Estimates of aerial vertebrate mortality at wind farms in a bird migration corridor and bat diversity hotspot

Journal Pre-proof Estimates of aerial vertebrate mortality at wind farms in a bird migration corridor and bat diversity hotspot Sergio A. Cabrera-Cruz, Juan Cervantes-Pasqualli, Montserrat Franquesa-Soler, Óscar Muñoz-Jiménez, Guillermo Rodríguez-Aguilar, Rafael Villegas-Patraca PII:

S2351-9894(19)30307-5

DOI:

https://doi.org/10.1016/j.gecco.2020.e00966

Reference:

GECCO 966

To appear in:

Global Ecology and Conservation

Received Date: 21 April 2019 Revised Date:

11 February 2020

Accepted Date: 11 February 2020

Please cite this article as: Cabrera-Cruz, S.A., Cervantes-Pasqualli, J., Franquesa-Soler, M., MuñozJiménez, Ó., Rodríguez-Aguilar, G., Villegas-Patraca, R., Estimates of aerial vertebrate mortality at wind farms in a bird migration corridor and bat diversity hotspot, Global Ecology and Conservation (2020), doi: https://doi.org/10.1016/j.gecco.2020.e00966. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.

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Title: Estimates of aerial vertebrate mortality at wind farms in a bird migration corridor and bat diversity hotspot

Author names and affiliations: Sergio A. Cabrera-Cruza Present address: University of Delaware, Department of Entomology and Wildlife Ecology, 531 South College Avenue 250, Newark, DE 19716, USA. [email protected] Juan Cervantes-Pasquallia Present address: Instituto de Ecología A.C., Red de Ecología Funcional, Carretera antigua a Coatepec 351, El Haya, Xalapa, Veracruz 91070 México. [email protected] Montserrat Franquesa-Solera Present address: Universidad Nacional Autónoma de México, Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Antigua Carretera a Pátzcuaro 8701, Ex Hacienda de San José de la Huerta, Morelia, Michoacán 58190, México. [email protected] Óscar Muñoz-Jiméneza ([email protected]) Guillermo Rodríguez-Aguilara ([email protected]) Rafael Villegas-Patracaa ([email protected]) a

Instituto de Ecología A.C., Unidad de Servicios Profesionales Altamente Especializados, Carretera antigua a Coatepec esquina Camino a Rancho Viejo 1, Fraccionamiento Briones, Coatepec, Veracruz 91520, México

Corresponding author (post-publication): Rafael Villegas-Patraca (email address: [email protected], phone number: +52(228)8334629)

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ABSTRACT

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Three major flyways of the Nearctic – Neotropical bird migration system converge at the coastal plains of the Isthmus of Tehuantepec, Mexico. Approximately one million vultures and raptors traverse the area during the autumn migration season, and more than 60 species of nocturnally migrating birds have been recorded there. Furthermore, more than 60 bat species inhabit this region, which also harbors the most important wind resource area of the country. There, the number of wind turbines increased from 98 to >1500 between 2006 and 2015. We estimated bird and bat mortality at three wind farms in the Isthmus, correcting for different sources of bias. Between June and November 2015, we found 75 bird and 72 bat carcasses, belonging to 30 and 20 species respectively. Although we found more bird than bat carcasses, our corrected estimates are higher for bats than for birds. Corrected mortality ranges between 4.0 – 5.6 birds/MW and 8.9 – 21.4 bats/MW during the months of the study, or between 9.18 – 12.95 birds/MW/year and 20.44 – 43.67 bats/MW/year. Contrary to patterns of aerial vertebrate mortality at wind farms in temperate latitudes, all bat and most bird fatalities were from resident species, even when considering bird migration months only. Corrected bird mortality was highest at the wind farm with the tallest wind turbines. Our estimated fatalities/MW/year are higher than rates of bat and bird mortality recorded at numerous wind farms in the United States, and our estimates may still be biased low. Thus, our results offer a first glimpse to the magnitude of bird and bat mortality at this tropical hotspot for aerial vertebrates. More than 15 wind farms are currently operating in the region, hence a larger-scale effort is needed to fully understand the cumulative mortality of aerial vertebrates, particularly of resident species, at this wind energy hub and diversity hotspot.

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Keywords: bird mortality, bat mortality, environmental impact, Isthmus of Tehuantepec, Mexico, wind energy.

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1. Introduction

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Wind energy has become an increasingly important sector of the renewable energy industry, contributing to satisfy a growing demand for electricity worldwide (Jacobson and Delucchi, 2011; Pasqualetti et al., 2004). In Mexico, electric generation from wind increased from 5.0GWh to 8,745.1GWh between 2005 and 2015 (SENER, 2016), where most of the wind energy developments took place at the southern Isthmus of Tehuantepec (hereafter the Isthmus; Alemán-Nava et al., 2014). At this region, the number of installed wind turbines increased from 98 to >1500 in the same period (pers. obs.).

