• Energy Research

The current development of renewable energy infrastructure (EI) can lead to an irreversible loss of biodiversity, but negative impacts can be minimised through effective planning. As a case study, we identify the essential areas for the conservation of a globally threatened bird, the great bustard (Otis tarda). We used 21,296 observations and the Kernel method to calculate the home-range area of the world's largest population of this species. The home-range area (11,142 km2) is highly fragmented in small habitat patches (n = 240 areas, mean = 46.42 km2). A large fraction (55.8 %) of this area is outside Special Protection Areas, thus being highly vulnerable to new EI developments. We identified 842.241 km of transport power lines (>50 kV) that intersect with great bustard home-ranges, and therefore may cause collision fatalities of up to 2.46 individuals per km and year. Undergrounding these lines, as well as any other planned lines, is a priority to reduce bird mortality. If EI projects are not well planned, a significant loss of agro-steppe habitat can occur (32.2 % in our control area). We strongly suggest that planning of new EI should take into account the home-range area and flight movements of agro-steppe threatened birds, both inside and outside SPAs. In general, EI projects are assessed on a case-by-case basis, without considering the synergistic effects of all projects that can affect protected species in a region. This work illustrates how large-scale mapping of endangered species is essential for an effective planning of EI. The study was funded by projects PB97-1252, BOS2002-01543, CGL2005-04893/BOS, CGL2008-02567, and CGL2012- 36345 of the Spanish Ministry for Science and Innovation. Peer reviewed

6 páginas, 1 figura y 2 tables A study was conducted to evaluate the effectiveness of groundwire marking in reducing bird mortality through collision at a power transmission line in southwestern Spain. Monthly flight intensity observations and weekly searches for dead birds were carried out at four sectors of the line comprising 28·2 km, during two consecutive winters, 1989–1990 and 1990–1991, respectively before and after groundwire marking with coloured PVC spirals. Flight intensity and collision frequency decreased respectively by 61% and 60% at marked spans compared to the same spans prior to marking, while there was no significant change in collision frequency at spans left unmarked. After marking, the percentage of birds flying between the cables decreased and that flying above them increased. Our results suggest that many birds avoided flying across the marked spans of the line or climbed while approaching them, and therefore collided less frequently. The percentage decrease in mortality observed in our study falls within the range of results of other groundwire marking or removal studies The study was financed by Red Electrica de España, SA. Peer reviewed

