legs each of a few metres in diameter (SEER, 2022[87]).

Installation of anchors, foundations and cables can also temporarily disturb or degrade habitats. The extent and significance of these impacts depends on the technology (e.g. type of foundation, anchor and mooring line), method (e.g. whether cables are buried or protected), and local conditions (e.g. sediment type) (Maxwell et al., 2022[86]). In some cases, disturbance may continue throughout the project lifetime. For example, catenary mooring lines may drag across the sea floor. Unlike for habitat loss, the seabed can naturally recover (at least partially) from disturbance (Maxwell et al., 2022[86]). The rate of recovery is typically faster for shallower water with soft bottoms as they are more dynamic (SEER, 2022[87]).

The construction of wind energy facilities can fragment habitats, leading to a host of impacts (see discussion under solar energy). While the spatial footprint of wind turbine infrastructure such as access roads may not be large, they can have a disproportionate impact on habitat connectivity. A study of 39 wind facilities, for example, found that new facilities decreased the amount of undeveloped land by 1.8% but changed metrics of landscape pattern from 50-140% (Diffendorfer et al., 2019[155]). The extent of pre-construction development can play a key role in determining overall impact of a wind energy facility. Utilising existing development reduced habitat fragmentation.

Wind turbines can also provide a barrier effect to species if they are located on paths used to access foraging or breeding grounds, or for migration. Various species of birds have been observed to change their flight paths to avoid flying through wind energy facilities (Cabrera-Cruz and Villegas-Patraca, 2016[156]). The impact of barrier effects is likely greatest on migratory species, as adjusting flight paths to avoid (often multiple) wind energy facilities (and potential rest stops), may burn scarce energy reserves. Barrier effects for non-volant species may occur if the wind energy facility is fenced.

The new substrate provided by turbine foundations can also create new habitat for fish and marine invertebrates (ter Hofstede et al., 2022[157]). Several studies have documented the establishment of communities on offshore turbine foundations (Lindeboom et al., 2011[158]) (De Mesel et al., 2015[159]). Turbines have also been proved to provide refuge for fish (Bergström, Sundqvist and Bergström, 2013[160]; Langhamer, 2012[161]). In the Netherlands’ North Sea, the Flat Earth Consortium pilot launched by the Ministry of Economic Affairs of the Netherlands and the World Wide Fund for Nature (WWF) aims at further enhancing this effect by adding artificial reef structures in areas around turbine foundations that have been damaged by trawling (Didderen, 2019[162]). The reef effect can, however, be both positive and negative for biodiversity. It is important to consider the historical context (i.e., has there been past loss of hard substrate habitats), carefully assess impacts on communities and ecosystem services, and monitor impacts (e.g., potential colonisation by invasive non-native species). Furthermore, it is necessary to consider the long-term implications of decommissioning infrastructure (e.g., whether infrastructure supporting new reef structures should be removed) (European Commission, 2020[89]).

Species respond differently to the physical presence and noise of wind energy facilities. Some are unaffected, some appear to be attracted to the facilities, while other species avoid wind energy facilities (Łopucki, Klich and Gielarek, 2017[163]; Lindeboom et al., 2011[158]). Non-species-specific factors, such as season (Peschko et al., 2020[164]), wind-turbine location and extent of land-use change (Fernández‐Bellon et al., 2018[165]), may affect the magnitude and direction of species responses.

Species displacement (effectively habitat loss), owing to avoidance of wind energy facilities may have a more extensive impact on biodiversity than direct habitat loss through clearance. According to one estimate, direct habitat loss through clearing only accounts for 3-5% of wind turbines’ impact area, while most of their impact area is due to habitat fragmentation and species avoidance behaviour (McDonald et al., 2009[78]).

Avoidance of onshore wind energy facilities has been observed for a number of species, and is particularly well-documented in birds and bats (Fernández‐Bellon et al., 2018[165]) (Shaffer and Buhl, 2015[166]) (Pearce-Higgins et al., 2009[167]) (Pearse et al., 2021[168]; Therkildsen et al., 2021[169]). A study of 130 black kites (Milvus migrans) at the migratory bottleneck of the Strait of Gibraltar found that the birds avoided areas up to approximately 674 m from operating wind turbines and an estimated 3-14% of suitable soaring area (Marques et al., 2019[170]). Another study found that activity within 1 000 m of wind turbines by gleaners and fast-flying bats is reduced by 54% and 20%, respectively (Barré et al., 2018[171]). A multi-site study of several avian species in the UK suggested that displacement impacts during construction may be as or even more important than displacement triggered by turbine operations (Pearce-Higgins et al., 2012[172]).

Although less-studied, evidence of species avoiding operating wind energy facilities also exists for non-volant terrestrial mammals, such as pronghorn (Antilocapra americana) in the US (Smith et al., 2020[173]; Milligan et al., 2023[174]), reindeer (Rangifer tarandus) in Sweden (Skarin, Sandström and Alam, 2018[175]), European hare (Lepus europaeus) and roe deer (Capreolus capreolus) in Poland (Łopucki, Klich and Gielarek, 2017[163]), wolves (Canis lupus signatus) in Portugal (Skarin, Sandström and Alam, 2018[175]; Łopucki, Klich and Gielarek, 2017[163]), blackbuck (Antilope cervicapra), chinkara (Gazella bennettii), golden jackal (Canis aureus) and jungle cat (Felis chaus) in India (Kumara et al., 2022[176]). Subsoil biodiversity can also be affected by wind energy facilities. For example, in the Netherlands, earthworms were less abundant close to wind turbines, likely due to their avoidance of vibratory noise associated with wind turbine operation (Velilla et al., 2021[177]).

Offshore wind facilities have also been observed to affect species behaviour. The construction phase is when most displacement of marine mammals can be observed, owing to pile-driving noise (Box 3.1). Displacement of harbour porpoises (Phocoena phocoena) (Dähne et al., 2013[178]; Brandt et al., 2018[179]; Graham et al., 2019[180]) and harbour seals (Phoca vitulina) (Russell et al., 2016[181]), have been well-documented. However, other cetaceans and pinnipeds as well as fish are also likely affected by construction noise (Kok et al., 2021[182]; Bailey, Brookes and Thompson, 2014[183]).

The operation phase of offshore wind turbines can displace bird species, similar to onshore wind turbines (Lindeboom et al., 2011[158]; Peschko et al., 2020[164]). Displacement of non-avian species owing to offshore wind turbine operations has been less studied. A seven-year monthly demersal trawl survey using a Before-After-Control-Impact (BACI) design found that relative decreases in fish and invertebrate abundances during wind farm operation were neither statistically nor substantively evident. Some species (e.g., black sea bass) had significantly higher catch per unit effort, consistent with the artificial reef effect (Wilber et al., 2022[184]).

Species displacement can be temporary (e.g., during construction or while species become accustomed to the operation of wind turbines), or it could persist throughout the lifetime of the wind energy facility. The impact of temporary displacement is likely to depend on when it occurs (e.g. impacts could be particularly high during breeding season) (Pearce-Higgins et al., 2012[172]). Accounting for seasonal and daily movement patterns of species of concern in the construction schedule (e.g., scheduling road construction or underwater piling outside breeding seasons) could help reduce construction phase impacts.

In addition to avoidance behaviour, species may experience higher levels of stress around wind energy facilities. For example, roe deer close to wind energy facilities were found to have higher levels of the stress hormone cortisol (Klich et al., 2020[185]), while wolves close to wind energy facilities were found to have lower reproduction rates (Ferrão da Costa et al., 2017[186]). Male Japanese tree frogs living close to wind turbines were found to have a higher call rate and corticosterone levels and lower immunity than frogs from control sites without turbines during the breeding season (Park and Do, 2022[187]).

Knowledge gaps remain regarding the behavioural and physiological responses of species to wind turbine facility construction and operation, and how this effects ecosystem structure and function. In addition to continued study of volant species responses, further studies of the responses of non-volant terrestrial and marine species, in particular fish and invertebrates,5 and a variety of ecosystems6 could help create a fuller picture of wind energy impacts and help inform mitigation.

Ecological communities may be affected at wind energy facilities by the introduction or spread of invasive alien species (IAS). The movement of people, construction material and equipment provide a vector for IAS. For example, in the case of offshore wind facilities, increased vessel activity for construction and maintenance could introduce non-native species to wind facility sites. Marine vessels are well-known vectors of IAS, which they transport via hull fouling and ballast water exchange (Costello et al., 2022[191]). Additionally, the degradation or alteration of habitats from wind turbine construction could make ecosystems more susceptible to the spread of non-native and invasive species. For example, operational monitoring at the Serra da Lousã onshore wind facility in Portugal found two new IAS present. Two other IAS, already present at the site, had spread along access roads and turbine pads (Passo, 2017[192]). Offshore wind turbines require anchors, pilings or foundations that can alter benthic habitats, providing a potential niche and stepping-stone for invasive alien species (Adams et al., 2014[193]).

Wind energy facilities potentially affect the quantity or quality of provisioning, regulating, supporting and cultural ecosystem services, or people’s access to these services. A commonly reported concern is the impact of wind turbines on cultural values. The development of wind energy facilities can undermine the aesthetic value of landscapes, affecting land value and impacting tourism (Gibbons, 2015[194]; Dröes and Koster, 2021[195]; Voltaire and Koutchade, 2020[196]; Parsons et al., 2020[197]). For example, the installation of offshore wind facilities in Catalonia, Spain could affect preferences for beach trips by residents and tourists and result in a loss of welfare (Voltaire and Koutchade, 2020[196]). Although declines in tourism could reduce pressure on other ecosystem services, underscoring the potential for trade-offs across ecosystem services.

The land-use change associated with wind farm deployment can also undermine an ecosystem’s ability to sequester and store carbon. For example, the construction of 3 848 wind turbines in Scotland led to 4.9 million tonnes of CO2 emissions because of land use change. Emissions vary from turbines across Scotland vary from 16 g CO2/kWh in shrubland to 1 760 g CO2/kWh in peatland (Albanito et al., 2022[198]).

Where wind energy is deployed in agricultural land or fishing grounds, it may negatively affect provisioning services. For example, in some jurisdictions, fisheries cannot or can only partly access offshore wind farms. Some offshore wind facilities overlap with existing fishing grounds, presenting an opportunity cost. For example, 90% of Danish and 40% of German annual plaice landings in the German EEZ overlap with areas where offshore wind farms are and will be developed (Van Hoey et al., 2021[199]). International gillnet fisheries could lose up to 50% in landings within the North Sea German EEZ. In theory, part of the loss to fisheries could be compensated by fishery displacement (see indirect impacts) and, in the longer term, potential spill over effects, where offshore wind facilities act as marine protected areas allowing populations to thrive and then spill over to surrounding areas where they could bolster fishing (Van Hoey et al., 2021[199]; Ashley, Mangi and Rodwell, 2014[200]).

Reduced prevalence of some species in and around wind energy facilities may have extensive, albeit poorly understood knock-on effects on ecological communities (Keehn and Feldman, 2018[201]). Long-term monitoring is required to identify and understand the extent of these impacts. One mechanism by which knock-on effects can occur is cascading impacts, whereby declines in species in higher trophic levels affects those in lower trophic levels. For example, a long-term study in the Western Ghats, India, found that both the abundance of predatory birds and the frequency of predation attempts by raptors on ground-dwelling prey were almost four times lower in sites with wind turbines (Thaker, Zambre and Bhosale, 2018[202]). The density of the endemic superb fan-throated lizard (Sarada superba) was significantly higher in sites with wind turbines. Furthermore, the lizards in wind sites showed physiological, behavioural and morphological differences consistent with the effects of predator release. A study of bat mortalities in wind turbines in Germany concluded that may lead to the loss of trophic interactions and ecosystem services, contributing to functional simplification and impaired crop production, respectively (Scholz and Voigt, 2022[203]).

The construction and operation of wind energy facilities may have indirect impacts by displacing other activities. For example, a 25-fold increase in offshore wind energy is expected in the North and Baltic Seas by 2050, potentially competing with fisheries and aquaculture. Fishermen tend to respond by displacing fisheries or by switching fishing gear (e.g., mobile gear to crab or lobster potting) (EC, 2021[204]). This could increase fishing pressure elsewhere, with potential implications for biodiversity.

The cumulative impacts and population-level effects of multiple wind energy developments (and other human pressures) remain understudied and poorly understood. While current levels of mortality from wind turbine collision are thought to have negligible impacts on the populations of many of the affected species, some species could face significant cumulative impacts and population-level effects. Migratory birds and bats are likely to be at particular risk of cumulative impacts as they may cross the paths of multiple wind farms. Furthermore, bats, and some of the groups of bird species demonstrating the highest risk of collision (e.g. Accipitriformes, Bucerotiformes, Circoniformes), tend to be species with long lifespans, low fecundity and late ages of maturity, which makes them particularly sensitive to additional mortality (Thaxter et al., 2017[108]).

A recent assessment of the vulnerability of populations of 23 priority bird species killed at wind and solar facilities in California, USA, concluded that 48% were vulnerable to population-level effects from additional mortalities caused by renewables and other sources. Notably, the study found that Californian renewable energy facilities could have population-level effects not only for local subpopulations but also for non-local subpopulations (e.g. distant subpopulations of migratory species) (Conkling et al., 2022[80]).

Based on expert elicitation and population models, (Frick et al., 2017[205]) concluded that wind energy development could have significant population-level impacts on migratory bats in North America, with the hoary bat population declining by as much as 90% in the coming 50 years. The impact on populations of rare and already threatened species are also of particular concern. For example, the little brown myotis (Myotis lucifugus), which was listed as Endangered in 2014 under the Species At Risk Act (SARA), accounted for 13% of all mortalities from wind turbines in Canada and 87% of mortalities in Ottawa (Zimmerling and Francis, 2016[206]).

A global review of bat multiple mortality events (MMEs), defined as cases in which ≥ 10 dead bats were counted or estimated at a specific location within a maximum timescale of a year, identified collision with wind turbines as the leading cause of reported MMEs in bats, alongside white-nose syndrome (O’Shea et al., 2016[207]). Owing to their important role in ecosystem function and ecosystem service provision (see Box 3.3), the cumulative impact on bats of turbine collision, white-nose syndrome (for North American bats), and other threats such as habitat loss, hunting for bushmeat and climate change is a conservation concern (Frick, Kingston and Flanders, 2019[208]).

A growing body of literature examines population-level impacts and identifies species whose populations are most likely to be significantly affected (see e.g. (Diffendorfer et al., 2021[209])). Long-term studies of wind turbine collisions and of population dynamics (particularly for bats, as these are less well understood) are critical for improving understanding of population-level impacts. Cumulative impacts of offshore wind energy facilities also warrant further exploration (see (Brignon et al., 2022[210]) for priority research areas).

The electricity system relies on transmission and distribution lines to transfer power from the source to the end-user. Transmission systems are designed to transfer higher voltages over long distances, from the site of energy generation to a substation. Distribution lines carry lower voltages over shorter distances from the substation to end-users (Biasotto and Kindel, 2018[212]). Existing power line networks consist predominantly of overhead lines, but also of underground cables.

