Maxent suitability outputs

Maps of habitat suitability produced by MaxEnt for each species; coordinate system: RGF9

Environmental variables

Raster files of environmental variables used for MaxEnt models and measures of ecological overlap: temperature, precipitation, percentage of meadow, density of hedgerows, TWI, winter NDVI, spring EVI; coordinate system: RGF9

Species occurrences

Species occurrences coordinates; coordinate system: RGF9

Capture-recapture data

Capture-recapture dat

Appendix A. A table showing all the tested models, detailing their structure and their comparison using AIC values.

A table showing all the tested models, detailing their structure and their comparison using AIC values

Retrofitting of power lines effectively reduces mortality by electrocution in large birds: an example with the endangered Bonelli’s eagle

<p>Capture-mark-recapture dataset of the french Bonelli's eagle population.</p

Capture-recapture data

Data description The capture-recapture data used in Cayuela et al. (2018, J. Appl. Ecol) were collected in a spatially structured population of Bombina variegata in France, over an 9-years period (2000-2008). Several capture sessions were performed per year (detailed in Supplementary material S1 of the paper). The individuals are in raws and the capture occasion on column (labelled “H:”). The column “S:” specifies the end of the capture history. The column labeled “$COV:sex” is the sex coded as a group effect (1 = male, 2 = female). The capture-recapture histories are coded with the following events. For an individual captured at t and t–1, we attributed a code of 1 if it had not dispersed and occupied a patch destroyed at t+1 or a code of 4 if the patch was still available; we attributed a code of 2 if an individual had dispersed and occupied a patch destroyed at t+1 or a code of 5 if the patch was still available. For an individual not captured at t–1 but captured at t, a code of 3 or 6 was attributed respectively if it occurred in a patch destroyed at t+1 or not. An individual was coded 0 if it was not captured at t. The txt file is compatible with E-SURGE program. Code to enter in the GEMACO in E-SURGE program to run the most general model. For Initial State: IS - Step 1 - (1): to For Transition: Survival - Step 1 - (5): from(1:6, 7:12).t(6 10 14 19 20 23 26).g+[t(6 10 14 19 20 23 26)+t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28)] For Transition: Dispersal - Step 2 - (5): from(1:3, 4:6).t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28, 6 10 14 19 20 23 26)+g For Transition: Site dynamics - Step 3 - (8): t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28, 6, 10, 14, 19, 20, 23, 26) For Transition: Recapture - Step 4 - (11): from(1:6, 7:12)+t(1 2 3 4 5 6, 7 8 9 10, 11 12 13 14, 15 16 17 18, 19, 20, 21 22 23, 24 25 26, 27 28 29)+g For Event: Events - Step 1 - (0): firste+next

Birth timing data of wild boar

Birth timing data of wild boa

Ecological Effects of the Invasive Giant Madagascar Day Gecko on Endemic Mauritian Geckos: Applications of Binomial-Mixture and Species Distribution Models

<div><p>The invasion of the giant Madagascar day gecko <i>Phelsuma grandis</i> has increased the threats to the four endemic Mauritian day geckos (<i>Phelsuma</i> spp.) that have survived on mainland Mauritius. We had two main aims: (i) to predict the spatial distribution and overlap of <i>P. grandis</i> and the endemic geckos at a landscape level; and (ii) to investigate the effects of <i>P. grandis</i> on the abundance and risks of extinction of the endemic geckos at a local scale. An ensemble forecasting approach was used to predict the spatial distribution and overlap of <i>P. grandis</i> and the endemic geckos. We used hierarchical binomial mixture models and repeated visual estimate surveys to calculate the abundance of the endemic geckos in sites with and without <i>P. grandis</i>. The predicted range of each species varied from 85 km² to 376 km². Sixty percent of the predicted range of <i>P. grandis</i> overlapped with the combined predicted ranges of the four endemic geckos; 15% of the combined predicted ranges of the four endemic geckos overlapped with <i>P. grandis</i>. Levin's niche breadth varied from 0.140 to 0.652 between <i>P. grandis</i> and the four endemic geckos. The abundance of endemic geckos was 89% lower in sites with <i>P. grandis</i> compared to sites without <i>P. grandis</i>, and the endemic geckos had been extirpated at four of ten sites we surveyed with <i>P. grandis</i>. Species Distribution Modelling, together with the breadth metrics, predicted that <i>P. grandis</i> can partly share the equivalent niche with endemic species and survive in a range of environmental conditions. We provide strong evidence that smaller endemic geckos are unlikely to survive in sympatry with <i>P. grandis</i>. This is a cause of concern in both Mauritius and other countries with endemic species of <i>Phelsuma</i>.</p></div

Model selection results. Abundance was modelled with habitat and status as site-level covariates.

<p>K = number of parameters used.</p><p>Delta AICc = difference between lowest AICc model and model AICc.</p><p>AICc weight = model probability among all candidate models.</p><p>Detection probability was modelled with observation-level covariates: cloud = cloud percentage cover; habitat = building, non-palm or palm; status = presence or absence of <i>P. grandis</i>; and temp = temperature. We used the corrected Akaike Information Criterion (AICc) to determine the best supported model.</p