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The Isthmus sits in the transition between the Nearctic and Neotropical realms (RíosMuñoz, 2013), creating a biodiversity hotspot. At least 64 bat species occur at its southern end (García-Grajales and Buenrostro-Silva, 2012), one of which was recently discovered to occur in the region after two carcasses were found at different wind farms (Torres-Morales et al., 2014). The Isthmus is the narrowest landmass between the Gulf of Mexico and the Pacific Ocean (~220 km at its narrowest stretch), serving as a corridor for migratory birds from at least three migratory flyways of the Nearctic-Neotropical migration system (Bildstein and Zalles, 2001; Binford, 1989; Lamb et al., 2018). On average, more than one million soaring birds traverse the region every autumn (Cabrera-Cruz et al., 2017a), and nearly 60 species of Nearctic-Neotropical nocturnal migrants have been recorded in the same area (Cabrera-Cruz et al., 2017b; VillegasPatraca et al., 2012a). Furthermore, the Isthmus is considered an Important Bird Area based on all four criteria used for such designation (BirdLife International, 2018).

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The concentration of wind farms in the Isthmus has sparked concerns about collisions with wind turbines causing elevated mortality of aerial vertebrates. However, only one published study has evaluated bat mortality in the Isthmus but it was limited to a single wind farm (Bolívar-Cimé et al., 2016), and bird mortality surveys at wind farms in the region remain unpublished. Furthermore, estimates of both bird and bat mortality at wind energy facilities around the world are geographically biased towards temperate countries in North America and Europe (Thaxter et al., 2017). Thus, investigation of aerial vertebrate mortality at wind farms in the Isthmus, a tropical wind energy hub with high bat diversity and large volumes of bird migration, was warranted.

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In this study we document wind turbine-related mortality of birds and bats at a hotspot for aerial vertebrates, generating information that highlights some of the differences in mortality patterns between wind energy facilities at temperate and tropical latitudes.

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2. Material and Methods

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2.1 Study area

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We searched for carcasses of aerial vertebrates at three different wind farms in the southern Isthmus of Tehuantepec in Oaxaca, Mexico (Fig. 1). The western, northern, and eastern wind farms have an installed capacity of 26.35 MW, 86.5 MW, and 160 MW respectively. Throughout the manuscript, we present details and results for each wind farm from west to east. Wind turbines at each wind farm sit at the far edge of rectangular servicing areas (Fig. A1) and are 3

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connected by access roads ~6 m wide. Transects of turbines are arranged in a general northsouth direction, generally oriented west-east (Fig. 1). The number of turbines, maximum turbine height, and distance between turbines along transects vary per wind farm (Table 1), but all turbines are on tubular towers. Wind farms are located in the coastal plains of the Isthmus, the region with Mexico’s highest wind energy potential (Alemán-Nava et al., 2014; Elliott et al., 2003), which has a gentle elevation gradient, with the northernmost and southernmost wind turbines sitting at approximately 50 and 20 meters above sea level, respectively. Between the western and northern wind farms lies a locally protected area partly encompassing the Tolistoque ridge where we have identified at least three bat roosts (GRA and OMJ, personal observations; Fig. 1), and the Ojo de Agua communal protected area, which is home to at least 32 bat species (Briones-Salas et al., 2013). We have also identified three more bat roosts to the east of the northern wind farm, and another to the south. During autumn migration season, thousands of soaring migratory birds reach the coastal plains of the Isthmus either through the west or east of Tolistoque (Cabrera-Cruz et al., 2017a), potentially encountering the western or the northern and eastern wind farms, respectively. The area occupied by these wind farms is immersed in a matrix of agricultural land (mostly seasonal sorghum cultures), with patches of rangeland, deciduous forest, and second-growth deciduous forest (Muñoz-Jiménez et al., 2019).

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2.2 Mortality surveys

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We conducted carcass searches between June 6 and November 30, 2015. Every day, except under inclement weather (i.e. rain), a team of three searchers visited one of the wind farms (western, northern, or eastern). Searchers walked linear transects along access roads connecting wind turbines, constantly searching for carcasses of aerial vertebrates, walking parallel to each other and always starting at one of the far ends of each access road (i.e. at the first or last wind turbine in the road). Vehicles transit access roads, but speed is limited to 15 – 20 km/h, slow enough to prevent collisions with wildlife; hence, we considered carcasses found on access roads to be a casualty of a fatal interaction with wind turbines. When searchers arrived to a wind turbine, they searched for carcasses in the rectangular servicing area, and then continued along the access roads. Searches started approximately 20 – 30 minutes after sunrise, as soon as there was enough light to see the ground and spot possible carcasses, and lasted usually until around noon or until searchers considered the activity safe (temperature can exceed 40°C in our study site), but always after completing the full transect of turbines along the road. Thus, each day searchers surveyed a different number of access roads and turbines, depending on the wind farm visited and weather. If the wind farm was not fully sampled in a single day, searchers surveyed the remaining road(s) and turbines during the next visit. Searchers registered carcasses in any state of decomposition that had not been previously detected, including those partially buried due to predation by arthropods (Villegas-Patraca et al., 2012b), and feather spots in the case of birds.