A double trend is increasing the need for long-distance power transfers and the associated power line infrastructure. First, deeper market integration with increasing interregional and international trade in electricity implies that greater amounts of electricity have to be transported across large distances (van der Weijde and Hobbs, 2012[213]) (Pollitt, 2009[214]). This is especially the case in the European market where market liberalisation encourages cross-border electricity transfers (Brown, 2015[215]). Second, the increased use of renewable sources of electricity worldwide requires soothing the allocation of power across large areas, as such sources are often located in remote areas far from load centres and as the availability of wind and solar in particular is intermittent (van der Weijde and Hobbs, 2012[213]). Weather-dependent electricity also increases situations where excess local generation must be exported to balance demand and supply across regions (Brown, 2015[215]).

The IEA Net Zero pathway estimates that investment in electricity networks will need to increase to USD 820 billion/year by 2030 from about USD 260 billion/year in 2021 (IEA, 2021[216]). This would ensure the provision of large amounts of power line infrastructure as well as the modernisation of existing assets. Europe for instance, already houses 300 000 km of transmission lines and 10 million km of distribution lines (similar scales are found in the US) (IEA ETSAP, 2014[217]), and the EU has set the target of increasing the interconnectivity of national power grids by 15% by 2030 requiring an estimated 44 700 km of new or refurbished transmission lines (EU, 2019[218]).

While networks consist predominantly of overhead lines, underground and subsea cable technology is increasingly being deployed. From 2010-14, 8 000 km of subsea and underground lines were installed globally (Europacable, 2021[219]).

The scientific literature and the body of environmental impact studies evaluating the potential impacts on biodiversity of transmission and distribution lines are well developed, particularly for birds. However, knowledge gaps remain, particularly for impacts on non-avian species (e.g., amphibians), habitats and ecosystems (Biasotto and Kindel, 2018[212]). The scientific literature mainly covers the impact of overhead transmission lines, with fewer studies examining the impacts of distribution lines, which constitute a significantly larger network, and underground cables (Bernardino et al., 2018[220]).

One of the direct impacts of power lines is bird mortality caused by collision and electrocution. Collision risk is primarily associated with transmission lines, while electrocution risk is greatest for distribution lines. Overall, power lines are estimated to kill hundreds of thousands to millions of birds every year, including threatened species (Loss, Will and Marra, 2014[221]; Loss, Will and Marra, 2015[222]; Rioux, Savard and Gerick, 2013[223]). Several studies indicate that mortality induced by power line collision can have significant population-level impacts for some species (Schaub and Pradel, 2004[224]; Schaub et al., 2010[225]; Loss, Will and Marra, 2012[226]).

Some species are particularly prone to collision with power line. Species-specific factors such as type of vision, migratory behaviour and flight behaviour influence collision risk (Bernardino et al., 2018[220]). For example, species with high wing loading (i.e., weight to wing area ratio), such as bustards, storks, eagles, vultures and cranes, are at higher risk due to their low manoeuvrability. Site-specific factors also influence collision risk. Power lines that are placed perpendicular to major migratory corridors pose high risks for species on migration (Shobrak, 2012[227]). Similarly, power lines that cross important bird habitats such as wetlands and coastal areas are assumed to pose higher collision risks (Adrushchenko and Popenko, 2012[228]). Finally, pylon and wire characteristics are thought to influence power line bird collisions. There is a general agreement that wire height, number of levels of wire, wire diameter and presence of earth wires may influence bird collision rates (Bernardino et al., 2018[220]). However, very few studies manage to isolate one specific characteristic and its correlation with bird mortality.

Electrocution occurs predominantly at low to medium-voltage power lines. High voltage power lines tend not to have live and earthed components sufficiently close for an animal to touch both at once. The technical design of electricity transmission and distribution infrastructure (e.g., distance between exposed wires and other energised or grounded elements, and how insulators are attached to cross-arms), is a key determinant of risk (RPS, 2021[229]). Birds that use pylons for nesting or foraging are vulnerable, particularly if they are medium-sized or large birds likely to touch multiple exposed elements (Guil et al., 2011[230]; Tintó, Real and Mañosa, 2010[231]; Lehman, Kennedy and Savidge, 2007[232]).

Electrocution has been identified as the main cause of population decline for several avian species (Biasotto and Kindel, 2018[212]). It is of particular concern for threatened species and long-lived species. In Iran, 15% of the 235 birds reported to be electrocuted in 2018 were species of conservation concern, including the steppe eagle (Aquila nipalensis) and the Egyptian vulture (Neophron percnopterus) (Kolnegari et al., 2020[233]). In Southern Europe, electrocution poses risks to the viability of populations of Bonelli’s eagle (Aquila fasciata), even though mortality rates from power lines are low (Hernández-Matías et al., 2015[234]).

While the literature on electrocution from power lines focuses particularly on avian electrocutions, power lines also electrocute other taxa, including mammals and reptiles (e.g., snakes). Electrocutions of various primate species across Asia, Africa and Latin America have been documented (Katsis et al., 2018[235]). Among these species are threatened species, such as the critically endangered Javan slow loris (Nycticebus javanicus) (Moore, Wihermanto and Nekaris, 2014[236]) and the western purple-faced langur (Trachypithecus vetulus nestor) (Moore, Nekaris and Eschmann, 2010[237]; Parker, Nijman and Nekaris, 2008[238]). Electrocution has been a principal mortality factor for the endangered Central American squirrel monkey subspecies Saimiri oerstedii citrinellus and Saimiri oerstedii oerstedii (Boinski et al., 1998[239]).

Knowledge gaps remain concerning risk factors for collision and electrocution. Furthermore, the evidence base is geographically skewed. According to a recent review (Guil and Pérez-García, 2022[240]), most (80%) studies of bird electrocution at power lines are from developed countries, mostly in Europe and North America. No systematic studies exist for Oceania, and few exist for South America and Africa. Additionally, while evidence for the effectiveness of some mitigation measures exists, many widely accepted mitigation measures have not been consistently tested or have yielded very different results (Biasotto and Kindel, 2018[212]). Examples of mitigation measures and their evidence base is provided in Box 3.4.

Installing and maintaining overhead power lines can require clearing and managing vegetation in the zone situated below the cables (the right of way - RoW), to avoid interference and risks to the cables. The extent of habitat loss and degradation depends on the location and sensitivity of the affected habitat, the size of the project (e.g., higher voltage cables tend to require larger RoW) and the design of the project. Although generally of a small width, the RoW constitutes linear habitat loss or degradation over hundreds of kilometres. Furthermore, destroying or degrading habitat under power lines could have wider ecosystem effects by affecting hydrological regimes and exacerbating erosion. Studies of habitat loss and degradation from power line construction are, however, scarce. Habitat fragmentation and species avoidance (effective habitat loss) have been better studied for power lines (Biasotto and Kindel, 2018[212]).

RoWs can fragment habitats, leading to edge effects. Clearance of forest for power lines, for example, has been found to create microclimatic edge gradients qualitatively like those observed at forest edges adjacent to larger clearing (Pohlman, Turton and Goosem, 2009[248]). These microclimatic edge gradients can negatively impact interior forest plant species, while favouring disturbance-adapted plants, thereby leading to changes in ecological communities (Pohlman, Turton and Goosem, 2009[248]; Prieto et al., 2013[249]). Changes in fruiting phenology of species have also been observed at linear edges in the Atlantic Forest, with potential consequences for plant-seed disperser interactions (Reznik, Pires and Freitas, 2012[250]).

For small arboreal mammals, such as the lemuroid ringtail possum (Hemibelideus lemuroides), the loss of canopy connectivity resulting from power line construction in forests significantly limits their movements and could therefore fragment their population (Goosem and Marsh, 1997[251]; Wilson, Marsh and Winter, 2007[252]). Other taxa, such as salamander, may also be negatively impacted through the barrier effect created by power lines (Cecala, Lowe and Maerz, 2014[253]).

While habitat loss and fragmentation are generally negative for biodiversity, in some contexts power line deployment can benefit native and threatened species by creating new habitats. For example, various bird species, including threatened species, use pylons for nesting and foraging (Biasotto and Kindel, 2018[212]; Arkumarev et al., 2014[254]). Others, such as scrub-shrub birds have been found to successfully nest in RoW (King et al., 2009[255]). Use of RoW may allow some species to increase their range and population size (Dixon et al., 2013[256]; Howe, Coates and Delehanty, 2014[257]), although it may increase electrocution risk.

Non-avian taxa may also benefit from RoWs. For example, rare grassland species in North America and the gastropods (e.g. snails and slugs) that depend on them have been found to benefit from the clearance and maintenance of vegetation in RoWs (Nekola, 2012[258]). The open habitats created by power line construction and operation in Central Europe supports relatively high insect diversity (Plewa et al., 2020[259]). They also provide a corridor for certain species, such as large carnivores, to move across the landscape (Clarke, Pearce and White, 2006[260]; Bartzke et al., 2014[261]; Smith et al., 2008[262]). Positive impacts may occur when RoWs facilitate movement of native species across the landscape. Large carnivores, for example, have been found to prefer moving along RoWs (Bartzke et al., 2014[261]; Smith et al., 2008[262]). These mechanisms that benefit native and threatened species may also benefit invasive alien species and lead to their spread (see discussion below).

Whether the net benefit for biodiversity is positive or negative depends on the local context. (Eldegard, Totland and Moe, 2015[263]) suggest that management plans for power lines should differentiate between clearing through high conservation value forests where edge effects should be limited and clearings that can act as replacement habitat.

The presence of power lines may lead to species displacement (effective habitat loss) or provide a barrier to species movement. For example, displaying male bustards were found to reject sites within 350-400 m to medium voltage power lines. Relative rejection of potential displaying sites was estimated to be up to 3 500 m from power lines (Lóránt and Vadász, 2014[264]). Other studies have shown grassland bird species avoiding areas up to 6 000 m from power lines (Pruett, Patten and Wolfe, 2009[265]; Gillan et al., 2013[266]), and concluded that the presence of power lines contribute to abandonment of certain territories by Bearded Vulture (Krüger, Simmons and Amar, 2015[267]). Nesting and roosting sites (Santiago-Quesada et al., 2014[268]; Silva et al., 2010[269]) and demographic rates (e.g. nest survival, recruitment and population growth) (Gibson et al., 2018[270]) of some bird species have also been found to be negatively influenced by power lines. Avoidance behaviour has also been documented in ungulates, such as reindeer and white-tailed deer (Bartzke et al., 2014[261]; Rieucau, Vickery and Doucet, 2009[271]; Nellemann et al., 2001[272]).

In addition to their physical presence, power lines can affect species through noise and electromagnetic fields (EMF). The potential disturbance through noise during the construction phase of power lines are mentioned in several environmental impact statements for power line developments (Biasotto and Kindel, 2018[212]). (Colman et al., 2015[273]) suggest that disturbance through noise may temporarily reduce the presence of reindeer around the construction site. However, during the operational phase, noises associated with clicks or energy discharges in power lines are limited and their effect on wildlife is uncertain.

While impacts of EMF have been observed, relatively little is known about their extent and significance (Biasotto and Kindel, 2018[212]). Observed impacts of EMF include physiological impacts, such as altered development, behavioural effects (e.g. attraction, avoidance), and impaired navigation and orientation (Farr et al., 2021[274]; Biasotto and Kindel, 2018[212]). For terrestrial species, evidence exists of reproductive effects in birds (Fernie and Reynolds, 2005[275]; Tomás et al., 2012[276]), behavioural changes in ruminants (Burda et al., 2009[277]) and physiological changes in plants (e.g. increased genetic mutations and altered enzymatic activity) (Aksoy, Unal and Ozcan, 2010[278]; Mahmood et al., 2013[279]). In the marine environment, elasmobranchs, crustacea, cetacea, bony fish, and marine turtles, have been shown to be sensitive to EMF (Copping and Hemery, 2020[280]; Gill et al., 2014[281]). For example, a recent study of two commercially important lobster species (H. gammarus and C. pagurus) concluded that EMF emissions from subsea power cables could have a measurably affect their early life history and consequently population dynamics (Harsanyi et al., 2022[282]).

Owing to the rapid growth in offshore wind, further research into the EMF impacts from power lines in the ocean would be beneficial. Floating offshore wind may require long distance cables transmitting high voltage direct current, which typically emits high intensity magnetic fields over a greater spatial scale compared to alternating current.

The degradation of habitats or alteration of habitats resulting from power line construction and maintenance of RoW can create conditions for invasive alien species to colonise and disperse along RoW corridors (Biasotto and Kindel, 2018[212]). As with solar and wind energy, few studies examine the role of power lines in facilitating invasive alien species. The extent to which power lines support IAS is likely to be context specific. A study in Quebec, Canada concluded that power lines were efficient dispersal vectors of invasive plant species in fen but not bogs (Dubé, Pellerin and Poulin, 2011[283]). A Finnish study found that power line sites that supported alien species were characterised by productive soils light, surrounded by a dense urban fabric (Lampinen, Ruokolainen and Huhta, 2015[284]).

Pylons that provide perching, roosting or nesting sites for birds may facilitate spread of invasive plans species as these are also defecation sites. A study of black cherry (Prunus serotines), an invasive plant species in agricultural land in Europe, found high abundance under electricity pylons. A survey of 124 areas under pylons and 124 paired control plots in agricultural land found the plant in 82% of electricity pylons and 2% in control plots. The land under the pylons was relatively untouched compared to intensively managed agricultural land and therefore provided a refuge for the plant (Kurek, Sparks and Tryjanowski, 2015[285]).

The construction of power lines could facilitate access to previously unexploited areas, potentially threatening biodiversity. Indirect impacts from the construction of linear infrastructure, particularly roads, are well-documented albeit not often quantified (Barber et al., 2014[286]; Richardson et al., 2017[287]). While evidence of the induced impacts of power lines is slim, studies hypothesise that their construction can lead to increased deforestation (Hyde, Bohlman and Valle, 2018[288]) and hunting (Bartzke et al., 2014[261]).

Another indirect impact that can occur from power line construction and operation is increased fire risk and associated habitat loss. This is of particular concern given the increasing risk of forest fires under climate change (OECD, 2023[289]). Power line construction in forests could alter the vegetation community structure and composition at the edges of the utility corridor, and alter the microclimate, increasing the risk of forest fires igniting (Hyde, Bohlman and Valle, 2018[288]). Power lines can also be the ignition of wildfires. For example, in California, US, power lines are estimated to cause about 10% of wildfires. Power line ignitions can occur from high winds that cause wires to touch, debris blown into power lines and wildlife interactions (nest material or animals bridging wires). At least 44 wildfires during 2014-18 were ignited by avian electrocutions in the contiguous US (i.e., excluding Hawaii and Alaska) (Barnes et al., 2022[290]).  IAS in RoW can also increase fire risk (Cho, Malahlela and Ramoelo, 2015[291]). This underscores the importance of considering biodiversity in the planning, design, operation and maintenance of transmission and distribution infrastructure.

