Population characteristics, space use and habitat selection of two non-migratory caribou herds in central Alaska, 1994 - 2009

Horne, Jon S.; Craig, Tim; Joly, Kyle; Stout, Glenn W.; Cebrian, Merben R.; Garton, Edward O.

doi:10.7557/2.34.1.2572

Cited by 4 publications

(5 citation statements)

References 33 publications

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“…Alaska includes over 30 herds of caribou distributed throughout the state, although many of these are smaller herds that undertake only local migrations or none at all [29]. Four large migratory herds range across the Brooks Range in northern Alaska.…”

Section: Introductionmentioning

confidence: 99%

Using seasonal landscape models to predict space use and migratory patterns of an arctic ungulate

Baltensperger

Joly

2019

Mov Ecol

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Background Caribou in the Western Arctic Herd undertake one of the longest, remaining intact migrations of terrestrial mammals in the world. They are also the most important subsistence resource for many northern rural residents, who rely on the caribou’s migratory movements to bring them near for harvest. Migratory geography has never been static, but subsistence harvesters have reported recent shifts in migration away from areas where they traditionally occurred. The reasons behind these changes are not well-understood, but may be related to rapid climate change and anthropogenic disturbances. Methods To predict changes in distribution and shifting migratory areas over the past decade, we used GPS telemetry data from adult females to develop predictive ecological niche models of caribou across northwestern Alaska. We employed the machine-learning algorithm, TreeNet, to analyze interactive, multivariate relationships between telemetry locations and 37 spatial environmental layers and to predict the distributions of caribou during spring, calving season, insect-harassment season, late summer, fall, and winter from 2009 to 2017. Model results were analyzed to identify regions of repeated predicted use, quantify mean longitude, predict land cover selection, and track migratory changes over time. Results Distribution models accurately predicted caribou at a spatially-explicit, 500-m scale. Model analyses identified migratory areas that shifted annually across the region, but which predicted 4 main areas of repeated use. Niche models were defined largely by non-linear relationships with coastally-influenced, climatic variables, especially snow-free date, potential evapo-transpiration, growing season length, proximity to sea ice, winter precipitation and fall temperature. Proximity to roads and communities were also important and we predicted caribou to generally occur more than 20–100 km from these features. Conclusions Western Arctic Herd caribou were predicted to occur in warmer, snow-free and treeless areas that may provide conditions conducive for efficient travel and foraging. Rapidly changing seasonal climates and coastal influences that determine forage availability, and human impediments that slow or divert movements are related to geographically and phenologically dynamic migration patterns that may periodically shift caribou away from traditional harvest areas. An enhanced understanding of the geographic behavior of caribou over time could inform traditional harvests and help conserve important Western Arctic caribou migratory areas. Electronic supplementary material The online version of this article (10.1186/s40462-019-0162-8) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Using seasonal landscape models to predict space use and migratory patterns of an arctic ungulate

Baltensperger

Joly

2019

Mov Ecol

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“…Harzel et al (2006) suggested that displaying RSF results as a continuous surface can be misleading and RSF values should be reclassified, or binned, for map creation to provide honest and relevant predications. However, there has been minimal discussion on the most appropriate binning methods, and displaying RSF values as a continuous surface remains common (Brook & McLachlan, 2009; Dellinger, Proctor, Steury, Kelly, & Vaughan, 2013; Dugal et al, 2013; Fortin et al, 2008; Horne et al, 2014; Teichman, Cristescu, & Nielsen, 2013). …”

Section: Introductionmentioning

confidence: 99%

Mapping resource selection functions in wildlife studies: Concerns and recommendations

2016

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Predicting the spatial distribution of animals is an important and widely used tool with applications in wildlife management, conservation, and population health. Wildlife telemetry technology coupled with the availability of spatial data and GIS software have facilitated advancements in species distribution modeling. There are also challenges related to these advancements including the accurate and appropriate implementation of species distribution modeling methodology. Resource Selection Function (RSF) modeling is a commonly used approach for understanding species distributions and habitat usage, and mapping the RSF results can enhance study findings and make them more accessible to researchers and wildlife managers. Currently, there is no consensus in the literature on the most appropriate method for mapping RSF results, methods are frequently not described, and mapping approaches are not always related to accuracy metrics. We conducted a systematic review of the RSF literature to summarize the methods used to map RSF outputs, discuss the relationship between mapping approaches and accuracy metrics, performed a case study on the implications of employing different mapping methods, and provide recommendations as to appropriate mapping techniques for RSF studies. We found extensive variability in methodology for mapping RSF results. Our case study revealed that the most commonly used approaches for mapping RSF results led to notable differences in the visual interpretation of RSF results, and there is a concerning disconnect between accuracy metrics and mapping methods. We make 5 recommendations for researchers mapping the results of RSF studies, which are focused on carefully selecting and describing the method used to map RSF studies, and relating mapping approaches to accuracy metrics.

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“…We tested for overall differences in individual selection coefficients between males and females with multivariate analysis of variance (MANOVA) using the PillaiBartlett statistic (Horne et al, 2014). If there were no significant differences (P<0.05) in selection coefficients between sexes, we averaged the selection coefficients across individuals to generate population-level estimates.…”

Section: Modelling Home Range and Habitat Selection Simultaneouslymentioning

confidence: 99%

“…The synoptic model structure is based on a weighted distribution used to predict a species' probability of use of a given area based on an individual's space use (i.e., home range) and the habitat features that influence their space use (Horne et al, 2014).…”

Section: Modelling Home Range and Habitat Selection Simultaneouslymentioning

confidence: 99%

Spatial ecology of the water opossum Chironectes minimus in Atlantic Forest streams

et al. 2016

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Spatial ecology of the water opossum Chironectes minimus in Atlantic Forest streams.Mammalian Biology http://dx. ABSTRACTThe water opossum Chironectes minimus is the world's only semi-aquatic marsupial. It is considered rare, and it is reported on several regional conservation lists of species as either endangered or data deficient. Given its uniqueness and the poor knowledge of its ecology, we aimed to investigate home range size and overlap and habitat selection of the water opossum in Atlantic Forest streams in southeastern Brazil.We radio tracked water opossums and collected information about their habitats and behaviour from October 2004 to April 2010. We combined common home range estimators for animals living in linear habitats with the synoptic model of home range and habitat selection. For the 10 individuals monitored, the home ranges varied between 0.80 and 9.66 km of watercourses; none of them had exclusive home ranges. The home range size for males was, on average, three times larger than for females. The overlap data showed that, on average, one male could encompass the home ranges of up to five females simultaneously, but more than one male could have access to the same female.For habitat selection at the individual level, we could not find any strong influence of habitat features on water opossum preferences because individuals selected different sets of habitat variables. However, at the population level, we found a negative relationship between home range size and river size. The water opossum seems to prefer shallow and narrow watercourses to establish its home ranges. Here, we present valuable information to advance our knowledge of the water opossum and its ecology, which is urgent for conservation purposes.

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Population characteristics, space use and habitat selection of two non-migratory caribou herds in central Alaska, 1994 - 2009

Cited by 4 publications

References 33 publications

Using seasonal landscape models to predict space use and migratory patterns of an arctic ungulate

Using seasonal landscape models to predict space use and migratory patterns of an arctic ungulate

Mapping resource selection functions in wildlife studies: Concerns and recommendations

Spatial ecology of the water opossum Chironectes minimus in Atlantic Forest streams

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