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Relationships between survival and habitat suitability of semi-aquatic mammals

Citation

Wang, Guiming et al. (2021), Relationships between survival and habitat suitability of semi-aquatic mammals, Dryad, Dataset, https://doi.org/10.5061/dryad.t4b8gthzd

Abstract

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche-based species distribution models and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi-aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30-m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent-predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability-fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic species distribution models incorporating local abundance and demographic rates are needed.

Methods

Radio telemetry data collection

We captured American beaver using Hancock live traps (Hancock Trap Company, Custer, SD, USA) within Redstone from January to May 2011. We fit a 38-g (<0.05% of body mass) very high frequency (VHF) transmitter (Model 3530, Advanced Telemetry Systems, Isanti, MN, USA) to each captured subadult (10.9–16.0 kg) and adult (>16 kg) using tail-mounting methods; juveniles were excluded (Arjo et al. 2008, McClintic et al. 2014a). Smith et al. (2016) demonstrated that tail-mounting did not affect beaver survival in Minnesota. Capture and handling of beavers was approved by the Institutional Animal Care and Use Committee of the United States Department of Agriculture, National Wildlife Research Center (Protocol No. QA-1626). For survival analysis, we located radio-tagged beaver once every four weeks (i.e., tracking occasions) to determine the fates (i.e., live, dead, undetected, or missing) of radio-tracked individuals from January 2011 to April 2012. We determined additional information on the fates of tracked beaver from other relocations collected via triangulation between tracking occasions (for home range estimation in a different study) and used those live resighting or dead recovery data for the Barker survival model. We located dead beaver as practically possible by triangulation on the VHF mortality signal. 

Encounter history input for program MARK

For the encounter history input, we used monthly live detections (completed during the first week of a monthly interval) of radio-tagged individuals via VHF telemetry as a live encounter occasion. Live detections occurring anytime between the two successive live encounter occasions within a month were treated as live resightings

Environmental covriates

The normalized difference vegetation index (NDVI)

We derived two monthly NDVI time series from 250-m resolution, 16-day MODIS, multi-spectral satellite imagery using R package MODIStsp. The NDVI time series included: (1) NDVI for Redstone’s entire American beaver population for each monthly tracking interval (popndvi); and (2) wetland- or colony-specific NDVI for each monthly tracking interval (colndvi). We delineated the spatial extent of beaver colonies using a minimum convex polygon from all VHF locations of all radio-tagged beaver inhabiting a wetland. We averaged NDVI values over all cells or pixels within a colony to estimate colony-specific NDVI using R packages raster and sp. If a radio-tracked individual did not occupy a known colony, we extracted NDVI values by using a circular buffer representing the average spatial extent of beaver colonies. The circular buffer was centered at the centroid of the VHF locations of the individual. Variable popndvi was calculated as the average of all colndvi values by month. 

Lanscape variables

To evaluate landscape-beaver survival relationships, we included landscape variables: woody wetland edge density (m ha-1, wwetbd), shrub edge density (shrubbd), water body edge density (waterbd), and relative frequency (0-1.0) of grassland (grassfq) out of 30 landscape variables. We derived raster layers for these four landscape variables from 2011 National Land Cover Database (NLCD) using the program Biomapper. We calculated averages of the four landscape variables for each colony using the same geospatial analysis as we did for NDVI.

Usage Notes

The data input file includes the inline note for explanations by column, serving as metadata.  There are no missing values in the input data.