Little evidence exists of the cumulative impacts of extensive transmission and distribution electricity networks on biodiversity. However, studies suggest that cumulative impacts could be significant in some ecosystems and deserve consideration. In the Amazon region, for instance, close to 40 000 km of transmission and distribution lines have been built, directly impacting approximately 23 000 km2 of land (Hyde, Bohlman and Valle, 2018[288]). The transmission network in the Legal Amazon region is expected to be extended further, affecting intact forests and protected areas. Long-term studies of habitat fragmentation have highlighted the negative, synergistic nature of anthropogenic threats on the Amazon (Laurance et al., 2011[292]).

A study of the cumulative direct and indirect impacts of power lines in a 573 500 ha area of coastal New South Wales, Australia, concluded that the spatial footprint of power lines was <1% of landscape while the direct and indirect impacts accumulated to ~2% (10 103 ha). When also combined with roads, ~8% (33 780 ha) of habitat in the study area was potentially affected (C. Strevens, L. Puotinen and J. Whelan, 2008[293]).

The cumulative impacts from collision, electrocution and barrier effects on migratory species is also of concern. In addition to power lines, migratory birds are likely to be confronted by wind energy facilities and other human threats across their flyway. The potential for cumulative impacts on migratory species indicates the importance of international co-operation.

The evidence for adverse biodiversity impacts from the construction, operation and decommissioning of solar and wind energy facilities and power lines underscores the importance of considering biodiversity when expanding renewable power. As the boxes in this section have highlighted, impact mitigation measures exist and are being increasingly deployed (for a comprehensive overview of mitigation measures see (Bennun et al., 2021[1])). Through effective mainstreaming of biodiversity into power system planning (see Chapter 4) and appropriate policy mixes (see Chapter 5) governments can help ensure effective mitigation of these impacts and promote positive outcomes for biodiversity in renewable power projects.

Infrastructure for renewable power generation, transmission and distribution (and other low-emission technologies such as electric vehicles and batteries), place considerable demand on mineral resources. While the transition to low-emissions electricity systems will reduce coal mining, it will put increased pressure on other (critical) minerals. Low-emission technologies are becoming the fastest growing segment of mineral demand (IEA, 2021[294]), which is itself projected to increase (OECD, 2019[295]).

The extent to which the expansion of renewable power infrastructure drives up demand for minerals will depend in part on the specific technology used, material efficiency gains and the extent to which components are recycled. For example, silver and silicon metal currently dominate the solar market but are not recuperated at the end of life, unlike copper (MTE, 2020[296]).

The dependency of low-emissions infrastructure on critical minerals brings a host of economic (e.g. risk of supply chain rupture; geopolitical risks), social (e.g. human rights) and environmental challenges (IEA, 2021[294]; MTE, 2022[297]; MTE, 2020[296]; MTE, 2020[298]) (OECD, 2016[299]), one of which is mitigating the biodiversity impacts of mineral extraction and processing.

In a net-zero scenario by 2050, mineral demand (tonnes) from low-emission technologies increases six-fold between 2020 and 20407 (IEA, 2021[294]). Most of the demand is for electric vehicles (EVs) and battery storage, followed by electricity networks, solar PV and wind. The material intensity and mineral requirements of infrastructure for electricity generation vary across technologies (Månberger and Stenqvist, 2018[300]). Offshore wind has the highest material intensity (i.e., kg/MW), followed by onshore wind, and solar PV. Nuclear, coal and natural gas all have lower material intensities (Figure 3.2) (IEA, 2021[294]).

Wind turbines comprise various materials including concrete, steel, iron, fibreglass, polymers, aluminium, copper, zinc and rare earth elements (neodymium, praseodymium, dysprosium, and terbium). Wind turbines and low-carbon transport are the largest consumers of rare earth magnets, at 10% and 25% of the global market respectively (MTE, 2022[301]). The material intensity of turbines depends on both turbine size and type. For example, direct drive turbines have greater mineral demand than gearbox models. Permanent magnet synchronous generator models (PMSG) have greater demand on rare earth elements than double-fed induction generators and electrically excited synchronous generators (IEA, 2021[294]). Offshore turbines tend to be larger than onshore turbines, explaining their higher mineral resource demand, and are typically direct drive PMSG, therefore placing greater demand on rare earth elements.

For solar PV, key mineral resources include copper, silicon and silver. Solar PV demand for copper is projected to almost triple by 2040 in a “well below 2 °C” scenario, while demand for silicon and silver increases by 45%, with material intensity reductions reducing demand growth (IEA, 2021[294]). CSP places substantial demand on chromium, copper, manganese and nickel resources. As with wind energy, the mineral demands and intensities depend on the specific technologies used (e.g., crystalline silicon (c-Si) modules, which are the dominant PV technology, or alternatives such as cadmium telluride (CdTe), copper indium gallium diselenide (CIGS) and amorphous silicon (a-Si)).

The core components of electricity networks are iron for supporting structures (for above ground cables), copper or aluminium for wires and cables, and concrete for the foundations (RTE, 2019[302]; IEA, 2021[303]). Grid expansion to meet growing electricity demand and the integration of renewable energies could lead to a doubling in demand for copper and aluminium from electricity grids by 2040 in a “well below 2 °C” scenario (IEA, 2021[294]).

The current production of many energy transition minerals is more geographically concentrated than that of oil or gas. For example, the top three producing nations for lithium (Australia, Chile, People’s Republic of China [China]), cobalt (Democratic Republic of Congo [DRC], Russia, Australia) and rare earth elements (China, United States, Myanmar), account for more than three-quarters of global output. DRC and China were responsible for approximately 70% and 60% of global production of cobalt and rare earth elements respectively in 2019 (IEA, 2021[294]). Other countries or regions with a high concentration of mining include Brazil, West Africa, India and Southeast and Central Asia. The regions with the highest extraction growth rates (between 7% and 10% per year) are in mining clusters in Peru, the DRC, Zambia, India, China, and in Western Australia (Luckeneder et al., 2021[304]).

This uneven spread of mining has implications for biodiversity. First, whereas biodiversity impacts from the installation and operation of renewable power facilities and electricity networks occur predominantly within the country consuming electricity (Holland et al., 2019[305]), the upstream impacts tend to occur elsewhere. Second, active mines and potential mineral reserves often overlap with areas of high biodiversity (Murguía, Bringezu and Schaldach, 2016[306]; Luckeneder et al., 2021[304]; Sonter et al., 2020[307]) and weak environmental governance (Lèbre et al., 2020[308]). Indeed, the past decade has seen a significant increase of mining in ecologically vulnerable regions (identified using terrestrial biome categorisations, protected areas and water scarcity as proxy indicators) (Luckeneder et al., 2021[304]), and there is substantial debate around deep-sea mining (Box 3.5).

An analysis based on nine metals (bauxite, copper, gold, iron, lead, manganese, nickel, silver and zinc), for example, estimated that 79% of global metal ore extraction in 2019 originated from five8 of the six most species-rich biomes9 (Luckeneder et al., 2021[304]). In absolute values, deserts and xeric shrublands were the most exploited terrestrial biome during the past twenty years, followed by tropical and subtropical moist broadleaf forests, and temperate broadleaf and mixed forests. Mining volumes in tropical moist forest ecosystems, which are the most biodiversity-rich ecosystems on the planet, doubled from 2000-2019. Moreover, half of global metal ore extraction in 2019 took place at 20 km or less from protected areas, and 8% took place within protected areas (Luckeneder et al., 2021[304]).

Mining (mineral extraction and processing) can impact biodiversity in multiple ways. The extent and significance of mining impacts depend on the mineral resource and extraction method, the local species and ecosystems where the mine is found, and the socio-economic and political context (Sonter, Ali and Watson, 2018[313]).

Habitat loss and degradation are among the main direct impacts of mining. Mining can directly remove, fragment, or degrade natural habitat (Yang et al., 2013[314]; Sonter et al., 2014[315]), with the affected area ranging from <1 to several dozen km2 in area, depending on the mineral being mined (Edwards et al., 2013[316]). This can have significant impacts on biodiversity. In Brazil, for example, mining has destroyed exceptionally diverse plant communities (Jacobi, do Carmo and de Campos, 2011[317]). Mining can also pollute air, land and water with gaseous waste (e.g. CO2, SO2, NOx), particulate matter and solid wastes (Appleton et al., 2006[318]; Dudka and Adriano, 1997[319]; N Yenkie et al., 2006[320]). For example, the Indonesian Grasberg copper and gold mine, which neighbours Lorentz National Park, a World Heritage Site, has been associated with pollution of rivers and lakes in the area due to riverine tailing disposal (Martinez-Alier, 2001[321]). While many of the impacts are at a site or landscape level, mining impacts can also occur at regional or even global level (Sonter, Ali and Watson, 2018[313]). For example, sediment export from mining in the Department of Madre de Dios in Peru degrades ecosystems along connecting rivers in Brazil (Asner et al., 2013[322]).

The expansion of roads and railways to support mining can lead to indirect impacts on biodiversity (Edwards et al., 2013[316]), as can urban expansion around mines (Sonter et al., 2017[323]). Mining in the Amazon, for example, was found to significantly increase forest loss up to 70 km beyond mining lease boundaries, causing 11 670 km2 of deforestation from 2005-15 (Sonter et al., 2017[323]). This deforestation is thought to result from several direct and indirect pathways including the establishment of mining infrastructure, urban expansion to support a growing workforce and the development of mineral commodity supply chains. Owing to the spatial concentration of critical minerals within landscapes and biomes, the cumulative direct and indirect impacts of multiple mining sites could be significant.

References

[110] Adams, J. et al. (2016), Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure, US Geological Survey, https://doi.org/10.3133/ofr20161154.

[228] Adrushchenko, Y. and V. Popenko (2012), Birds and Power Lines in Steppe Crimea: Positive and Negative Impacts, Ukraine. – Raptors Conservation 24, http://rrrcn.ru/en/archives/12268 (accessed on 20 July 2022).

[41] Aili, A. et al. (2022), “Radiative cooling and cold storage for concentrated solar power plants”, Energy Storage and Saving, Vol. 1/2, pp. 93-101, https://doi.org/10.1016/j.enss.2022.02.002.

[278] Aksoy, H., F. Unal and S. Ozcan (2010), “Genotoxic Effects Of Electromagnetic Fields From High Voltage Power Lines On Some Plants”, International Journal of Environmental Rsearch, Vol. 4/4, https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=182110 (accessed on 2 August 2022).

[198] Albanito, F. et al. (2022), “Quantifying the land-based opportunity carbon costs of onshore wind farms”, Journal of Cleaner Production, Vol. 363, p. 132480, https://doi.org/10.1016/j.jclepro.2022.132480.

[97] American Wind and Wildlife Institute (2021), Wind Energy Interactions with Wildlife and Their Habitats: A Summary of Research Results and Priority Questions, https://tethys.pnnl.gov/sites/default/files/publications/AWWI-Wind-Power-Wildlife-Interactions-Summary-2021.pdf.

[37] Añel, J. (ed.) (2012), “An Approach to Enhance the Conservation-Compatibility of Solar Energy Development”, PLoS ONE, Vol. 7/6, p. e38437, https://doi.org/10.1371/journal.pone.0038437.

[78] Añel, J. (ed.) (2009), “Energy Sprawl or Energy Efficiency: Climate Policy Impacts on Natural Habitat for the United States of America”, PLoS ONE, Vol. 4/8, p. e6802, https://doi.org/10.1371/journal.pone.0006802.

[33] Antonio Sánchez-Zapata, J. et al. (2016), “Effects of Renewable Energy Production and Infrastructure on Wildlife”, https://doi.org/10.1007/978-3-319-27912-1_5.

[318] Appleton, J. et al. (2006), “Impacts of mercury contaminated mining waste on soil quality, crops, bivalves, and fish in the Naboc River area, Mindanao, Philippines”, Science of The Total Environment, Vol. 354/2-3, pp. 198-211, https://doi.org/10.1016/j.scitotenv.2005.01.042.

[254] Arkumarev, V. et al. (2014), “Congregations of wintering Egyptian Vultures<i>Neophron percnopterus</i>in Afar, Ethiopia: present status and implications for conservation”, Ostrich, Vol. 85/2, pp. 139-145, https://doi.org/10.2989/00306525.2014.971450.

[230] Arlettaz, R. (ed.) (2011), “Minimising Mortality in Endangered Raptors Due to Power Lines: The Importance of Spatial Aggregation to Optimize the Application of Mitigation Measures”, PLoS ONE, Vol. 6/11, p. e28212, https://doi.org/10.1371/journal.pone.0028212.

[58] Armstrong, A., N. Ostle and J. Whitaker (2016), “Solar park microclimate and vegetation management effects on grassland carbon cycling”, Environmental Research Letters, Vol. 11/7, p. 074016, https://doi.org/10.1088/1748-9326/11/7/074016.

[11] Armstrong, A. et al. (2020), “Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees”, Environmental Research Letters, Vol. 15/11, p. 114055, https://doi.org/10.1088/1748-9326/abbf7b.

[129] Arnett, E. et al. (2008), “Patterns of Bat Fatalities at Wind Energy Facilities in North America”, Journal of Wildlife Management, Vol. 72/1, pp. 61-78, https://doi.org/10.2193/2007-221.

[140] Arnett, E. et al. (2010), “Altering turbine speed reduces bat mortality at wind‐energy facilities”, Frontiers in Ecology and the Environment, Vol. 9/4, pp. 209-214, https://doi.org/10.1890/100103.

[139] Arnett, E. et al. (2009), Effectiveness of changing wind turbine cut-in speed to reduce bat fatalities at wind facilities..

[200] Ashley, M., S. Mangi and L. Rodwell (2014), “The potential of offshore windfarms to act as marine protected areas – A systematic review of current evidence”, Marine Policy, Vol. 45, pp. 301-309, https://doi.org/10.1016/j.marpol.2013.09.002.

[322] Asner, G. et al. (2013), “Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring”, Proceedings of the National Academy of Sciences, Vol. 110/46, pp. 18454-18459, https://doi.org/10.1073/pnas.1318271110.

[109] AWWI (2019), Wind Turbine Interactions with Wildlife and Their Habitats A Summary of Research Results and Priority Questions Last Updated with Latest Publicly Wind Turbine Interactions with Wildlife and Their Habitats: A Summary of Research Results and Priority Questions, https://awwi.org/resources/summary-of-wind-power-interac- (accessed on 1 July 2022).

[90] Baerwald, E. et al. (2008), “Barotrauma is a significant cause of bat fatalities at wind turbines”, Current Biology, Vol. 18/16, pp. R695-R696, https://doi.org/10.1016/J.CUB.2008.06.029.

[141] Baerwald, E. et al. (2009), “A Large-Scale Mitigation Experiment to Reduce Bat Fatalities at Wind Energy Facilities”, Journal of Wildlife Management, Vol. 73/7, pp. 1077-1081, https://doi.org/10.2193/2008-233.

[183] Bailey, H., K. Brookes and P. Thompson (2014), “Assessing environmental impacts of offshore wind farms: lessons learned and recommendations for the future”, Aquatic Biosystems, Vol. 10/1, p. 8, https://doi.org/10.1186/2046-9063-10-8.

[286] Barber, C. et al. (2014), “Roads, deforestation, and the mitigating effect of protected areas in the Amazon”, Biological Conservation, Vol. 177, pp. 203-209, https://doi.org/10.1016/j.biocon.2014.07.004.