# databases used for statistical analyses in manuscript WLB-2024-01345 [https://doi.org/10.5061/dryad.tht76hf7v](https://doi.org/10.5061/dryad.tht76hf7v) ## Description of the data and file structure **List of excel files used for GLMMs and other analyses in manuscript WLB-2024-01345.R1 – “Precipitation and female experience are major determinants of the breeding performance of Canarian houbara bustards”** ### Files and variables #### File: GLM2b2NestInitiatDate.xlsx **Description:** ** database for GLMM Nest Initiation Date (NIDF, see Supplementary Table S3)** ##### Variables * definitions as in other excel files #### File: GLM4aNestAttemptSuccess.xlsx **Description:** **database for GLMM Nest Attempt Success (see Supplementary Table S3)** ##### Variables * clutchOrder: order of the clutch (1 first, 2 second –replacement-, 3 third –replacement-clutch), chicksSurvived: chicks survived until productivity control (1= yes/0= no, see Methods), MeanTemp: during 23 days incubation + 2 months in nestings that have chicks on the control date, AvMaxTemp: average maximum temperature during 23 days incubation + 2 months in nestings that have chicks on the control date, AvMinTemp: average minimum temperature during 23 days incubation + 2 months in nestings that have chicks on the control date, pp: precipitation during 23 days incubation + 2 months in nestings that have chicks on the control date, other variables as defined in other excel files #### File: GLM4bFledSuccess.xlsx **Description:** **database for GLMM Fledging Success (see Supplementary Table S3)** ##### Variables * Variables:** **pp: precipitation during** **23 days since nesting start + 2 months in nestings that have chicks on the control date; 23+1 month, in nestings that do not have chicks on the control date, other variables as defined in other excel files #### File: GLM5ReClutchProb.xlsx **Description:** **database for GLMM Re-clutching Probability (see Supplementary Table S3)** ##### Variables * Variables: Reclutch: 1= has a replacement clutch/0= does not have a replacement clutch, DurationIncubation: duration of the incubation period (days), MeanTemp, AvMaxTemp, AvMinTemp, pp: measured over the incubation period, other variables as defined in other excel files #### File: Weighted\_precipitations.xlsx **Description:** **databases to calculate weighted precipitation amounts, periods of precipitation and nestings (see Methods for details)** ##### Variables * definitions as in other excel files #### File: GLM6a3FemaleProductivity.xlsx **Description:** **database for GLMM Productivity (see Supplementary Table S3)** ##### Variables * nClutches: number of clutches (1,2,3), NchicksSurvived (1,2 up to fledging), pp2: precipitation measured from one month before the first laying to the laying date of the last clutch, other variables as defined in other excel files #### File: GLM6bFemaleProductivity.xlsx **Description:** **database for GLMM Productivity (as GLM6a, but measuring precipitation over the same period for all years: from 1 September to 13 March [mean hatching start date of the latest year, which was 2022]; see Supplementary Table S3)** ##### Variables * as in GLM6a3FemaleProductivity.xlsx, but measuring precipitation over the same period for all years: from 1 September to 13 March [mean hatching start date of the latest year, which was 2022; other variables as defined in other excel files #### File: GLM7aLengthBreedSeason.xlsx **Description:** **database for GLMM Length of the Breeding Season (see Supplementary Table S3)** ##### Variables * daysBreeding: duration of the breeding season in days (see definition in Methods), temperature and precipitation (PP) measured from 1 month before the first day of incubation of that year in any female until the date of independence of the last chick (see Azar et al 2018: Total rainfall during the nesting period (the period between the first and last nest found each year). other variables as defined in other excel files #### File: GLM7bLengthBreedSeason.xlsx **Description:** **database for GLMM Length of the Breeding Season, same as GLM7aLengthBreedSeason.xlsx, but precipitation and temperature measured over an equal period for all years: from 1 September to 13 March (= average hatching starting date of the latest year, 2022) (see Supplementary Table S3)** ##### Variables * as in GLM7aLengthBreedSeason.xlsx, but precipitation and temperature measured over an equal period for all years: from 1 September to 13 March #### File: WeightedPrecipitationPeriods.xlsx **Description:** **database to calculate weighted precipitation periods and nestings (see Methods for details)** ##### Variables * as in other excel files #### File: GLM2cNestInitiatDate.xlsx **Description:** **database for GLMM Nest Initiation Date of First Clutches (NIDF2, see Supplementary Table S3)** ##### Variables * definitions as in other excel files #### File: GLM1bNestingRate.xlsx **Description:** **database for GLMM Nesting Rate (see Supplementary Table S3)** ##### Variables * indiv= individual female, year, femaleNests: 1=Yes/0=No, startNest = date when nesting started, pp30days: precipitation on the 30 days before (in mm), pp60ays: precipitation on the 60 days before (in mm), pp90days: precipitation on the 90 days before (in mm), TempMean30days: mean temperature on the 30 days before (in oC), TempMax30days: maximum temperature on the 30 days before (in oC), TempMin30days: minimum temperature on the 30 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), TempMax60days: maximum temperature on the 60 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), Weight: weight of the female (g), PC1p: Principal Component 1 of the PCA including weight, PC1sinP: Principal Component 1 of the PCA excluding weight, Breedingexperience: breeding experience of the female, as defined in Methods. #### File: GLM1cNestingRate2.xlsx **Description:** ##### Variables * indiv= individual female, year, femaleNests: 1=Yes/0=No, startNest = date when nesting started, pp30days: precipitation on the 30 days before (in mm), pp60ays: precipitation on the 60 days before (in mm), pp90days: precipitation on the 90 days before (in mm), TempMean30days: mean temperature on the 30 days before (in oC), TempMax30days: maximum temperature on the 30 days before (in oC), TempMin30days: minimum temperature on the 30 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), TempMax60days: maximum temperature on the 60 days before (in oC), TempMean60days: mean temperature on the 60 days before (in oC), Weight: weight of the female (g), PC1p: Principal Component 1 of the PCA including weight, PC1sinP: Principal Component 1 of the PCA excluding weight, Breedingexperience: breeding experience of the female, as defined in Methods, pp_1sep_13mar: precipitation measured between 1st September and 13th March, T_1sep_13mar: temperature measured between 1st September and 13th March #### File: GLM2a2NestInitiatDate.xlsx **Description:** **database for GLMM Nest Initiation Date (NIDF, see Supplementary Table S3)** ##### Variables * ordinalDate: Ordinal date as defined in Methods, rest of variables: definitions as in other excel files #### File: GLM3HatchSuccess.xlsx **Description:** **database for GLMM Hatching Success (see Supplementary Table S3)** ##### Variables * : endNest: date when incubation finished, ppIncub: precipitation during incubation (23 days since start incubation), AvMaxTempIncub: average maximum temperature during incubation, AvMaxTempIncub: average maximum temperature during incubation, ppIncub: mean temperature during incubation, hatchSuccess: 1= incubation until hatching date is successful/ 0= incubation until hatching date is not successful, rest of variables: definitions as in other excel files ## Code/software data can be viewed using EXCEL; other files from the process of statistical analysis were obtained using package “lme4” (Bates et al. 2015) in R v.2.15.1 (R Development Core Team, 2015) Precipitation is one of the main triggers of reproduction in desert-breeding birds. The unpredictability of rainfall patterns in arid environments has led species to adapt their breeding effort to episodes of abundant food after rainfall. The response is not the same for all individuals in a population, and may vary especially with the age and experience of each female. Here we investigate the effects of precipitation, temperature, body size and breeding experience, among other variables, on reproductive parameters of 20 females of Canarian houbara bustard (Chlamydotis undulata fuertaventurae), an endangered desert bird endemic of the eastern Canary Islands. Precipitation and breeding experience were the main determinants of female breeding performance. Higher rainfall determined an increase in nesting rate, and earlier autumn rains caused an advancement of nesting to October, allowing the breeding season to be extended to eight months. This favoured an extraordinary increase in productivity in more rainy breeding seasons, with 15 times more females nesting in the two most rainy winters than in dry years. In addition, females with more breeding experience showed a higher tendency to breed, higher nest attempt and fledging success, and longer breeding season, which allowed them to rear more chicks. A female even double brooded successfully in the same season, which, considering that chicks remain with the mother for up to six months, indicates a great capacity to optimise reproductive investment, by adapting to highly variable rainfall regimes. In recent decades, the eastern Canary Islands have undergone a process of aridification, and climate models predict a medium-term increase in the frequency and duration of drought periods. Thus, Canarian houbaras are particularly vulnerable to climate change, so measures are urgently needed to reduce their mortality and improve the quality of their habitat, in order to favour their reproduction and prevent their extinction.  We used 5-year breeding phenology and breeding success data from 20 female houbara bustards captured in Lanzarote and equipped with backpack-mounted GSM/GPRS data loggers. The influence of predictor variables on breeding parameters was modeled by means of generalized linear mixed models (GLMMs) using package “lme4” (Bates et al. 2015) in R v.2.15.1 (R Development Core Team, 2015).