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Access roads and areas facilitate wind farm maintenance operations, hence they are kept mostly clear of vegetation. The servicing pads, rectangular areas surrounding turbines with same width as the whole servicing area but length varying by wind farm, are typically covered with gravel, while the rest of the servicing areas are usually covered by grass, weeds, and 4

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sometimes small shrubs. Thus the major proportion of the area searched was bare ground (roads) with a small proportion of gravel (pads), followed by grassy/weedy areas (servicing areas, adjacent to the graveled pads).

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Every month between July and November for the western wind farm, and between June and November for the northern and eastern wind farms, our searchers visited two, eight, and two times the western, northern, and eastern wind farms respectively, representing a total of 10, 48, and 12 full-wind-farm carcass searches at each wind farm. Searches were performed within periods of 139, 177, and 162 days (i.e. number of days between first and last search), and the average search interval (i.e. number of days between carcass searches) was of 13.9, 3.7, and 13.5 days at the western, northern, and eastern wind farms respectively.

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When searchers found a carcass, they collected the specimen and identified it to species in situ when possible, otherwise they identified it later with the aid of field guides and measuring instruments. For each carcass, searchers recorded: wind farm, GPS coordinates, date, ID number of closest turbine, name of the searcher, and a unique identifier to the carcass.

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2.3. Estimation of mortality

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Typically, not all carcasses are found during searches. This is in part because of imperfect searcher efficiency, because not all animals fall within the search area, and because some carcasses are scavenged and have different persistence probabilities. Hence, the number of carcasses found at a given wind farm does not reflect the true mortality, and a correction is needed. To estimate the number of animals that died due to a fatal interaction with wind turbines, we used an approach that requires first estimating the probability of finding an animal killed by a wind turbine (p*). We estimated p* using the function ‘pkorner’ from the package ‘carcass’ (Korner-Nievergelt et al., 2015) in R 3.3 (R Development Core Team, 2017). This function follows the method introduced by Korner-Nievergelt et al. (2011): ∗

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=

1− 1−

∑

−

1−

Where:

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p* = probability of finding an animal killed by a wind turbine

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f = searcher efficiency (average detection probability of a carcass during searches)

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s = daily carcass persistence (probability of a carcass remaining on site within 24 hours)

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d = search interval (days between searches)

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n = number of searches in the study

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This equation assumes that f and s are constant over time (Korner-Nievergelt et al. 2011). As implemented in R, the function requires the upper and lower 95% CI for s and f; and a statement specifying if f was constant over time, which we set as TRUE. We estimated this 5

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probability for birds and bats at each wind farm separately. Below we detail the estimation of f and s.

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2.3.1 Searcher efficiency (f)

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Detection of bird and bat carcasses varies by searcher, ground cover, carcass size, and other factors (Kunz et al., 2007; Peters et al., 2014). To account for searcher bias in our estimation of mortality, we evaluated the efficiency of our searchers at detecting carcasses of different sizes and under different ground cover conditions.

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We conducted six independent evaluations of searcher efficiency (at 2 ground covers x 3 searches), during which we distributed a total of 95 bird and 31 bat carcasses at randomly selected points within wind farms. We used frozen carcasses collected at these and other wind farms in the region during previous years. In the case of birds, we classified carcasses in three different size classes: large, medium, and small. Roadside hawk (Rupornis magnirostris), Whitetipped dove (Leptotila verreauxi) and Orange-breasted bunting (Passerina leclancherii) are examples of each category, respectively. We distributed carcasses in two different ground cover types: bare (e.g. graveled pads and access roads) and covered (e.g. grassy/weedy portions of servicing areas, or grassland surrounding wind turbines, when possible; Table A1). In the case of bats, we did not classify carcasses by size.

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Carcasses detected by searchers were immediately picked up, and at the end of every test evaluating their efficiency, we removed carcasses that were not detected, to prevent counting a trial carcass as a fatality. We recorded the number of detections and no-detections made by the searchers and estimated their efficiency using the function ‘search.efficiency’ from the R package ‘carcass’ (Korner-Nievergelt et al., 2015). For simplicity, we averaged the efficiency of finding carcasses of each group of aerial vertebrate in both ground cover types. Thus, we obtained two estimates of searcher efficiency, one for birds and other for bats.