[290] Barnes, T. et al. (2022), “Wildland fires ignited by avian electrocutions”, Wildlife Society Bulletin, https://doi.org/10.1002/wsb.1302.

[171] Barré, K. et al. (2018), “Estimating habitat loss due to wind turbine avoidance by bats: Implications for European siting guidance”, Biological Conservation, Vol. 226, pp. 205-214, https://doi.org/10.1016/j.biocon.2018.07.011.

[114] Barrios, L. and A. Rodríguez (2004), “Behavioural and environmental correlates of soaring-bird mortality at on-shore wind turbines”, Journal of Applied Ecology, Vol. 41/1, pp. 72-81, https://doi.org/10.1111/j.1365-2664.2004.00876.x.

[54] Barron-Gafford, G. et al. (2016), “The Photovoltaic Heat Island Effect: Larger solar power plants increase local temperatures”, Scientific Reports, Vol. 6/1, https://doi.org/10.1038/srep35070.

[261] Bartzke, G. et al. (2014), “International Journal of Biodiversity and Conservation The effects of power lines on ungulates and implications for power line routing and rights-of-way management”, Vol. 6/9, pp. 647-662, https://doi.org/10.5897/IJBC2014.0716.

[1] Bennun, L. et al. (2021), Mitigating biodiversity impacts associated with solar and wind energy development: guidelines for project developers, IUCN, International Union for Conservation of Nature, https://doi.org/10.2305/iucn.ch.2021.04.en.

[45] Berger-Tal, O. and D. Saltz (2019), “Invisible barriers: anthropogenic impacts on inter- and intra-specific interactions as drivers of landscape-independent fragmentation”, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 374/1781, p. 20180049, https://doi.org/10.1098/rstb.2018.0049.

[160] Bergström, L., F. Sundqvist and U. Bergström (2013), “Effects of an offshore wind farm on temporal and spatial patterns in the demersal fish community”, Marine Ecology Progress Series, Vol. 485, pp. 199-210, https://doi.org/10.3354/meps10344.

[220] Bernardino, J. et al. (2018), “Bird collisions with power lines: State of the art and priority areas for research”, Biological Conservation, Vol. 222, pp. 1-13, https://doi.org/10.1016/j.biocon.2018.02.029.

[70] Bevk, T. and M. Golobič (2020), “Contentious eye-catchers: Perceptions of landscapes changed by solar power plants in Slovenia”, Renewable Energy, Vol. 152, pp. 999-1010, https://doi.org/10.1016/j.renene.2020.01.108.

[212] Biasotto, L. and A. Kindel (2018), “Power lines and impacts on biodiversity: A systematic review”, Environmental Impact Assessment Review, Vol. 71, pp. 110-119, https://doi.org/10.1016/j.eiar.2018.04.010.

[170] Bijleveld, A. (ed.) (2019), “Wind turbines cause functional habitat loss for migratory soaring birds”, Journal of Animal Ecology, Vol. 89/1, pp. 93-103, https://doi.org/10.1111/1365-2656.12961.

[142] Biogradlija, A. (2022), RWE looks into black rotor wind blades for birds protection, https://www.industryandenergy.eu/renewables/rwe-looks-into-black-rotor-wind-blades-for-birds-protection/ (accessed on 11 October 2022).

[239] Boinski, S. et al. (1998), “Squirrel monkeys in Costa Rica: drifting to extinction”, Oryx, Vol. 32/01, p. 45, https://doi.org/10.1017/s0030605300029756.

[63] Brand, L. et al. (2016), “Mitigation-driven translocation effects on temperature, condition, growth, and mortality of Mojave desert tortoise ( Gopherus agassizii ) in the face of solar energy development”, Biological Conservation, Vol. 200, pp. 104-111, https://doi.org/10.1016/j.biocon.2016.05.032.

[179] Brandt, M. et al. (2018), “Disturbance of harbour porpoises during construction of the first seven offshore wind farms in Germany”, Marine Ecology Progress Series, Vol. 596, pp. 213-232, https://doi.org/10.3354/meps12560.

[95] Brigham, R. (ed.) (2014), “A Comprehensive Analysis of Small-Passerine Fatalities from Collision with Turbines at Wind Energy Facilities”, PLoS ONE, Vol. 9/9, p. e107491, https://doi.org/10.1371/journal.pone.0107491.

[210] Brignon, J. et al. (2022), “A risk-based method to prioritize cumulative impacts assessment on marine biodiversity and research policy for offshore wind farms in France”, Environmental Science &amp; Policy, Vol. 128, pp. 264-276, https://doi.org/10.1016/j.envsci.2021.12.003.

[215] Brown, T. (2015), “Transmission network loading in Europe with high shares of renewables”, IET Renewable Power Generation, Vol. 9/1, pp. 57-65, https://doi.org/10.1049/iet-rpg.2014.0114.

[16] Brunel (2021), What is Concentrated Solar Power and how does CSP work? - Brunel, https://www.brunel.net/en/blog/renewable-energy/concentrated-solar-power (accessed on 1 March 2022).

[277] Burda, H. et al. (2009), “Extremely low-frequency electromagnetic fields disrupt magnetic alignment of ruminants”, Proceedings of the National Academy of Sciences, Vol. 106/14, pp. 5708-5713, https://doi.org/10.1073/pnas.0811194106.

[52] Buton, C. (2023), Impacts écologiques des clôtures et solutions de remédiation possibles., https://www.trameverteetbleue.fr/sites/default/files/references_bibliographiques/impacts_ecologiques_des_clotures_bp_cpv_2023-07-28.pdf.

[293] C. Strevens, T., M. L. Puotinen and R. J. Whelan (2008), “Powerline easements: ecological impacts and contribution to habitat fragmentation from linear features”, Pacific Conservation Biology, Vol. 14/3, p. 159, https://doi.org/10.1071/pc080159.

[101] Cabrera-Cruz, S. et al. (2020), “Estimates of aerial vertebrate mortality at wind farms in a bird migration corridor and bat diversity hotspot”, Global Ecology and Conservation, Vol. 22, p. e00966, https://doi.org/10.1016/j.gecco.2020.e00966.

[6] Campbell, M. et al. (2009), “Minimizing utility-scale PV power plant LCOE through the use of high capacity factor configurations”, 2009 34th IEEE Photovoltaic Specialists Conference (PVSC), https://doi.org/10.1109/pvsc.2009.5411650.

[64] Castillo, S. (2021), Desert tortoise deaths raise questions as Nevada solar farms grow | Las Vegas Review-Journal, https://www.reviewjournal.com/news/science-and-technology/desert-tortoise-deaths-raise-concerns-as-solar-farms-solve-energy-need-2408456/ (accessed on 26 July 2022).

[253] Cecala, K., W. Lowe and J. Maerz (2014), “Riparian disturbance restricts in-stream movement of salamanders”, Freshwater Biology, Vol. 59/11, pp. 2354-2364, https://doi.org/10.1111/fwb.12439.

[284] Chapman, M. (ed.) (2015), “Urban Power Line Corridors as Novel Habitats for Grassland and Alien Plant Species in South-Western Finland”, PLOS ONE, Vol. 10/11, p. e0142236, https://doi.org/10.1371/journal.pone.0142236.

[30] Chock, R. et al. (2020), “Evaluating potential effects of solar power facilities on wildlife from an animal behavior perspective”, Conservation Science and Practice, Vol. 3/2, https://doi.org/10.1111/csp2.319.

[14] Choi, Y. (2014), “A Study on Power Generation Analysis of Floating PV System Considering Environmental Impact”, International Journal of Software Engineering and Its Applications, Vol. 8/1, pp. 75-84, https://doi.org/10.14257/ijseia.2014.8.1.07.

[291] Cho, M., O. Malahlela and A. Ramoelo (2015), “Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study”, International Journal of Applied Earth Observation and Geoinformation, Vol. 38, pp. 349-357, https://doi.org/10.1016/j.jag.2015.01.015.

[260] Clarke, D., K. Pearce and J. White (2006), “Powerline corridors: degraded ecosystems or wildlife havens?”, Wildlife Research, Vol. 33/8, p. 615, https://doi.org/10.1071/wr05085.

[273] Colman, J. et al. (2015), “High-voltage power lines near wild reindeer calving areas”, European Journal of Wildlife Research, Vol. 61/6, pp. 881-893, https://doi.org/10.1007/s10344-015-0965-x.

[80] Conkling, T. et al. (2022), “Vulnerability of avian populations to renewable energy production”, Royal Society Open Science, Vol. 9/3, https://doi.org/10.1098/rsos.211558.

[280] Copping, A. and L. Hemery (2020), OES-Environmental 2020 State of the Science Report: Environmental Effects of Marine Renewable Energy Development Around the World. Report for Ocean Energy Systems (OES), Office of Scientific and Technical Information (OSTI), https://doi.org/10.2172/1632878.

[191] Costello, K. et al. (2022), “Assessing the potential for invasive species introductions and secondary spread using vessel movements in maritime ports”, Marine Pollution Bulletin, Vol. 177, p. 113496, https://doi.org/10.1016/j.marpolbul.2022.113496.

[121] Cryan, P. (2014), “Behavior of bats at wind turbines”, Proc. Natl. Acad. Sci., Vol. 111/42, pp. 15126-15131, https://doi.org/10.1073/pnas.1406672111.

[122] Cryan, P. (2008), “Mating Behavior as a Possible Cause of Bat Fatalities at Wind Turbines”, Journal of Wildlife Management, Vol. 72/3, pp. 845-849, https://doi.org/10.2193/2007-371.

[53] Cypher, B. et al. (2021), “Photovoltaic solar farms in California: can we have renewable electricity and our species, too?”, California Fish and Wildlife Journal, Vol. 107/3, pp. 231-248, https://doi.org/10.51492/cfwj.hwisi.6.

[178] Dähne, M. et al. (2013), “Effects of pile-driving on harbour porpoises ( Phocoena phocoena ) at the first offshore wind farm in Germany”, Environmental Research Letters, Vol. 8/2, p. 025002, https://doi.org/10.1088/1748-9326/8/2/025002.

[151] Dai, K. et al. (2015), “Environmental issues associated with wind energy - A review”, Renewable Energy, Vol. 75, pp. 911-921, https://doi.org/10.1016/J.RENENE.2014.10.074.

[115] de Lucas, M. et al. (2008), “Collision fatality of raptors in wind farms does not depend on raptor abundance”, Journal of Applied Ecology, Vol. 45/6, pp. 1695-1703, https://doi.org/10.1111/j.1365-2664.2008.01549.x.

[72] De Marco, A. et al. (2014), “The contribution of Utility-Scale Solar Energy to the global climate regulation and its effects on local ecosystem services”, Global Ecology and Conservation, Vol. 2, pp. 324-337, https://doi.org/10.1016/J.GECCO.2014.10.010.

[159] De Mesel, I. et al. (2015), “Succession and seasonal dynamics of the epifauna community on offshore wind farm foundations and their role as stepping stones for non-indigenous species”, Hydrobiologia, Vol. 756/1, pp. 37-50, https://doi.org/10.1007/s10750-014-2157-1.

[150] Dhar, A. et al. (2020), “Perspectives on environmental impacts and a land reclamation strategy for solar and wind energy systems”, Science of The Total Environment, Vol. 718, p. 134602, https://doi.org/10.1016/j.scitotenv.2019.134602.

[162] Didderen, K. (2019), Pilot to actively restore native oyster reefs in theNorth Sea: comprehensive report to share lessons learned in 2018.

[155] Diffendorfer, J. et al. (2019), “Geographic context affects the landscape change and fragmentation caused by wind energy facilities”, PeerJ, Vol. 7, p. e7129, https://doi.org/10.7717/peerj.7129.

[209] Diffendorfer, J. et al. (2021), “Demographic and potential biological removal models identify raptor species sensitive to current and future wind energy”, Ecosphere, Vol. 12/6, https://doi.org/10.1002/ecs2.3531.

[92] Ding, H. (ed.) (2020), “An investigation into the potential for wind turbines to cause barotrauma in bats”, PLOS ONE, Vol. 15/12, p. e0242485, https://doi.org/10.1371/journal.pone.0242485.

[242] Dixon, A. et al. (2018), Efficacy of a mitigation method to reduce raptor electrocution at an electricity distribution, Conservation Evidence, https://conservationevidencejournal.com/reference/pdf/6861.

[256] Dixon, A. et al. (2013), “The Use of Power Lines by Breeding Raptors and Corvids in Mongolia: Nest-Site Characteristics and Management Using Artificial Nests”, Journal of Raptor Research, Vol. 47/3, pp. 282-291, https://doi.org/10.3356/jrr-12-00020.1.

[98] DoE (2023), U.S. Installed and Potential Wind Capacity Generation, https://windexchange.energy.gov/maps-data/321.

[12] Dörenkämper, M. et al. (2021), “The cooling effect of floating PV in two different climate zones: A comparison of field test data from the Netherlands and Singapore”, Solar Energy, Vol. 214, pp. 239-247, https://doi.org/10.1016/j.solener.2020.11.029.

[125] Drewitt, A. and R. Langston (2008), “Collision Effects of Wind-power Generators and Other Obstacles on Birds”, Annals of the New York Academy of Sciences, Vol. 1134/1, pp. 233-266, https://doi.org/10.1196/annals.1439.015.

[195] Dröes, M. and H. Koster (2021), “Wind turbines, solar farms, and house prices”, Energy Policy, Vol. 155, p. 112327, https://doi.org/10.1016/j.enpol.2021.112327.

[283] Dubé, C., S. Pellerin and M. Poulin (2011), “Do power line rights-of-way facilitate the spread of non-peatland and invasive plants in bogs and fens?”, Botany, Vol. 89/2, pp. 91-103, https://doi.org/10.1139/b10-089.

[319] Dudka, S. and D. Adriano (1997), “Environmental Impacts of Metal Ore Mining and Processing: A Review”, Journal of Environmental Quality, Vol. 26/3, pp. 590-602, https://doi.org/10.2134/jeq1997.00472425002600030003x.

[7] Dunlop, J. (2010), Photovoltaic Systems. 3rd Edition, American Technical Publishers, Inc., Orland Park. - References - Scientific Research Publishing, American Technical Publishers, Inc. Orland Park, https://www.scirp.org/(S(lz5mqp453ed%20snp55rrgjct55))/reference/referencespapers.aspx?referenceid=1697608 (accessed on 14 June 2022).

[204] EC (2021), OFFSHORE WIND AND FISHERIES | The European Maritime Spatial Planning Platform, https://maritime-spatial-planning.ec.europa.eu/sector-information/offshore-wind-and-fisheries (accessed on 19 July 2022).

[42] EC (2019), Water consumption solution for efficienct concentrated solar power, https://ec.europa.eu/research-and-innovation/en/projects/success-stories/all/water-consumption-solution-efficient-concentrated-solar-power#:~:text=As%20a%20result%2C%20they%20can,natural%20gas%2Dfired%20power%20plants.

[39] EC (2019), Water consumption solution for efficient concentrated solar power, https://ec.europa.eu/research-and-innovation/en/projects/success-stories/all/water-consumption-solution-efficient-concentrated-solar-power.

