Code accompanying - Variation in spatiotemporal activity may reduce competitive interactions between invasive wild pigs (Sus scrofa) and native mammal species

<p>This repository contains the code accompanying the paper “Variation in spatiotemporal activity may reduce competitive interactions between invasive wild pigs (Sus scrofa) and native mammal species”.</p&gt

Seasonal habitat-based density models for a marine top predator, the harbor porpoise, in a dynamic environment

Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species-habitat relationships can improve the assessment of trends and distribution by explicitly allowing high-resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat-based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005-2013) by means of dedicated line-transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on-effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for "season," allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large-scale international SCANS II survey with the more frequent, small-scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are especially relevant for marine spatial planning, which requires accurate fine-scale maps of species distribution to assess risks of increasing human activities at sea.</p

Age and seasonal variation in testis and baculum morphology in East Greenland polar bears (Ursus maritimus) in relation to high concentrations of persistent organic pollutants

Persistent organic pollutants (POPs) are found in high concentrations in the Artic. Polar bears (Ursus maritimus) are one of the most exposed mammals in the Arctic and are thereby vulnerable to reproductive disruption. Th

Solving the sample size problem for resource selection functions

Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals urn:x-wiley:2041210X:media:mee313701:mee313701-math-0001 and as many relocations per animal N as possible. These thresholds render many RSF-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than urn:x-wiley:2041210X:media:mee313701:mee313701-math-0002 animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies

Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data

In our paper "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data" (Global Ecology and Biogeography) we use GPS tracking data from 1,498 from 49 different species to evaluate the expert-based habitat suitability data from the International Union for Conservation of Nature (IUCN). Therefore, we used the GPS tracking data to estimate two measures of habitat suitability for each individual animal and habitat type: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN’s classification into suitable, marginal and unsuitable habitat types. Our results showed that IUCN habitat suitability data were in accordance with the GPS data (>95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a >50% probability of agreement based on proportional habitat use and selection ratios, respectively. These findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, our study shows that GPS tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. In this dataset we provide the measures of habitat suitability for each individual and each habitat type, calculated using different methods. In addition, we provide data on the body mass and IUCN Red List category of the species, as well as whether the species can be considered a habitat specialist or habitat generalist

Data of "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data"

In our paper "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data" (Global Ecology and Biogeography) we use GPS tracking data from 1,498 from 49 different species to evaluate the expert-based habitat suitability data from the International Union for Conservation of Nature (IUCN). Therefore, we used the GPS tracking data to estimate two measures of habitat suitability for each individual animal and habitat type: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN’s classification into suitable, marginal and unsuitable habitat types. Our results showed that IUCN habitat suitability data were in accordance with the GPS data (>95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a >50% probability of agreement based on proportional habitat use and selection ratios, respectively. These findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, our study shows that GPS tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. In this dataset we provide the measures of habitat suitability for each individual and each habitat type, calculated using different methods. In addition, we provide data on the body mass and IUCN Red List category of the species, as well as whether the species can be considered a habitat specialist or habitat generalist

bi4africa dataset - open source

The bii4africa dataset is presented in a multi-spreadsheet .ods file. The raw data spreadsheet (‘Scores_Raw’) includes 31,313 individual expert estimates of the impact of a sub-Saharan African land use on a species response group of terrestrial vertebrates or vascular plants. Estimates are reported as intactness scores - the remaining proportion of an ‘intact’ reference (pre-industrial or contemporary wilderness area) population of a species response group in a land use, on a scale from 0 (no individuals remain) through 0.5 (half the individuals remain), to 1 (same as the reference population) and, in limited cases, to 2 (two or more times the reference population). For species that thrive in human-modified landscapes, scores could be greater than 1 but not exceeding 2 to avoid extremely large scores biasing aggregation exercises. Expert comments are included alongside respective estimates

bii4africa dataset

The bii4africa dataset is presented in a multi-spreadsheet .xlsx file. The raw data spreadsheet (‘Scores_Raw’) includes 31,313 individual expert estimates of the impact of a sub-Saharan African land use on a species response group of terrestrial vertebrates or vascular plants. Estimates are reported as intactness scores - the remaining proportion of an ‘intact’ reference (pre-industrial or contemporary wilderness area) population of a species response group in a land use, on a scale from 0 (no individuals remain) through 0.5 (half the individuals remain), to 1 (same as the reference population) and, in limited cases, to 2 (two or more times the reference population). For species that thrive in human-modified landscapes, scores could be greater than 1 but not exceeding 2 to avoid extremely large scores biasing aggregation exercises. Expert comments are included alongside respective estimates