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2.3.2 Carcass persistence probability (s)

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We estimated the daily probability that a carcass remains around the turbines using information from previous research. Persistence rate of small and large bird carcasses at the northern windfarm ranges between 2.1 and 4.4 days in the dry season (March-June), and between 2.7 and 4.4 days in the rainy season (July-November); and persistence rate of bat carcasses is 2 days in both seasons (Villegas-Patraca et al., 2012b). Since our searches encompassed months of the dry (June) and rainy seasons (July – October), we considered mean persistence times from both seasons. For birds, we estimated an average of (2.1 + 4.4 + 2.7 + 4.4) / 4 = 3.4 days of bird carcass persistence, an average removal probability of 1/3.4 = 0.2941, and finally a daily persistence probability of 1 - 0.2941 = 0.7059 (95% CI = 0.64 – 0.85). For bats, we estimated an average of (2 + 2 + 2 + 2) / 4 = 2 days of bat carcass persistence, an average removal probability of 1/2 = 0.5, and a daily persistence probability of 1 - 0.5 = 0.5 (95% CI = 6

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0.45 – 0. 55). Given the close vicinity of the three wind farms, and that vegetation type does not seem to affect persistence rates of carcasses within the northern wind farm (Villegas-Patraca et al., 2012b), we assumed a similar persistence rate of bird and bat carcasses in the three wind farms.

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2.3.3 Estimating mortality

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We used an approach that implements Bayes Theorem to estimate the posterior distribution of the number of fatalities (Korner-Nievergelt et al., 2015), such that for any potential number of fatalities x, the probability (P) that mortality (N) equals x is given by: =

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=

∑

1−

1−

Where:

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c = number of carcasses found

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p = probability of carcass detection

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The probability of carcass detection (p), or the probability that an animal that died during the study period was found by a searcher, is a function of the parameters s, f, d, and n described in the previous section. But it is also affected in a simple multiplicative way by the proportion of carcasses that fell in the search area (a), such that p = ap* (Korner-Nievergelt et al., 2015).

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To estimate the proportion of killed animals that fall in the search area (a), we added the product of multiplying the proportion of area that was searched in 10m radial bands from the turbine, times the typical proportion of carcasses found in the corresponding band (KornerNievergelt et al. 2015). To estimate the proportion of area searched of each 10-m radial band we first used QGIS 3.8 (QGIS Development Team, 2019) to digitize the search areas around a typical wind turbine of each wind farm (i.e. the service area, pad included, and the adjacent access road) and estimated the total search area. For the western and northern wind farms we created eight 10m-wide radial bands radiating from the turbines and estimated their area. For the eastern wind farm, which has the tallest turbines, we created ten 10-m radial bands. Finally, we estimated the proportion of each band that was actually searched by intersecting each 10-m band to the search areas (Fig. A2). We estimated the mean proportion of animals that fell by 10-m bands using data from three empirical studies contained in the batdist dataset, available in the R package carcass (Korner-Nievergelt et al., 2015). The data in batdist shows that the highest proportion of bat carcasses concentrate in radial bands 2 – 4 (i.e. between 10 – 40 meters from the turbine), and that the proportion of carcasses decreases thereafter, a pattern that has been observed in other studies (Kerns et al. 2005; Hull and Muir 2010; Huso and Dalthorp 2014). Similarly, a recent summary of bird fatalities throughout the United States suggests that about 75% of bird carcasses are found within 75-m from the turbines (AWWI, 7

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2019). Thus, we used the data in batdist as proxy for the concentration of both bat and bird carcasses in radial bands around turbines. However, the empirical studies in batdist contain proportions of carcasses up to seven 10-m radial bands only. Because the proportion of carcasses decreases with further distance from the turbines, for simplicity we assumed that the proportions of carcasses in radial bands >70m are half the proportion of the preceding band. Thus, considering that the average proportion of carcasses in the 7th radial band (i.e. between 60-m and 70-m) is 0.05, we set the proportions for the 8th, 9th and 10th radial bands as 0.05/2, 0.05/4, and 0.05/8 respectively.

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After estimating a, we used the function ‘estimateN’ from the R package ‘carcass’ (Korner-Nievergelt et al., 2015) to estimate bird and bat mortality at each wind farm using the model in the equation above. estimateN accounts for the uncertainty in the estimate of detection probability (p) and returns the median of the posterior distribution along with its lower and upper 95% CI (Korner-Nievergelt et al., 2015).

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For each combination of wind farm – animal group (birds or bats), we specified in estimateN: 1) the number of carcasses found (c), 2) the estimated probability of finding an animal killed by a wind turbine (p*), 3) the proportion of killed animals that fall in the search area (a), with its upper and lower 95% CI; and 4) the maximal possible number of animals killed for which the posterior probability is estimated (we used 10 000; this large number was set to override an upper limit of the posterior distribution that is set within ‘estimateN’ for computational reasons; F. Korner-Nievergelt, pers. comm.). Finally, we divided the estimated number of fatalities from each wind farm by their respective nominal production capacity in order to obtain the estimated bird and bat fatalities/MW for the interval of days when we conducted carcass searches at each wind farm. We further extrapolated this to 365 days, to estimate a broad approximation of bird and bat fatalities/MW/year.