[316] Edwards, D. et al. (2013), “Mining and the African Environment”, Conservation Letters, Vol. 7/3, pp. 302-311, https://doi.org/10.1111/conl.12076.

[218] EU (2019), Clean energy for all Europeans package, https://energy.ec.europa.eu/topics/energy-strategy/clean-energy-all-europeans-package_en (accessed on 20 July 2022).

[219] Europacable (2021), ELECTRICITY TRANSMISSION OF TOMORROW UNDERGROUND AND SUBSEA CABLES IN EUROPE ®, https://europacable.eu/wp-content/uploads/2021/01/Europacable-Brochure-FINAL_Web-File.pdf (accessed on 20 July 2022).

[89] European Commission (2020), Commission notice Guidance document on wind energy developments and EU nature legislation Commission notice Guidance document on wind energy developments and EU nature legislation Guidance document on wind energy developments and EU Nature Legislation, European Commission (C2020) 7730 final, Brussels, https://ec.europa.eu/environment/nature/natura2000/management/docs/wind_farms_en.pdf (accessed on 3 May 2022).

[111] Everaert, J. and E. Stienen (2006), “Impact of wind turbines on birds in Zeebrugge (Belgium)”, Biodiversity and Conservation, Vol. 16/12, pp. 3345-3359, https://doi.org/10.1007/s10531-006-9082-1.

[126] Everaert, J. and E. Stienen (2006), “Impact of wind turbines on birds in Zeebrugge (Belgium)”, in Biodiversity and Conservation in Europe, Topics in Biodiversity and Conservation, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-1-4020-6865-2_8.

[18] Exley, G. et al. (2021), “Scientific and stakeholder evidence-based assessment: Ecosystem response to floating solar photovoltaics and implications for sustainability”, Renewable and Sustainable Energy Reviews, Vol. 152, https://doi.org/10.1016/J.RSER.2021.111639.

[68] Exley, G. et al. (2021), “Scientific and stakeholder evidence-based assessment: Ecosystem response to floating solar photovoltaics and implications for sustainability”, Renewable and Sustainable Energy Reviews, Vol. 152, p. 111639, https://doi.org/10.1016/j.rser.2021.111639.

[47] Fahrig, L. (2003), “Effects of Habitat Fragmentation on Biodiversity”, Annual Review of Ecology, Evolution, and Systematics, Vol. 34/1, pp. 487-515, https://doi.org/10.1146/annurev.ecolsys.34.011802.132419.

[274] Farr, H. et al. (2021), “Potential environmental effects of deepwater floating offshore wind energy facilities”, Ocean &amp; Coastal Management, Vol. 207, p. 105611, https://doi.org/10.1016/j.ocecoaman.2021.105611.

[165] Fernández‐Bellon, D. et al. (2018), “Effects of development of wind energy and associated changes in land use on bird densities in upland areas”, Conservation Biology, Vol. 33/2, pp. 413-422, https://doi.org/10.1111/cobi.13239.

[275] Fernie, K. and S. Reynolds (2005), “The Effects of Electromagnetic Fields From Power Lines on Avian Reproductive Biology and Physiology: A Review”, Journal of Toxicology and Environmental Health, Part B, Vol. 8/2, pp. 127-140, https://doi.org/10.1080/10937400590909022.

[186] Ferrão da Costa, G. et al. (2017), “The Indirect Impacts of Wind Farms on Terrestrial Mammals: Insights from the Disturbance and Exclusion Effects on Wolves (Canis lupus)”, in Biodiversity and Wind Farms in Portugal, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-60351-3_5.

[143] Ferrer, M. et al. (2022), “Significant decline of Griffon Vulture collision mortality in wind farms during 13-year of a selective turbine stopping protocol”, Global Ecology and Conservation, Vol. 38, p. e02203, https://doi.org/10.1016/j.gecco.2022.e02203.

[193] Frederiksen, M. (ed.) (2014), “Offshore marine renewable energy devices as stepping stones across biogeographical boundaries”, Journal of Applied Ecology, Vol. 51/2, pp. 330-338, https://doi.org/10.1111/1365-2664.12207.

[205] Frick, W. et al. (2017), “Fatalities at wind turbines may threaten population viability of a migratory bat”, Biological Conservation, Vol. 209, pp. 172-177, https://doi.org/10.1016/j.biocon.2017.02.023.

[208] Frick, W., T. Kingston and J. Flanders (2019), “A review of the major threats and challenges to global bat conservation”, Annals of the New York Academy of Sciences, Vol. 1469/1, pp. 5-25, https://doi.org/10.1111/nyas.14045.

[20] Fthenakis, V. and H. Kim (2009), “Land use and electricity generation: A life-cycle analysis”, Renewable and Sustainable Energy Reviews, Vol. 13/6-7, pp. 1465-1474, https://doi.org/10.1016/j.rser.2008.09.017.

[62] Germano, J. et al. (2015), “Mitigation-driven translocations: are we moving wildlife in the right direction?”, Frontiers in Ecology and the Environment, Vol. 13/2, pp. 100-105, https://doi.org/10.1890/140137.

[194] Gibbons, S. (2015), “Gone with the wind: Valuing the visual impacts of wind turbines through house prices”, Journal of Environmental Economics and Management, Vol. 72, pp. 177-196, https://doi.org/10.1016/j.jeem.2015.04.006.

[270] Gibson, D. et al. (2018), “Effects of power lines on habitat use and demography of greater sage-grouse (<i>Centrocercus urophasianus</i>)”, Wildlife Monographs, Vol. 200/1, pp. 1-41, https://doi.org/10.1002/wmon.1034.

[281] Gill, A. et al. (2014), “Marine Renewable Energy, Electromagnetic (EM) Fields and EM-Sensitive Animals”, in Marine Renewable Energy Technology and Environmental Interactions, Humanity and the Sea, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-017-8002-5_6.

[266] Gillan, J. et al. (2013), “Using spatial statistics and point-pattern simulations to assess the spatial dependency between greater sage-grouse and anthropogenic features”, Wildlife Society Bulletin, Vol. 37/2, pp. 301-310, https://doi.org/10.1002/wsb.272.

[5] Goodale, M. and A. Milman (2019), “Assessing the cumulative exposure of wildlife to offshore wind energy development”, Journal of Environmental Management, Vol. 235, pp. 77-83, https://doi.org/10.1016/j.jenvman.2019.01.022.

[251] Goosem, M. and H. Marsh (1997), “Fragmentation of a Small-mammal Community by a Powerline Corridor through Tropical Rainforest”, Wildlife Research, Vol. 24/5, p. 613, https://doi.org/10.1071/wr96063.

[180] Graham, I. et al. (2019), “Harbour porpoise responses to pile-driving diminish over time”, Royal Society Open Science, Vol. 6/6, p. 190335, https://doi.org/10.1098/rsos.190335.

[38] Grippo, M., J. Hayse and B. O’Connor (2014), “Solar Energy Development and Aquatic Ecosystems in the Southwestern United States: Potential Impacts, Mitigation, and Research Needs”, Environmental Management, Vol. 55/1, pp. 244-256, https://doi.org/10.1007/s00267-014-0384-x.

[73] Grodsky, S., J. Campbell and R. Hernandez (2021), “Solar energy development impacts flower-visiting beetles and flies in the Mojave Desert”, Biological Conservation, Vol. 263, p. 109336, https://doi.org/10.1016/j.biocon.2021.109336.

[35] Grodsky, S. and R. Hernandez (2020), “Reduced ecosystem services of desert plants from ground-mounted solar energy development”, Nature Sustainability, Vol. 3/12, pp. 1036-1043, https://doi.org/10.1038/s41893-020-0574-x.

[50] Guerin, T. (2017), “A case study identifying and mitigating the environmental and community impacts from construction of a utility-scale solar photovoltaic power plant in eastern Australia”, Solar Energy, Vol. 146, pp. 94-104, https://doi.org/10.1016/J.SOLENER.2017.02.020.

[240] Guil, F. and J. Pérez-García (2022), “Bird electrocution on power lines: Spatial gaps and identification of driving factors at global scales”, Journal of Environmental Management, Vol. 301, p. 113890, https://doi.org/10.1016/j.jenvman.2021.113890.

[83] GWEC (2022), Global Wind Report 2022, https://gwec.net/global-wind-report-2022/.

[243] Haas, D. et al. (2005), “Protecting birds on powerlines: a practical guide on the risks to birds from electricity transmission facilities and how to minimise any such adverse effects”, http://birdsandpowerlines.org/cm/media/Protecting_birds_on_powerlines.pdf (accessed on 20 July 2022).

[46] Haddad, N. et al. (2015), “Habitat fragmentation and its lasting impact on Earth’s ecosystems”, Science Advances, Vol. 1/2, https://doi.org/10.1126/sciadv.1500052.

[133] Hallmann, C. et al. (2017), “More than 75 percent decline over 27 years in total flying insect biomass in protected areas”, https://doi.org/10.1371/journal.pone.0185809.

[282] Harsanyi, P. et al. (2022), “The Effects of Anthropogenic Electromagnetic Fields (EMF) on the Early Development of Two Commercially Important Crustaceans, European Lobster, Homarus gammarus (L.) and Edible Crab, Cancer pagurus (L.)”, Journal of Marine Science and Engineering, Vol. 10/5, p. 564, https://doi.org/10.3390/jmse10050564.

[71] Hastik, R. et al. (2015), “Renewable energies and ecosystem service impacts”, Renewable and Sustainable Energy Reviews, Vol. 48, pp. 608-623, https://doi.org/10.1016/j.rser.2015.04.004.

[104] Hayes, M. (2013), “Bats Killed in Large Numbers at United States Wind Energy Facilities”, BioScience, Vol. 63/12, pp. 975-979, https://doi.org/10.1525/bio.2013.63.12.10.

[312] Heffernan, O. (2019), “Seabed mining is coming — bringing mineral riches and fears of epic extinctions”, Nature, Vol. 571/7766, pp. 465-468, https://doi.org/10.1038/d41586-019-02242-y.

[249] Hermy, M. (ed.) (2013), “Edge effects of linear canopy openings on understorey communities in a lowland Atlantic tropical forest”, Applied Vegetation Science, Vol. 17/1, pp. 121-128, https://doi.org/10.1111/avsc.12043.

[234] Hernández-Matías, A. et al. (2015), “Electrocution threatens the viability of populations of the endangered Bonelli’s eagle ( Aquila fasciata ) in Southern Europe”, Biological Conservation, Vol. 191, pp. 110-116, https://doi.org/10.1016/j.biocon.2015.06.028.

[9] Hernandez, R. et al. (2014), “Environmental impacts of utility-scale solar energy”, Renewable and Sustainable Energy Reviews, Vol. 29, pp. 766-779, https://doi.org/10.1016/j.rser.2013.08.041.

[77] Hernandez, R., M. Hoffacker and C. Field (2014), “Land-Use Efficiency of Big Solar”, Environmental Science & Technology, Vol. 48/2, pp. 1315-1323, https://doi.org/10.1021/es4043726.

[48] Hernandez, R. et al. (2015), “Solar energy development impacts on land cover change and protected areas”, Proceedings of the National Academy of Sciences, Vol. 112/44, pp. 13579-13584, https://doi.org/10.1073/PNAS.1517656112.

[127] Heuck, C. et al. (2019), “Wind turbines in high quality habitat cause disproportionate increases in collision mortality of the white-tailed eagle”, Biological Conservation, Vol. 236, pp. 44-51, https://doi.org/10.1016/j.biocon.2019.05.018.

[28] Ho, C. (2016), “Review of avian mortality studies at concentrating solar power plants”, https://doi.org/10.1063/1.4949164.

[305] Holland, R. et al. (2019), “The influence of the global electric power system on terrestrial biodiversity”, Proceedings of the National Academy of Sciences, Vol. 116/51, pp. 26078-26084, https://doi.org/10.1073/pnas.1909269116.

[263] Hooftman, D. (ed.) (2015), “Edge effects on plant communities along power line clearings”, Journal of Applied Ecology, Vol. 52/4, pp. 871-880, https://doi.org/10.1111/1365-2664.12460.

[10] Hooper, T., A. Armstrong and B. Vlaswinkel (2021), “Environmental impacts and benefits of marine floating solar”, Solar Energy, Vol. 219, pp. 11-14, https://doi.org/10.1016/j.solener.2020.10.010.

[144] Horn, J., E. Arnett and T. Kunz (2008), “Behavioral Responses of Bats to Operating Wind Turbines”, Journal of Wildlife Management, Vol. 72/1, pp. 123-132, https://doi.org/10.2193/2006-465.

[66] Horváth, G. (2010), “Reducing the Maladaptive Attractiveness of Solar Panels to Polarotactic Insects”, Conservation Biology, Vol. 24/6, pp. 1644-1653, https://doi.org/10.1111/j.1523-1739.2010.01518.x.

[65] Horváth, G. et al. (2009), “Polarized light pollution: a new kind of ecological photopollution”, Frontiers in Ecology and the Environment, Vol. 7/6, pp. 317-325, https://doi.org/10.1890/080129.

[257] Howe, K., P. Coates and D. Delehanty (2014), “Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem”, The Condor, Vol. 116/1, pp. 35-49, https://doi.org/10.1650/condor-13-115-r2.1.

[93] Hüppop, O. (2019), Migratory birds and bats., Pelagic Publishing.

[145] Huso, M. et al. (2021), “Relative energy production determines effect of repowering on wildlife mortality at wind energy facilities”, Journal of Applied Ecology, Vol. 58/6, pp. 1284-1290, https://doi.org/10.1111/1365-2664.13853.

[29] Huso, M., T. Dietsch and C. Nicolai (2016), Mortality Monitoring Design for Utility-Scale Solar Power Facilities, https://doi.org/10.3133/ofr20161087 (accessed on 22 February 2022).

[288] Hyde, J., S. Bohlman and D. Valle (2018), “Transmission lines are an under-acknowledged conservation threat to the Brazilian Amazon”, Biological Conservation, Vol. 228, pp. 343-356, https://doi.org/10.1016/j.biocon.2018.10.027.

[17] IBRD (2020), Concentrating Solar Power Clean Power on Demand 24/7, http://www.worldbank.org (accessed on 15 December 2021).

[303] IEA (2021), The Role of Critical Minerals in Clean Energy Transitions, IEA, https://www.iea.org/reports/the-role-of-critical-minerals-in-clean-energy-transitions.

[216] IEA (2021), Net Zero by 2050: A Roadmap for the Global Energy Sector, OECD Publishing, Paris, https://doi.org/10.1787/c8328405-en.

[294] IEA (2021), The Role of Critical Minerals in Clean Energy Transitions, International Energy Agency, https://www.iea.org/reports/the-role-of-critical-minerals-in-clean-energy-transitions.

[81] IEA (2020), Renewables 2020.

[84] IEA (2019), Offshore Wind Outlook, https://iea.blob.core.windows.net/assets/495ab264-4ddf-4b68-b9c0-514295ff40a7/Offshore_Wind_Outlook_2019.pdf.

[217] IEA ETSAP (2014), Electricity Transmission and Distribution, https://iea-etsap.org/E-TechDS/PDF/E12_el-t&d_KV_Apr2014_GSOK.pdf (accessed on 20 July 2022).

[4] IFC (2013), Good Practice Handbook on Cumulative Impact Assessment and Management: Guidance for the Private Sector in Emerging Markets, https://www.ifc.org/wps/wcm/connect/topics_ext_content/ifc_external_corporate_site/sustainability-at-ifc/publications/publications_handbook_cumulativeimpactassessment (accessed on 1 July 2022).

[135] Inger, R. et al. (2009), “Marine renewable energy: potential benefits to biodiversity? An urgent call for research”, Journal of Applied Ecology, https://doi.org/10.1111/j.1365-2664.2009.01697.x.

[85] IPCC (2011), Special Report on Renewable Energy Sources and Climate Change Mitigation..

[88] IRENA (2019), Future of wind - Deployment, investment, technology, grid integration and socioeconomic aspects.

[309] IUCN Members (2020), Protection of deep-ocean ecosystems and biodiversity through a moratorium on seabed mining, https://portals.iucn.org/library/sites/library/files/resrecfiles/WCC_2020_RES_122_EN.pdf.

[317] Jacobi, C., F. do Carmo and I. de Campos (2011), “Soaring Extinction Threats to Endemic Plants in Brazilian Metal-Rich Regions”, AMBIO, Vol. 40/5, pp. 540-543, https://doi.org/10.1007/s13280-011-0151-7.

[22] Jeal, C. et al. (2019), “Impacts of a concentrated solar power trough facility on birds and other wildlife in South Africa”, Ostrich, Vol. 90/2, pp. 129-137, https://doi.org/10.2989/00306525.2019.1581296.

[244] Jenkins, A., J. Smallie and M. Diamond (2010), “Avian collisions with power lines: a global review of causes and mitigation with a South African perspective”, Bird Conservation International, Vol. 20/3, pp. 263-278, https://doi.org/10.1017/s0959270910000122.

[190] JNCC (2010), Statutory nature conservation agency protocol for minimising the risk of injury to marine mammals from piling noise, https://data.jncc.gov.uk/data/31662b6a-19ed-4918-9fab-8fbcff752046/JNCC-CNCB-Piling-protocol-August2010-Web.pdf.

[25] Kagan, R. et al. (2014), Avian Mortality at Solar Energy Facilities in Southern California: A Preliminary Analysis, National Fish and Wildlife Forensics Laboratory, https://www.ourenergypolicy.org/wp-content/uploads/2014/04/avian-mortality.pdf (accessed on 20 December 2021).

[211] Kasso, M. and M. Balakrishnan (2013), “Ecological and Economic Importance of Bats (Order Chiroptera)”, ISRN Biodiversity, Vol. 2013, pp. 1-9, https://doi.org/10.1155/2013/187415.

[235] Katsis, L. et al. (2018), “Spatial Patterns of Primate Electrocutions in Diani, Kenya”, International Journal of Primatology, Vol. 39/4, pp. 493-510, https://doi.org/10.1007/s10764-018-0046-6.

[201] Keehn, J. and C. Feldman (2018), “Disturbance affects biotic community composition at desert wind farms”, Wildlife Research, Vol. 45/5, p. 383, https://doi.org/10.1071/wr17059.

[79] Kim, J. et al. (2021), “Current site planning of medium to large solar power systems accelerates the loss of the remaining semi-natural and agricultural habitats”, Science of The Total Environment, Vol. 779, p. 146475, https://doi.org/10.1016/j.scitotenv.2021.146475.

[255] King, D. et al. (2009), “Effects of width, edge and habitat on the abundance and nesting success of scrub–shrub birds in powerline corridors”, Biological Conservation, Vol. 142/11, pp. 2672-2680, https://doi.org/10.1016/j.biocon.2009.06.016.

[185] Klich, D. et al. (2020), “Roe deer stress response to a wind farms: Methodological and practical implications”, Ecological Indicators, Vol. 117, p. 106658, https://doi.org/10.1016/j.ecolind.2020.106658.

[182] Kok, A. et al. (2021), “An echosounder view on the potential effects of impulsive noise pollution on pelagic fish around windfarms in the North Sea”, Environmental Pollution, Vol. 290, p. 118063, https://doi.org/10.1016/j.envpol.2021.118063.

[233] Kolnegari et al. (2020), “Electrical Components Involved in Avian-Caused Outages in Iran”, Bird Conservation International, Vol. 31/3, pp. 364-378, https://doi.org/10.1017/s0959270920000507.

[67] Kosciuch, K. et al. (2021), “Aquatic Habitat Bird Occurrences at Photovoltaic Solar Energy Development in Southern California, USA”, Diversity, Vol. 13/11, p. 524, https://doi.org/10.3390/d13110524.

[267] Krüger, S., R. Simmons and A. Amar (2015), “Anthropogenic activities influence the abandonment of Bearded Vulture (<i>Gypaetus barbatus</i>) territories in southern Africa”, The Condor, Vol. 117/1, pp. 94-107, https://doi.org/10.1650/condor-14-121.1.

[176] Kumara, H. et al. (2022), “Responses of birds and mammals to long-established wind farms in India”, Scientific Reports, Vol. 12/1, https://doi.org/10.1038/s41598-022-05159-1.

[285] Kurek, P., T. Sparks and P. Tryjanowski (2015), “Electricity pylons may be potential foci for the invasion of black cherry Prunus serotina in intensive farmland”, Acta Oecologica, Vol. 62, pp. 40-44, https://doi.org/10.1016/j.actao.2014.11.005.

[34] Lambert, Q. et al. (2021), “Effects of solar park construction and solar panels on soil quality, microclimate, CO 2 effluxes, and vegetation under a Mediterranean climate”, Land Degradation & Development, Vol. 32/18, pp. 5190-5202, https://doi.org/10.1002/ldr.4101.

[161] Langhamer, O. (2012), “Artificial Reef Effect in relation to Offshore Renewable Energy Conversion: State of the Art”, The Scientific World Journal, Vol. 2012, pp. 1-8, https://doi.org/10.1100/2012/386713.

[292] Laurance, W. et al. (2011), “The fate of Amazonian forest fragments: A 32-year investigation”, Biological Conservation, Vol. 144/1, pp. 56-67, https://doi.org/10.1016/j.biocon.2010.09.021.

[76] Laurance, W., M. Goosem and S. Laurance (2009), “Impacts of roads and linear clearings on tropical forests”, Trends in Ecology &amp; Evolution, Vol. 24/12, pp. 659-669, https://doi.org/10.1016/j.tree.2009.06.009.

[308] Lèbre, É. et al. (2020), “The social and environmental complexities of extracting energy transition metals”, Nature Communications, Vol. 11/1, https://doi.org/10.1038/s41467-020-18661-9.

[82] Lee, J. and F. Zhao (2022), GWEC Global Wind Report 2022, Global Wind Energy Council, https://gwec.net/wp-content/uploads/2022/04/Annual-Wind-Report-2022_screen_final_April.pdf (accessed on 8 June 2022).

[232] Lehman, R., P. Kennedy and J. Savidge (2007), “The state of the art in raptor electrocution research: A global review”, Biological Conservation, Vol. 136/2, pp. 159-174, https://doi.org/10.1016/J.BIOCON.2006.09.015.

[49] Leskova, O., R. Frakes and S. Markwith (2022), “Impacting habitat connectivity of the endangered Florida panther for the transition to utility-scale solar energy”, Journal of Applied Ecology, https://doi.org/10.1111/1365-2664.14098.

[158] Lindeboom, H. et al. (2011), “Short-term ecological effects of an offshore wind farm in the Dutch coastal zone; a compilation”, Environmental Research Letters, Vol. 6/3, p. 035101, https://doi.org/10.1088/1748-9326/6/3/035101.

[136] Li, S. (ed.) (2017), “High mortality of blue, humpback and fin whales from modeling of vessel collisions on the U.S. West Coast suggests population impacts and insufficient protection”, PLOS ONE, Vol. 12/8, p. e0183052, https://doi.org/10.1371/journal.pone.0183052.

[245] LOD (2019), Installation of bird protection measures on the high voltage electricity, https://www.birds-electrogrid.lt/uploads/Projekto%20dokumentai/LIFE13%20BIO-LT-001303%20FINAL%20REPORT_approved_web.pdf.

[163] Łopucki, R., D. Klich and S. Gielarek (2017), “Do terrestrial animals avoid areas close to turbines in functioning wind farms in agricultural landscapes?”, Environmental Monitoring and Assessment, Vol. 189/7, https://doi.org/10.1007/S10661-017-6018-Z.

[264] Lóránt, M. and C. Vadász (2014), “The Effect of Above-Ground Medium Voltage Power Lines on Displaying Site Selection of the Great Bustard (<i>Otis Tarda</i>) in Central Hungary”, Ornis Hungarica, Vol. 22/2, pp. 42-49, https://doi.org/10.2478/orhu-2014-0017.

[103] Loss, S. et al. (2014), “Bird–building collisions in the United States: Estimates of annual mortality and species vulnerability”, The Condor, Vol. 116/1, pp. 8-23, https://doi.org/10.1650/condor-13-090.1.

[222] Loss, S., T. Will and P. Marra (2015), “Direct Mortality of Birds from Anthropogenic Causes”, Annual Review of Ecology, Evolution, and Systematics, Vol. 46/1, pp. 99-120, https://doi.org/10.1146/annurev-ecolsys-112414-054133.

[94] Loss, S., T. Will and P. Marra (2013), “Estimates of bird collision mortality at wind facilities in the contiguous United States”, Biological Conservation, Vol. 168, pp. 201-209, https://doi.org/10.1016/j.biocon.2013.10.007.

[226] Loss, S., T. Will and P. Marra (2012), “Direct human-caused mortality of birds: improving quantification of magnitude and assessment of population impact”, Frontiers in Ecology and the Environment, Vol. 10/7, pp. 357-364, https://doi.org/10.1890/110251.

[40] Lovich, J. and J. Ennen (2011), “Wildlife Conservation and Solar Energy Development in the Desert Southwest, United States”, BioScience, Vol. 61/12, pp. 982-992, https://doi.org/10.1525/bio.2011.61.12.8.

[304] Luckeneder, S. et al. (2021), “Surge in global metal mining threatens vulnerable ecosystems”, Global Environmental Change, Vol. 69, p. 102303, https://doi.org/10.1016/j.gloenvcha.2021.102303.

[310] Lusty, P. et al. (2021), Deep-sea mining evidence review, Report commissioned by UK Government., https://www.bgs.ac.uk/download/deep-sea-mining-evidence-review/.

[279] Mahmood, M. et al. (2013), “Effects of electromagnetic field on the nitrogen, protein and chlorophyll&lt;br&gt;content and peroxidase enzyme activity in oil palm (Elaeis guineensis Jacq.)&lt;br&gt;leaves”, Emirates Journal of Food and Agriculture, Vol. 25/6, p. 471, https://doi.org/10.9755/ejfa.v25i6.15583.

[300] Månberger, A. and B. Stenqvist (2018), “Global metal flows in the renewable energy transition: Exploring the effects of substitutes, technological mix and development”, Energy Policy, Vol. 119, pp. 226-241, https://doi.org/10.1016/j.enpol.2018.04.056.

[221] Margalida, A. (ed.) (2014), “Refining Estimates of Bird Collision and Electrocution Mortality at Power Lines in the United States”, PLoS ONE, Vol. 9/7, p. e101565, https://doi.org/10.1371/journal.pone.0101565.

[119] Marques, A. et al. (2014), “Understanding bird collisions at wind farms: An updated review on the causes and possible mitigation strategies”, Biological Conservation, Vol. 179, pp. 40-52, https://doi.org/10.1016/j.biocon.2014.08.017.

[321] Martinez-Alier, J. (2001), “Mining conflicts, environmental justice, and valuation”, Journal of Hazardous Materials, Vol. 86/1-3, pp. 153-170, https://doi.org/10.1016/s0304-3894(01)00252-7.

[56] Masson, V. et al. (2014), “Solar panels reduce both global warming and urban heat island”, Frontiers in Environmental Science, Vol. 2, https://doi.org/10.3389/fenvs.2014.00014.

[130] Matthew, F. et al. (2016), Understanding the risk to European protected species (bats) at onshore wind turbine sites to inform risk management. Technical Report. Defra, http://eprints.uwe.ac.uk/33789.

[86] Maxwell, S. et al. (2022), “Potential impacts of floating wind turbine technology for marine species and habitats”, Journal of Environmental Management, Vol. 307, p. 114577, https://doi.org/10.1016/j.jenvman.2022.114577.

[146] May, R. et al. (2020), “Paint it black: Efficacy of increased wind turbine rotor blade visibility to reduce avian fatalities”, Ecology and Evolution, Vol. 10/16, pp. 8927-8935, https://doi.org/10.1002/ece3.6592.

[118] McClure, C. et al. (2021), “Flight Altitudes of Raptors in Southern Africa Highlight Vulnerability of Threatened Species to Wind Turbines”, Frontiers in Ecology and Evolution, Vol. 9, https://doi.org/10.3389/fevo.2021.667384.

[189] McGarry, T. (2017), Understanding the Effectiveness of Acoustic Deterrent Devices on Minke Whale (Balaenoptera acutorostrata), A Low Frequency Cetacean.

[188] McGarry, T. et al. (2022), Evidence base for application of Acoustic Deterrent Devices (ADDs) as marine mammal mitigation (Version 3), JNCC, https://data.jncc.gov.uk/data/e2d08d7a-998b-4814-a0ae-4edf5d887a02/jncc-report-615-v4.pdf.

[51] McInturff, A. et al. (2020), “Fence Ecology: Frameworks for Understanding the Ecological Effects of Fences”, BioScience, https://doi.org/10.1093/biosci/biaa103.

[174] Milligan, M. et al. (2023), “Wind‐energy development alters pronghorn migration at multiple scales”, Ecology and Evolution, Vol. 13/1, https://doi.org/10.1002/ece3.9687.

[241] Minderman, J. (ed.) (2015), “Retrofitting of power lines effectively reduces mortality by electrocution in large birds: an example with the endangered Bonelli’s eagle”, Journal of Applied Ecology, Vol. 52/6, pp. 1465-1473, https://doi.org/10.1111/1365-2664.12476.

[36] Montag, H., G. Parker and T. Clarkson (2016), The Effects of Solar Farms on Local Biodiversity: A Comparative Study, https://2lwej44565rn2mmjlk31pmwq-wpengine.netdna-ssl.com/wp-content/uploads/2016/05/The-Effects-of-Solar-Farms-on-Local-Biodiversity-A-Comparative-Study.pdf (accessed on 16 December 2021).

[237] Moore, R., K. Nekaris and C. Eschmann (2010), “Habitat use by western purple-faced langurs Trachypithecus vetulus nestor (Colobinae) in a fragmented suburban landscape”, Endangered Species Research, Vol. 12/3, pp. 227-234, https://doi.org/10.3354/esr00307.

[236] Moore, R., Wihermanto and K. Nekaris (2014), “Compassionate conservation, rehabilitation and translocation of Indonesian slow lorises”, Endangered Species Research, Vol. 26/2, pp. 93-102, https://doi.org/10.3354/esr00620.