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3. Results

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During the whole study period we found between 4 (western) and 37 (northern) bird carcasses belonging to 26 species and 7 morphospecies (individuals identified at the level of genus), and between 23 (eastern) and 49 (northern) bat carcasses (Table 2) belonging to 18 species and 3 morphospecies. Four bird and two bat morphospecies belong to a genus other than the rest of the carcasses found; hence, at least 30 bird species and 20 bat species had a fatal interaction with wind turbines in our study area. We also found two groups of feathers that we could not identify, and 6 bat carcasses that we identified to the family level only (Table A2).

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The average area searched around each wind turbine, considering up to eight 10-m radial bands for the western and northern wind farms were of 2001.3 m2 and 2056.5 m2, respectively. For the eastern wind farm, considering ten 10-m radial bands around each turbine, the average search area was of 4427.2 m2. The average efficiency of our searchers (parameter f) finding bird and bat carcasses was of 0.60 (SE = 0.18; 95% CI= 0.23 – 0.77), and 0.43 (SE = 0.11; 95% CI= 0.23 – 0.67) respectively. Our estimated bird carcass detection 8

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probability (and 95% CI; parameter p*) for the western wind farm was of 0.10 (0.05 – 0.19); we did not find bat carcasses at the western wind farm. Bird and bat carcass detection probabilities (and 95% CI) for the northern windfarm were of 0.31 (0.16 – 0.49) and 0.11 (0.05 – 0.16); for the western eastern windfarm were of 0.10 (0.05 – 0.19) and 0.03 (0.01 – 0.05).

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We estimate that the proportion of killed animals that fell into the searched area (parameter a) was of 0.35, 0.24, and 0.52 for the western, northern, and eastern wind farms respectively. Our corrected estimation of mortality for the three wind farms during the months of the study ranges between 4.0 – 5.6 birds/MW and 8.9 – 21.4 bats/MW, or between 9.18 – 12.95 birds/MW/year and 20.44 – 43.67 bats/MW/year. (Table 2). We found more bird and bat carcasses at the northern, followed by eastern and western wind farms, but estimated bird mortality at the eastern wind farm, with the tallest turbines, is ~5 times higher than at western wind farm, and 1.3 times higher than at the northern wind farm. However, the estimated fatalities/MW and fatalities/MW/year are relatively similar among wind farms. Corrected bat mortality/MW and mortality/MW/year is >2 times higher at the northern than at the eastern wind farm.

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Bird mortality was overrepresented by one taxonomic group: 24 out of 75 of carcasses belong to the Columbidae family (doves and pigeons; Table A2). Of these, 23 (32%) are from resident species of the Ground-doves group (genus Columbina), and the White-tipped dove (Leptotila verreauxi). The taxonomic family with the second highest mortality was Icteridae with 9 carcasses, all of resident species. The Cuculidae, Odontophoridae, and Tyrannidae families had 7 carcasses each. During migration season (September – November), bird mortality was higher in resident (n = 24 carcasses) than in migratory species (n = 12 carcasses). Bird carcasses found during migration months belong to 19 species and six morphospecies. During migration months, the Columbidae family had the highest mortality (10 carcasses) followed by Icteridae, Tyrannidae and Vireonidae (5, 4, and 4 carcasses each).

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The great majority (64%) of bat mortality concentrated on species of four taxonomic families, with Phyllostomidae, Mormoopidae, Molossidae and Vespertilionidae contributing with the highest number of carcasses (n = 21, 17, 13, and 13 respectively; Table A2). All carcasses are from bat species resident in the region.

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4. Discussion

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During the six months of our surveys we found 75 bird and 72 bat carcasses. However, our estimated bird and bat fatalities/MW/year rank among the highest when compared to wind farms in the United States (US) (Strickland et al., 2011). For example, our estimates of bat fatality/MW/year are within the range reported for wind farms in the Eastern US, where the greatest rates of bat mortality have been recorded in North America (Arnett et al., 2008). Similarly, our estimated bird fatality/MW/year at the three wind farms is higher than in most regions of the contiguous US except in California (Loss et al., 2013). Thus, our results suggest that mortality of aerial vertebrates in the Isthmus, a small region in southern Mexico, is comparable or even higher than the mortality estimated for multiple regions of the contiguous 9

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US. However, our estimated fatalities/MW/year derive from simple extrapolation of the fatalities estimated for the period our searches took place, and assume a constant fatality rate throughout the year, which most likely is not true. Nevertheless, because annual mortality estimates based on partial sampling are thought to derive in substantial underestimation of actual mortality (Loss et al., 2013), we would expect that full-year surveys at the Isthmus would yield mortality estimates higher that those presented here. Hence, this result should be taken as a first broad estimation of the mortality of aerial vertebrates in the Isthmus that we hope future efforts will refine, but highlight the need for further research in the area. Furthermore, we also consider that the mortality estimated for the six months of our study may be biased low for the reasons discussed below.