[301] MTE (2022), • MTE (2022), « L’éolien et les moteurs pour véhicules électriques : choix technologiques, enjeux matières et opportunités industrielles » https://www.ecologie.gouv.fr/sites/default/files/rapport_cgdd_02_eolien_moteurs_vehicules_electriques_juillet2022.p, https://www.ecologie.gouv.fr/sites/default/files/rapport_cgdd_02_eolien_moteurs_vehicules_electriques_juillet2022.pdf.

[297] MTE (2022), La mobilité bas-carbone : choix technologiques, enjeux matières et opportunités industrielles, https://www.ecologie.gouv.fr/sites/default/files/rapport_cgdd_01_mobilite_bas_carbone_fevrier2022.pdf.

[296] MTE (2020), Le photovoltaïque : choix technologiques, enjeux matières et opportunités industrielles, http://www.ecologie.gouv.fr/sites/default/files/Plan%20ressources%20Photovoltaique.pdf.

[298] MTE (2020), Les réseaux électriques (lignes électriques, stockage stationnaire et réseau intelligents) : choix technologiques, enjeux matières et opportunités industrielles, https://www.ecologie.gouv.fr/sites/default/files/Plan%20ressources%20R%C3%A9.

[306] Murguía, D., S. Bringezu and R. Schaldach (2016), “Global direct pressures on biodiversity by large-scale metal mining: Spatial distribution and implications for conservation”, Journal of Environmental Management, Vol. 180, pp. 409-420, https://doi.org/10.1016/j.jenvman.2016.05.040.

[23] Murphy-Mariscal, M., S. Grodsky and R. Hernandez (2018), “Solar Energy Development and the Biosphere”, A Comprehensive Guide to Solar Energy Systems, pp. 391-405, https://doi.org/10.1016/B978-0-12-811479-7.00020-8.

[32] Murphy-Mariscal, M., S. Grodsky and R. Hernandez (2018), “Solar Energy Development and the Biosphere”, in A Comprehensive Guide to Solar Energy Systems, Elsevier, https://doi.org/10.1016/b978-0-12-811479-7.00020-8.

[61] Murphy-Mariscal, M., S. Grodsky and R. Hernandez (2018), “Solar Energy Development and the Biosphere”, A Comprehensive Guide to Solar Energy Systems, pp. 391-405, https://doi.org/10.1016/B978-0-12-811479-7.00020-8.

[8] Murray, J. (2021), Profiling the five largest solar power plants in China, https://www.nsenergybusiness.com/features/largest-solar-plants-china/ (accessed on 19 July 2022).

[320] N Yenkie, M. et al. (2006), “Impacts of mining activities on water and soil German Academic Exchange Fellowship View project Wastewater treatment View project Impacts of Mining Activities on Water and Soil”, Article in Indian Journal of Environmental Health, Vol. 47/4, pp. 81-90, https://www.researchgate.net/publication/5932180 (accessed on 1 August 2022).

[258] Nekola, J. (2012), “The impact of a utility corridor on terrestrial gastropod biodiversity”, Biodiversity and Conservation, Vol. 21/3, pp. 781-795, https://doi.org/10.1007/s10531-011-0216-8.

[272] Nellemann, C. et al. (2001), “Winter distribution of wild reindeer in relation to power lines, roads and resorts”, Biological Conservation, Vol. 101/3, pp. 351-360, https://doi.org/10.1016/s0006-3207(01)00082-9.

[289] OECD (2023), Taming Wildfires in the Context of Climate Change, OECD Publishing, Paris, https://doi.org/10.1787/dd00c367-en.

[138] OECD (2021), “Towards G7 action to combat ghost fishing gear: A background report prepared for the 2021 G7 Presidency of the United Kingdom”, OECD Environment Policy Papers, No. 25, OECD Publishing, Paris, https://doi.org/10.1787/a4c86e42-en.

[295] OECD (2019), Global Material Resources Outlook to 2060: Economic Drivers and Environmental Consequences, OECD Publishing, Paris, https://doi.org/10.1787/9789264307452-en.

[299] OECD (2016), OECD Due Diligence Guidance for Responsible Supply Chains of Minerals from Conflict-Affected and High-Risk Areas: Third Edition, OECD Publishing, Paris, https://doi.org/10.1787/9789264252479-en.

[207] O’Shea, T. et al. (2016), “Multiple mortality events in bats: a global review”, Mammal Review, Vol. 46/3, pp. 175-190, https://doi.org/10.1111/mam.12064.

[238] Parker, L., V. Nijman and K. Nekaris (2008), “When there is no forest left: fragmentation, local extinction, and small population sizes in the Sri Lankan western purple-faced langur”, Endangered Species Research, Vol. 5, pp. 29-36, https://doi.org/10.3354/esr00107.

[187] Park, J. and Y. Do (2022), “Wind Turbine Noise Behaviorally and Physiologically Changes Male Frogs”, Biology, Vol. 11/4, p. 516, https://doi.org/10.3390/biology11040516.

[197] Parsons, G. et al. (2020), “The effect of offshore wind power projects on recreational beach use on the east coast of the United States: Evidence from contingent-behavior data”, Energy Policy, Vol. 144, p. 111659, https://doi.org/10.1016/j.enpol.2020.111659.

[172] Pearce-Higgins, J. et al. (2012), “Greater impacts of wind farms on bird populations during construction than subsequent operation: results of a multi-site and multi-species analysis”, Journal of Applied Ecology, Vol. 49/2, pp. 386-394, https://doi.org/10.1111/j.1365-2664.2012.02110.x.

[167] Pearce-Higgins, J. et al. (2009), “The distribution of breeding birds around upland wind farms”, Journal of Applied Ecology, Vol. 46/6, pp. 1323-1331, https://doi.org/10.1111/J.1365-2664.2009.01715.X.

[168] Pearse, A. et al. (2021), “Migrating Whooping Cranes avoid wind‐energy infrastructure when selecting stopover habitat”, Ecological Applications, Vol. 31/5, https://doi.org/10.1002/eap.2324.

[100] Perold, V., S. Ralston-Paton and P. Ryan (2020), “On a collision course? The large diversity of birds killed by wind turbines in South Africa”, Ostrich, Vol. 91/3, pp. 228-239, https://doi.org/10.2989/00306525.2020.1770889.

[192] Perrow, M. (ed.) (2017), Vegetation, Pelagic Publishing.

[164] Peschko, V. et al. (2020), “Effects of offshore windfarms on seabird abundance: Strong effects in spring and in the breeding season”, Marine Environmental Research, Vol. 162, p. 105157, https://doi.org/10.1016/j.marenvres.2020.105157.

[259] Plewa, R. et al. (2020), “Establishment and Maintenance of Power Lines are Important for Insect Diversity in Central Europe”, Zoological Studies, Vol. 59, p. e3, https://doi.org/10.6620/ZS.2020.59-3.

[116] Poessel, S. et al. (2018), “Flight response to spatial and temporal correlates informs risk from wind turbines to the California Condor”, The Condor, Vol. 120/2, pp. 330-342, https://doi.org/10.1650/condor-17-100.1.

[248] Pohlman, C., S. Turton and M. Goosem (2009), “Temporal variation in microclimatic edge effects near powerlines, highways and streams in Australian tropical rainforest”, Agricultural and Forest Meteorology, Vol. 149/1, pp. 84-95, https://doi.org/10.1016/J.AGRFORMET.2008.07.003.

[214] Pollitt, M. (2009), Electricity liberalisation in the European Union: A progress report..

[184] Pol, M. (ed.) (2022), “Demersal fish and invertebrate catches relative to construction and operation of North America’s first offshore wind farm”, ICES Journal of Marine Science, Vol. 79/4, pp. 1274-1288, https://doi.org/10.1093/icesjms/fsac051.

[325] Popper, A. et al. (2022), “Offshore wind energy development: Research priorities for sound and vibration effects on fishes and aquatic invertebrates”, The Journal of the Acoustical Society of America, Vol. 151/1, pp. 205-215, https://doi.org/10.1121/10.0009237.

[265] Pruett, C., M. Patten and D. Wolfe (2009), “It’s Not Easy Being Green: Wind Energy and a Declining Grassland Bird”, BioScience, Vol. 59/3, pp. 257-262, https://doi.org/10.1525/bio.2009.59.3.10.

[246] Raab, R. et al. (2011), “Underground cabling and marking of power lines: conservation measures rapidly reduced mortality of West-Pannonian Great Bustards <i>Otis tarda</i>”, Bird Conservation International, Vol. 22/3, pp. 299-306, https://doi.org/10.1017/s0959270911000463.

[74] Randle-Boggis, R. et al. (2020), “Realising co-benefits for natural capital and ecosystem services from solar parks: A co-developed, evidence-based approach”, Renewable and Sustainable Energy Reviews, Vol. 125, p. 109775, https://doi.org/10.1016/j.rser.2020.109775.

[247] Raptor Protection of Slovakia (2019), Protecting birds from power lines focusing on countries of Danube/Carpathian region, https://energy.danube-region.eu/wp-content/uploads/sites/6/sites/6/2019/09/Study_Birds_FIN.pdf (accessed on 7 February 2023).

[250] Reznik, G., J. Pires and L. Freitas (2012), “Efeito de bordas lineares na fenologia de espécies arbóreas zoocóricas em um remanescente de Mata Atlântica”, Acta Botanica Brasilica, Vol. 26/1, pp. 65-73, https://doi.org/10.1590/s0102-33062012000100008.

[287] Richardson, M. et al. (2017), “A review of the impact of pipelines and power lines on biodiversity and strategies for mitigation”, Biodiversity and Conservation, Vol. 26/8, pp. 1801-1815, https://doi.org/10.1007/S10531-017-1341-9/TABLES/3.

[120] Richardson, S. et al. (2021), “Peaks in bat activity at turbines and the implications for mitigating the impact of wind energy developments on bats”, Scientific Reports, Vol. 11/1, https://doi.org/10.1038/s41598-021-82014-9.

[271] Rieucau, G., W. Vickery and G. Doucet (2009), “A patch use model to separate effects of foraging costs on giving-up densities: an experiment with white-tailed deer (Odocoileus virginianus)”, Behavioral Ecology and Sociobiology, Vol. 63/6, pp. 891-897, https://doi.org/10.1007/s00265-009-0732-7.

[223] Rioux, S., J. Savard and A. Gerick (2013), “Avian mortalities due to transmission line collisions: a review of current estimates and field methods with an emphasis on applications to the Canadian electric network”, Avian Conservation and Ecology, Vol. 8/2, https://doi.org/10.5751/ace-00614-080207.

[43] Roehrkasten, S., D. Schaeuble and S. Helgenberger (2015), Secure and Sustainable Power Generation in a Water-Constrained World, https://www.rifs-potsdam.de/sites/default/files/files/iass_2015_powergenerationinawaterconstrainedworld.pdf.

[117] Roemer, C. et al. (2017), “Bat flight height monitored from wind masts predicts mortality risk at wind farms”, Biological Conservation, Vol. 215, pp. 116-122, https://doi.org/10.1016/j.biocon.2017.09.002.

[91] Rollins, K. et al. (2012), “A Forensic Investigation Into the Etiology of Bat Mortality at a Wind Farm: Barotrauma or Traumatic Injury?”, Veterinary Pathology, Vol. 49/2, pp. 362-371, https://doi.org/10.1177/0300985812436745.

[229] RPS (2021), Electrocutions and Collisions of Birds in EU Countries: The Negative Impact and Best Practices for Mitigation.

[302] RTE (2019), French Transmission Network Development Plan, https://eolmernormandie.debatpublic.fr/images/documents/dmo/biblio/sddr2019_rapport_complet.pdf.

[113] Rydell, J. et al. (2010), “Bat mortality at wind turbines in northwestern Europe”, Acta Chiropterologica, Vol. 12/2, pp. 261-274, https://doi.org/10.3161/150811010X537846.

[124] Rydell, J. et al. (2010), “Bat Mortality at Wind Turbines in Northwestern Europe”, Acta Chiropterologica, Vol. 12/2, pp. 261-274, https://doi.org/10.3161/150811010x537846.

[13] Sacramento, E. et al. (2015), “Scenarios for use of floating photovoltaic plants in Brazilian reservoirs”, IET Renewable Power Generation, Vol. 9/8, pp. 1019-1024, https://doi.org/10.1049/iet-rpg.2015.0120.

[19] Saikia, L. (ed.) (2022), “Land-use intensity of electricity production and tomorrow’s energy landscape”, PLOS ONE, Vol. 17/7, p. e0270155, https://doi.org/10.1371/journal.pone.0270155.

[134] Sánchez-Bayo, F. and K. Wyckhuys (2019), “Worldwide decline of the entomofauna: A review of its drivers”, Biological Conservation, Vol. 232, pp. 8-27, https://doi.org/10.1016/J.BIOCON.2019.01.020.

[268] Santiago-Quesada, F. et al. (2014), “Roost location and landscape attributes influencing habitat selection of migratory waterbirds in rice fields”, Agriculture, Ecosystems &amp; Environment, Vol. 188, pp. 97-102, https://doi.org/10.1016/j.agee.2014.02.019.

[225] Schaub, M. et al. (2010), “Massive immigration balances high anthropogenic mortality in a stable eagle owl population: Lessons for conservation”, Biological Conservation, Vol. 143/8, pp. 1911-1918, https://doi.org/10.1016/j.biocon.2010.04.047.

[224] Schaub, M. and R. Pradel (2004), “ASSESSING THE RELATIVE IMPORTANCE OF DIFFERENT SOURCES OF MORTALITY FROM RECOVERIES OF MARKED ANIMALS”, Ecology, Vol. 85/4, pp. 930-938, https://doi.org/10.1890/03-0012.

[128] Schmuecker, S. et al. (2020), “Use of Upland and Riparian Areas by Wintering Bald Eagles and Implications for Wind Energy”, The Journal of Wildlife Management, Vol. 84/8, pp. 1578-1589, https://doi.org/10.1002/jwmg.21927.

[326] Schöll, E. and U. Nopp-Mayr (2021), “Impact of wind power plants on mammalian and avian wildlife species in shrub- and woodlands”, Biological Conservation, Vol. 256, p. 109037, https://doi.org/10.1016/j.biocon.2021.109037.

[203] Scholz, C. and C. Voigt (2022), “Diet analysis of bats killed at wind turbines suggests large-scale losses of trophic interactions”, Conservation Science and Practice, p. e12744, https://doi.org/10.1111/CSP2.12744.

[153] Scottish Government (2020), Renewable developments on Scotland’s national forests and lands: EIR release, https://www.gov.scot/publications/foi-19-02646/.

[87] SEER (2022), Benthic Disturbance from offshore Wind Foundations, Anchors, and Cables, Tethys, https://tethys.pnnl.gov/summaries/benthic-disturbance-offshore-wind-foundations-anchors-cables.

[166] Shaffer, J. and D. Buhl (2015), “Effects of wind-energy facilities on breeding grassland bird distributions”, Conservation Biology, Vol. 30/1, pp. 59-71, https://doi.org/10.1111/cobi.12569.