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First, for our searcher efficiency trials we re-used carcasses found during previous surveys. We did this attempting to recreate the type of carcasses that our searchers would find, assuming that this would provide a good test of their searching efficiency. However, there are at least two problems with this approach, one being that vertebrate scavengers may have reduced interest in old carcasses, and the other that searchers were tested on a set of carcasses that had already been found. The latter issue may have been more impactful in the case of bats, for which we did not categorize carcasses into size classes as we did with birds. Body mass of bat species found under turbines in this study and those found by Bolívar-Cimé et al. (2016) at the northern wind farm range between ~5g (Natalus stramineus [currently N. mexicanus]; Mexican funnel-eared bat; Tejedor, 2011) and ~66g (Artibeus lituratus, Great fruit-eating bat; Stockwell 2001). It is likely that detection rates of carcasses from large bat species are higher than for smaller species, and that we reused carcasses from large species. We did not keep a record of the identity of the bat carcasses used for our searcher efficiency trials. Both of these problems may have resulted in overestimating searcher efficiency and consequently underestimating mortality.

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Second, our carcass searches were conducted in a limited area (i.e. servicing areas and access roads), whereas typical methods involve searching for carcasses in the area surrounding turbines within a distance related for example to turbine height (Kunz et al., 2007). Thus, we under-searched wind turbines for bird and bat fatalities. For example, for the northern wind farm we estimate that the area searched around each turbine amounts to 7.2% of a circular area with a 75m radius, the maximum turbine height in that wind farm. The three wind farms visited in this study were built on property leased from local owners, who only leased the land needed for the construction and operation of the wind farms (i.e. the areas searched for carcasses) while the rest of the lands are used mainly for agricultural activities. Thus, wind turbines are immersed in a matrix of private lands to which we did not have access. However, although our carcass searches did not cover all the area typically searched, we did have access to the areas closest to the base of each wind turbine, where the highest proportion of carcasses usually occur (Hull and Muir, 2010; Huso and Dalthorp, 2014; AWWI, 2019). The distribution of carcasses around wind turbines is affected by multiple factors including wind direction (KornerNievergelt et al. 2015). Wind direction in the coastal plains of the Isthmus is predominantly from the North year round (Romero-Centeno et al., 2003), and access roads of all wind farms are downwind of the turbines, hence our searches were fortuitously on the side where one would expect bird and bat carcasses to fall predominantly due to the influence of the wind. 10

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Furthermore, when estimating the proportion of killed animals that fall into the search area it is better to use an estimate of the proportion of carcasses that are in the searched area than the searched area itself (F. Korner-Nievergelt, pers. comm.), as we did. Bolívar-Cimé et al. (2016) followed the same approach and our corrected estimates of bat mortality for the northern wind farm are similar. Had we estimated the posterior probability of fatalities considering the search area instead of the proportion of carcasses that fall there, our estimated mortality would have been much higher. While we consider that the approach we used is appropriate, we also acknowledge that under-sampling the turbines leads to mortality underestimation that should be tried to solve in future efforts in the Isthmus. Finally, our estimates do not consider fatalities involving animals that may have moved outside the search areas on their own before dying.

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Despite our likely underestimation of bird and bat mortality, some of our general results contrast with patterns of aerial vertebrate fatalities related to wind energy developments in more temperate latitudes. For example, raptors are one the groups of birds most vulnerable to collisions with wind turbines in the United States, and abundance seems to be an important predictor of their mortality at wind energy developments (Strickland et al., 2011). However, we did not find any raptor during our searches, even though our study period encompassed the peak of autumn bird migration when tens of thousands Broad-winged Hawks and Swainson’s Hawks traverse our study area every year (Cabrera-Cruz and Villegas-Patraca, 2016, CabreraCruz et al., 2017a, Villegas-Patraca et al., 2014).

388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408

Our results also contrast with patterns of bat mortality in temperate areas. In terms of richness, 24 bat species have been recorded to have fatal interactions with wind turbines across North America (AWWI, 2017) while we found 20 bat species only in six months at a small region in southern Mexico. In terms of life history, bat mortality at wind farms in North America (Arnett et al., 2008), Brazil (Barros et al., 2015), and in temperate regions worldwide (Thaxter et al., 2017) is highly biased towards migratory species or species with long dispersal movements, but all bat carcasses found in our study area belong to resident species (Bolívar-Cimé et al., 2016), suggesting that the dynamics of bat mortality in this region respond to a different species trait, possibly related to patterns of aerial habitat use (Arnett et al., 2016; Bolívar-Cimé et al., 2016). We acknowledge, however, 1) that migratory movements of bats in the Neotropics are poorly understood (Fraser et al., 2010), 2) that at least one of the species found in our study (Artibeus lituratus) is known to perform long-distance movements in other tropical regions (Arnone et al., 2016), and 3) that the migratory Western Red bat (Lasiurus blossevillii, of which we found three carcasses) occurs in the Isthmus (Cryan, 2003). Hence migration and long dispersal movements may also relate to bat mortality in this region. Nevertheless, mortality of non-migratory bat species occurs in southern Europe and Africa too (Arnett et al., 2016). We consider necessary further efforts to understand long-distance dispersal movements of bats in this region and in southern Mexico in general. Interestingly, Molossidae (Chiroptera) was among the families with greatest fatalities in our study area, and it has been identified as highly vulnerable to wind farms around the world (Barros et al., 2015; Rodríguez-Durán and FelicianoRobles, 2015; Thaxter et al., 2017).

409 410

Although we found more bird than bat carcasses, our corrected estimates is higher for bats than for birds, supporting the notion that bat mortality at wind farms outnumbers bird 11

411 412 413 414 415 416 417 418 419 420 421

mortality (AWWI, 2017), and suggesting that this pattern also occurs in tropical regions. However, our results also demonstrate that not all patterns of bird and bat mortality at wind farms in temperate latitudes repeat in the tropics, but that differences can be expected and some may still be unknown. The bird and bat fatalities estimated here highlights that mortality surveys in this and other similar regions should be made public to allow evaluating the negative impacts that wind energy developments at diversity hotspot have on aerial vertebrates, particularly of resident species. We consider that a larger-scale effort is needed to understand the cumulative mortality of aerial vertebrates at the installed wind farms in the Isthmus, and that further research is needed at this and other tropical regions to elucidate the relationships of bird and bat mortality to wind farm and landscape characteristics, as this could help reduce impacts of wind farms on aerial vertebrates.

422 423

5. Conclusions

424 425 426 427 428 429 430 431 432

Our estimates for mortality of aerial vertebrates at three wind farms in the Isthmus rank higher than estimates of bird and bat mortality at multiple wind farms in the United States. Largerscale efforts are needed to estimate the cumulative impacts that all wind farms in the Isthmus have on aerial vertebrates, particularly of resident species. Our results provide a first approximation to the annual fatality rates of aerial vertebrates due to collisions with wind farms in the Isthmus, but future efforts should improve this for example by considering larger search areas and longer search periods. We consider that further research on bird and bat mortality at wind farms in tropical areas may uncover different drivers of mortality than those known from temperate latitudes.

433 434

Acknowledgements

435 436 437

Thanks to our carcass searchers: Carlos Corona, Irani Moya, Dulce Santiago, Delfino Santiago, and Anayani Rivera, for their hard work under often strenuous conditions. Thanks to Jeffrey Buler, Todd Mabee, and two anonymous reviewers for valuable comments to this manuscript.

438 439

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592

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593

Figures (NO COLOR IN PRINT)

594 595 596 597 598 599 600 601 602 603

Figure 1. Footprint of a cluster of wind farms (light-blue polygons) at the coastal plains of the Isthmus of Tehuantepec, showing for the western, northern, and eastern wind farms an area around each wind turbine with radius equal to turbine height (green circles); along with locally protected areas (green polygons between the western and northern wind farms), and bat roosts identified in the study area (white circles). All layers are overlaid on a digital elevation model showing the Tolistoque ridge NE and NW of the western and northern wind farms respectively. Inset shows the wind energy potential of Mexico (DTU and World Bank Group, 2018), with the Isthmus of Tehuantepec enclosed by a black rectangle, and the location of the wind farms as a white circle on the south side of the Isthmus. Color version online.

604

17

605

Tables

606

Table 1. Wind turbine attributes for each wind farm. Wind farm

607

Turbines Turbine (n) Height* (m)

Service area dimensions (m)

Turbines per access roads (n)

Western 31 93 40 x 15 4 – 10 Northern 98 75 35 x 15 23 – 27 Eastern 80 125 60 x 30 6 – 23 * Turbine heights are to blade tip at 12:00 position.