[227] Shobrak, M. (2012), “Electrocution and collision of birds with power lines in Saudi Arabia”, Zoology in the Middle East, Vol. 57/1, pp. 45-52, https://doi.org/10.1080/09397140.2012.10648962.

[269] Silva, J. et al. (2010), “Estimating the influence of overhead transmission power lines and landscape context on the density of little bustard Tetrax tetrax breeding populations”, Ecological Modelling, Vol. 221/16, pp. 1954-1963, https://doi.org/10.1016/j.ecolmodel.2010.03.027.

[175] Skarin, A., P. Sandström and M. Alam (2018), “Out of sight of wind turbines—Reindeer response to wind farms in operation”, Ecology and Evolution, Vol. 8/19, pp. 9906-9919, https://doi.org/10.1002/ECE3.4476.

[112] Skov, H. et al. (2018), Bird Collision Avoidance Study, http://www.nirasconsulting.co.uk (accessed on 1 July 2022).

[96] Smallwood, K. (2013), “Comparing bird and bat fatality-rate estimates among North American wind-energy projects”, Wind Energy and Wildlife Conservation, Vol. 37/1, pp. 19-33, https://doi.org/10.1002/wsb.260.

[105] Smallwood, K. (2013), “Comparing bird and bat fatality-rate estimates among North American wind-energy projects”, Wildlife Society Bulletin, Vol. 37/1, pp. 19-33, https://doi.org/10.1002/wsb.260.

[148] Smallwood, K. and D. Bell (2020), “Effects of Wind Turbine Curtailment on Bird and Bat Fatalities”, The Journal of Wildlife Management, Vol. 84/4, pp. 685-696, https://doi.org/10.1002/jwmg.21844.

[131] Smallwood, K. and B. Karas (2009), “Avian and Bat Fatality Rates at Old-Generation and Repowered Wind Turbines in California”, Journal of Wildlife Management, Vol. 73/7, pp. 1062-1071, https://doi.org/10.2193/2008-464.

[147] Smallwood, K. and C. Thelander (2008), “Bird Mortality in the Altamont Pass Wind Resource Area, California”, Journal of Wildlife Management, Vol. 72/1, pp. 215-223, https://doi.org/10.2193/2007-032.

[173] Smith, K. et al. (2020), “Pronghorn Winter Resource Selection Before and After Wind Energy Development in South-Central Wyoming”, Rangeland Ecology & Management, Vol. 73/2, pp. 227-233, https://doi.org/10.1016/j.rama.2019.12.004.

[262] Smith, M. et al. (2008), “Mammalian Predator Distribution Around a Transmission Line”, Southeastern Naturalist, https://bioone.org/journals/Southeastern-Naturalist/volume-7/issue-2/1528-7092(2008)7[289:MPDAAT]2.0.CO;2/Mammalian-Predator-Distribution-Around-a-Transmission-Line/10.1656/1528-7092(2008)7[289:MPDAAT]2.0.CO;2.short (accessed on 2 August 2022).

[15] SolarPACES (2018), How CSP Works: Tower, Trough, Fresnel or Dish - SolarPACES, https://www.solarpaces.org/how-csp-works/ (accessed on 16 December 2021).

[313] Sonter, L., S. Ali and J. Watson (2018), “Mining and biodiversity: key issues and research needs in conservation science”, Proceedings of the Royal Society B: Biological Sciences, Vol. 285/1892, p. 20181926, https://doi.org/10.1098/rspb.2018.1926.

[307] Sonter, L. et al. (2020), “Renewable energy production will exacerbate mining threats to biodiversity”, Nature Communications 2020 11:1, Vol. 11/1, pp. 1-6, https://doi.org/10.1038/s41467-020-17928-5.

[323] Sonter, L. et al. (2017), “Mining drives extensive deforestation in the Brazilian Amazon”, Nature Communications, Vol. 8/1, https://doi.org/10.1038/s41467-017-00557-w.

[315] Sonter, L. et al. (2014), “Processes of land use change in mining regions”, Journal of Cleaner Production, Vol. 84, pp. 494-501, https://doi.org/10.1016/j.jclepro.2014.03.084.

[102] Sovacool, B. (2009), “Contextualizing avian mortality: A preliminary appraisal of bird and bat fatalities from wind, fossil-fuel, and nuclear electricity”, Energy Policy, Vol. 37/6, pp. 2241-2248, https://doi.org/10.1016/j.enpol.2009.02.011.

[59] Suuronen, A. et al. (2017), “The Influence of Solar Power Plants on Microclimatic Conditions and the Biotic Community in Chilean Desert Environments”, Environmental Management, Vol. 60/4, pp. 630-642, https://doi.org/10.1007/s00267-017-0906-4.

[152] Tabassum-Abbasi, M. et al. (2014), “Wind energy: Increasing deployment, rising environmental concerns”, Renewable and Sustainable Energy Reviews, Vol. 31, pp. 270-288, https://doi.org/10.1016/j.rser.2013.11.019.

[55] Taha, H. (2013), “The potential for air-temperature impact from large-scale deployment of solar photovoltaic arrays in urban areas”, Solar Energy, Vol. 91, pp. 358-367, https://doi.org/10.1016/j.solener.2012.09.014.

[2] Tanner, A. and A. Johnston (2017), “The Impact of Rural Electric Access on Deforestation Rates”, World Development, Vol. 94, pp. 174-185, https://doi.org/10.1016/j.worlddev.2016.12.046.

[60] Tanner, K., K. Moore and B. Pavlik (2014), “Changes to shade and water regimes imposed by solar development affect desert plant performance and community attributes”, Conference: 99th ESA Annual Convention, https://www.researchgate.net/publication/267287102_Changes_to_shade_and_water_regimes_imposed_by_solar_development_affect_desert_plant_performance_and_community_attributes.

[157] ter Hofstede, R. et al. (2022), “Offshore wind farms contribute to epibenthic biodiversity in the North Sea”, Journal of Sea Research, Vol. 185, p. 102229, https://doi.org/10.1016/j.seares.2022.102229.

[202] Thaker, M., A. Zambre and H. Bhosale (2018), “Wind farms have cascading impacts on ecosystems across trophic levels”, Nature Ecology & Evolution, Vol. 2/12, pp. 1854-1858, https://doi.org/10.1038/s41559-018-0707-z.

[108] Thaxter, C. et al. (2017), “Bird and bat species’ global vulnerability to collision mortality at wind farms revealed through a trait-based assessment”, Proceedings of the Royal Society, Vol. 284/1862, https://doi.org/10.1098/rspb.2017.0829.

[169] Therkildsen, O. et al. (2021), “Changes in flight paths of large-bodied birds after construction of large terrestrial wind turbines”, Journal of Environmental Management, Vol. 290, p. 112647, https://doi.org/10.1016/j.jenvman.2021.112647.

[156] Thompson, D. (ed.) (2016), “Response of migrating raptors to an increasing number of wind farms”, Journal of Applied Ecology, Vol. 53/6, pp. 1667-1675, https://doi.org/10.1111/1365-2664.12673.

[123] Thompson, M. et al. (2017), “Factors associated with bat mortality at wind energy facilities in the United States”, Biological Conservation, Vol. 215, pp. 241-245, https://doi.org/10.1016/J.BIOCON.2017.09.014.

[231] Tintó, A., J. Real and S. Mañosa (2010), “Predicting and Correcting Electrocution of Birds in Mediterranean Areas”, Journal of Wildlife Management, Vol. 74/8, pp. 1852-1862, https://doi.org/10.2193/2009-521.

[276] Tomás, G. et al. (2012), “Clutch size and egg volume in great tits (Parus major) increase under low intensity electromagnetic fields: A long-term field study”, Environmental Research, Vol. 118, pp. 40-46, https://doi.org/10.1016/j.envres.2012.07.007.

[149] Tomé, R. et al. (2017), “Radar Assisted Shutdown on Demand Ensures Zero Soaring Bird Mortality at a Wind Farm Located in a Migratory Flyway”, in Wind Energy and Wildlife Interactions, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-51272-3_7.

[31] Turney, D. and V. Fthenakis (2011), “Environmental impacts from the installation and operation of large-scale solar power plants”, Renewable and Sustainable Energy Reviews, Vol. 15/6, pp. 3261-3270, https://doi.org/10.1016/j.rser.2011.04.023.

[154] Urziceanu, M. et al. (2021), “Local-scale impact of wind energy farms on rare, endemic, and threatened plant species”, PeerJ, Vol. 9, p. e11390, https://doi.org/10.7717/peerj.11390.

[69] van de Ven, D. et al. (2021), “The potential land requirements and related land use change emissions of solar energy”, Scientific Reports, Vol. 11/1, https://doi.org/10.1038/s41598-021-82042-5.

[213] van der Weijde, A. and B. Hobbs (2012), “The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty”, Energy Economics, Vol. 34/6, pp. 2089-2101, https://doi.org/10.1016/j.eneco.2012.02.015.

[199] Van Hoey, G. et al. (2021), Overview of the effects of offshore wind farms on fisheries and aquaculture, Publications Office of the European Union.

[177] Velilla, E. et al. (2021), “Vibrational noise from wind energy‐turbines negatively impacts earthworm abundance”, Oikos, Vol. 130/6, pp. 844-849, https://doi.org/10.1111/oik.08166.

[26] Visser, E. et al. (2019), “Assessing the impacts of a utility-scale photovoltaic solar energy facility on birds in the Northern Cape, South Africa”, Renewable Energy, Vol. 133, pp. 1285-1294, https://doi.org/10.1016/j.renene.2018.08.106.

[132] Voigt, C. (2021), “Insect fatalities at wind turbines as biodiversity sinks”, Conservation Science and Practice, Vol. 3/5, p. e366, https://doi.org/10.1111/CSP2.366.

[107] Voigt, C. et al. (2022), “Wind turbines without curtailment produce large numbers of bat fatalities throughout their lifetime: A call against ignorance and neglect”, Global Ecology and Conservation, Vol. 37, p. e02149, https://doi.org/10.1016/j.gecco.2022.e02149.

[106] Voigt, C. et al. (2015), “Wildlife and renewable energy: German politics cross migratory bats”, European Journal of Wildlife Research, Vol. 61/2, pp. 213-219, https://doi.org/10.1007/s10344-015-0903-y.

[196] Voltaire, L. and O. Koutchade (2020), “Public acceptance of and heterogeneity in behavioral beach trip responses to offshore wind farm development in Catalonia (Spain)”, Resource and Energy Economics, Vol. 60, p. 101152, https://doi.org/10.1016/j.reseneeco.2020.101152.

[181] Votier, S. (ed.) (2016), “Avoidance of wind farms by harbour seals is limited to pile driving activities”, Journal of Applied Ecology, Vol. 53/6, pp. 1642-1652, https://doi.org/10.1111/1365-2664.12678.

[75] Walston, L. et al. (2021), “Modeling the ecosystem services of native vegetation management practices at solar energy facilities in the Midwestern United States”, Ecosystem Services, Vol. 47, p. 101227, https://doi.org/10.1016/j.ecoser.2020.101227.

[21] Walston, L. et al. (2016), “A preliminary assessment of avian mortality at utility-scale solar energy facilities in the United States”, Renewable Energy, Vol. 92, pp. 405-414, https://doi.org/10.1016/j.renene.2016.02.041.

[27] Walston, L. et al. (2016), “A preliminary assessment of avian mortality at utility-scale solar energy facilities in the United States”, Renewable Energy, Vol. 92, pp. 405-414, https://doi.org/10.1016/J.RENENE.2016.02.041.

[3] Whitehead, A., H. Kujala and B. Wintle (2017), Dealing with Cumulative Biodiversity Impacts in Strategic Environmental Assessment: A New Frontier for Conservation Planning, Wiley-Blackwell, https://doi.org/10.1111/conl.12260.

[137] Wilson (2006), Collision risks between marine renewable energy devices and mammals, fish and diving birds: Report to the Scottish executive.

[44] Wilson, M. et al. (2015), “Habitat fragmentation and biodiversity conservation: key findings and future challenges”, Landscape Ecology, Vol. 31/2, pp. 219-227, https://doi.org/10.1007/s10980-015-0312-3.

[252] Wilson, R., H. Marsh and J. Winter (2007), “Importance of canopy connectivity for home range and movements of the rainforest arboreal ringtail possum (Hemibelideus lemuroides)”, Wildlife Research, Vol. 34/3, p. 177, https://doi.org/10.1071/wr06114.

[324] Wiser, R. et al. (2021), “Land-Based Wind Market Report: 2021 Edition”, http://www.osti.gov (accessed on 27 October 2021).

[57] Wu, Z. et al. (2014), “Environmental impacts of large-scale CSP plants in northwestern China”, Environ. Sci.: Processes Impacts, Vol. 16/10, pp. 2432-2441, https://doi.org/10.1039/c4em00235k.

[311] WWF (2021), In too deep: What we know, and don’t know, about deep seabed mining, https://wwfint.awsassets.panda.org/downloads/in_too_deep_what_we_know_and_don_t_know_about_deep_seabed_mining_1.pdf.

[314] Yang, X. et al. (2013), “China’s ion-adsorption rare earth resources, mining consequences and preservation”, Environmental Development, Vol. 8, pp. 131-136, https://doi.org/10.1016/j.envdev.2013.03.006.

[24] Zhang, J. (ed.) (2020), “A summary of bird mortality at photovoltaic utility scale solar facilities in the Southwestern U.S.”, PLOS ONE, Vol. 15/4, p. e0232034, https://doi.org/10.1371/journal.pone.0232034.

[206] Zimmerling, J. and C. Francis (2016), “Bat mortality due to wind turbines in Canada”, The Journal of Wildlife Management, Vol. 80/8, pp. 1360-1369, https://doi.org/10.1002/jwmg.21128.

[99] Zimmerling, J. et al. (2013), “Canadian Estimate of Bird Mortality Due to Collisions and Direct Habitat Loss Associated with Wind Turbine Developments”, Avian Conservation and Ecology, Vol. 8/2, https://doi.org/10.5751/ace-00609-080210.

Notes

← 1. For sites with multiple full study years, each year was treated as a separate study and is indicated by year in the analyses. Each study is referred to as a site-year.

← 2. The cause of mortality could not be determined for 61% of carcasses.

← 3. A pre-construction, plant conservation decision that designated buffer zones around rare desert plants within the solar field, which were roped off and left undisturbed.

← 4. Mortality estimates of individual studies vary in how raw counts are adjusted for known sources of detection error and sampling intensity, for example, carcass removal by predators or the distance from the wind turbine that is searched.

← 5. See (Popper et al., 2022[325]) for a list of short-term priorities for fish and marine invertebrates identified by a workgroup of the 2020 State of the Science Workshop on Wildlife and Offshore Wind Energy.

← 6. (Schöll and Nopp-Mayr, 2021[326]) for example, note a relative absence of studies looking at shrub and woodland species, despite woodland being increasingly targeted for wind energy development.

← 7. Aluminium and steel are not included in this estimate.

← 8. Tropical and subtropical moist broadleaf forest; tropical and subtropical grasslands, savannahs and shrublands; deserts and xeric shrublands; tropical and subtropical dry broadleaf forests; and montane grasslands and shrublands.

← 9. Species-richness refers to the number of species in an area.

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