Distance between turbines (m) 125 135 240

Blade length (m)

Capacity (MW)

39 24.5 39.5

0.85 0.85 2

608

18

609 610

Table 2. Bird and bat fatalities (n) and estimated mortality recorded at three wind farms in the Isthmus of Tehuantepec between 6 June and 30 November 2015. Wind farm

Birds n

Western

4

Northern

37

Eastern

34

Estimate (95% CI) 129 (39 – 381) 485 (270 – 991) 644 (322 – 1418)

Estimated fatalities/ MW 4.89

Estimated fatalities/ MW/year 12.85

5.60 4.02

Bats n

Estimate (95% CI)

Estimated fatalities/ MW NA

0

NA

11.56

49

9.06

23

1837 21.23 (1027 – 3464) 1454 9.08 (759 – 2819)

Estimated fatalities/ MW/year NA 43.79 20.47

19

611

20

Appendix Table A1. Raw data from our evaluations of observer efficiency: number of bird and bat carcasses placed and found at surfaces with different ground cover types in three wind farms in the Isthmus of Tehuantepec, southern Mexico. Ground cover grass/shrub grass/shrub grass/shrub bare bare bare grass/shrub grass/shrub grass/shrub bare bare bare grass/shrub grass/shrub grass/shrub bare bare bare grass/shrub grass/shrub grass/shrub bare bare bare

Group bird bird bird bird bird bird bird bird bird bird bird bird bird bird bird bird bird bird bat bat bat bat bat bat

Size large large large large large large medium medium medium medium medium medium small small small small small small bat bat bat bat bat bat

Placed 5 3 2 4 2 4 7 9 10 2 2 6 8 5 3 6 8 9 2 6 5 9 6 3

Found 3 2 1 4 2 4 2 4 5 2 2 5 3 2 0 1 3 5 1 1 2 5 3 2

Table A2. Number of carcasses found by bird and bat species at three wind farms in the Isthmus of Tehuantepec, southern Mexico. Seasonality (birds) represented by R or M (Resident or Migratory); all bat species are resident. Birds Family / Species Anatidae Dendrocygna autumnalis Ardeidae Bubulcus ibis Butorides virescens Caprimulgidae Nyctidromus albicollis Cardinalidae Spiza americana Cathartidae Cathartes aura Columbidae Columbina inca Columbina passerina Columbina sp (morphospecies 1) Columbina talpacoti Leptotila verreauxi Zenaida asiatica Cracidae Ortalis poliocephala Cuculidae Coccyzus minor Crotophaga sulcirostris Geococcyx velox Emberizidae Peucaea sp (morphospecies 2) Hirundinidae Hirundo rustica Icteridae Icterus sp (morphospecies 3) Molothrus sp (morphospecies 4) Quiscalus mexicanus Odontophoridae Colinus virginianus Parulidae Cardellina pusilla

Wind farms Seasonality Western Eastern Northern Total R

1

1

R R

1 1

1 1

R

1

1

M

1

1

M

2

2

R R Ra R R M

2

3 1

R R R

M

11 3 1 1 7 1

1

1

1

2 4 1

1

R

Ra

6 2 1 1 7

1 4

1 1

1 1

1

ND b Ra R

1 4

3

1 1 7

R

4

3

7

M

1

1

2

1

Mniotilta varia Trochilidae Archilochus colubris Turdidae Turdus grayi Tyrannidae Empidonax sp (morphospecies 5) Myiozetetes similis Tyrannus forficatus Tyrannus sp (morphospecies 6) Tyrannus tyrannus Vireonidae Vireo flavoviridis Vireo sp (morphospecies 7) No ID Feathers Total

M

1

1

M

1

1

R

1

1

1

1

1 2 2 1 1

M Ma

3 1

3 1

ND NA

2 34

2 75

ND b R M ND M

1

2 1 1

4

37

a

We were able to assign seasonality to this morphospecies because we only have either resident or migratory species of this genus in the region. b

On the contrary, we were not able to assign seasonality to this morphospecies because we only have both resident and migratory species of this genus.

Table A2. Contd. Bats Family / Species Emballonuridae Balantiopteryx plicata Molossidae Eumops auripendulus Eumops underwoodi Molossus molossus Molossus rufus Nyctinomops laticaudatus Promops centralis Mormoopidae Mormoops megalophylla Pteronotus davyi Pteronotus parnellii No ID 1 Phyllostomidae Artibeus jamaicensis Artibeus lituratus Centurio senex Dermanura sp (morphospecies 1) Glossophaga commissarisi Glossophaga morenoi Glossophaga soricina Glossophaga sp (morphospecies 2) Vespertilionidae Lasiurus blossevillii Dasypterus intermedius Myotis sp (morphospecies 3) No ID 2 Total bats

Wind farms Eastern Northern Total

1 2 1 1 1

1 4 2 1 1 1 2 1 1

2

2

1

1 1 5 3 2 1

3 2 1

4 10 3 1

4 10 3 2

2

4 2 6 1 1 3 1 3

1 2

2 6 2 4

3 8 2 4

23

49

72

5

1

Figure A1. Service areas, pads, and road.

Figure A2. Service area (brown rectangles) and service road (brown stripe) around wind turbines (black dots) overlapped on radial bands 10-m wide radiating from the turbines, showing the proportion of each band, as percentage, that was searched for carcasses at each wind farm (i.e. the percentage area of each 10-m ring that intersects the search areas). We used this to estimate the proportion of killed animals that fell in the search areas (parameter a), see Methods.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: