Conservation implications of sex‐specific landscape suitability for a large generalist carnivore

Abstract

Aim: Terrestrial mammal distribution models typically do not differentiate between sexes when making spatial predictions, which could have important conservation implications. As male carnivores are usually more risk tolerant and travel longer distances, male potential range should be larger and include more human-modified areas than female range. To evaluate if differences between females and males could influence their conservation planning, we quantified sex-specific suitable range for a recolonizing population of American black bears (Ursus americanus). Location:We applied this method in Missouri, USA. Methods:We collected telemetry data from 57 females and 43 male bears from 2010 to 2018. We used three machine-learning methods (generalized boosted regression, random forest and maximum entropy) to develop sex-specific distribution models, which were combined into a weighted average ensemble model and converted into a binary (presence/absence) model using an optimized threshold. We used 80% of individuals for each sex as training data, and 20% as evaluation data. Results:All models had high predictive performance; the greatest uncertainty in model predictions corresponded with the periphery of the distributions, whereas there was high agreement in the core distribution. Male suitable range was 66% larger than female range, and males were predicted to occur in more human-modified areas and more likely to be present in developed land and agriculture.Main conclusions: Distribution models based on data from both sexes, or that is male-biased, could overestimate the female (i.e., reproductive) range and potentially misrepresent the biologically relevant species distribution. This bias can potentially lead to misguided decisions and suboptimal use of resources. By improving models when sex-specific data are available, we can better focus resources in areas where there is reproductive potential, leading to more accurate assessments of species' conservation status and better identifying areas vital for species persistence. K E Y W O R D Scarnivore, habitat suitability, mammal, range, sex-specific, spatial ecology, species distribution model, ursid | 1489 GANTCHOFF eT Al.

Improved prediction of Canada lynx distribution through regional model transferability and data efficiency

“…These models can provide both an understanding of the specific environmental components that might define a species' habitat as well as generate spatial predictions of distribution at a landscape scale (Elith & Leathwick, 2009). Species distribution models have been used extensively to create maps of predicted habitat (Derville et al, 2018; Gantchoff et al, 2019), evaluate threats from climate change or increased anthropogenic disturbance (Diniz‐Filho et al, 2009; Requena‐Mullor et al, 2019), or consider habitat corridors and connectivity (Zeller et al, 2018). Accurate SDMs are particularly important for landscape‐scale conservation planning given the large‐scale changes associated with climate (Park Williams et al, 2013), anthropogenic alterations (Curtis et al, 2018), habitat loss and fragmentation (Sala et al, 2000), wildfire (Hansen et al, 2010), and insect outbreaks (Kurz et al, 2008).…”

“…While the impact of sample size on SDMs has been extensively considered, the general concern has been with too little data, rather than too much (Hernandez et al, 2006; Stockwell & Peterson, 2002). However, the recent availability of extensive Global Positioning System (GPS) datasets presents a novel challenge to conventional SDMs as there is little consensus regarding how to treat the large volume of animal relocations (Gantchoff et al, 2019; Li et al, 2017; Magg et al, 2016; Maiorano et al, 2015; Rice et al, 2013; Shoemaker et al, 2018) which may create redundant or spatially correlated nonindependent information with respect to species distributions, particularly if few animals are sampled. Yet, GPS data provide high spatial accuracy, reduced sampling bias, and less species misidentification; all these issues plague the opportunistic sampling schemes common in SDM literature (Aubry et al, 2017; Newbold, 2010).…”

Using habitat suitability and landscape connectivity in the spatial prioritization of public outreach and management during carnivore recolonization

“…We used GPS telemetry data (2011–2018) from 97 individual bears which were located in and around the Ozarks highlands (~41,078 km 2 of south‐central Missouri), and collected as part of the Missouri Black Bear Project (see Gantchoff et al., 2019 for capture and collaring methods). All capturing and handling of bears followed the American Society of Mammalogists guidelines (Sikes et al., 2016) and was approved by the Mississippi State University (protocols 13‐094 and 17‐431) and the State University of New York (protocol 180504) Institutional Animal Care and Use Committees.…”

Understanding Species–Habitat Associations: A Case Study with the World’s Bears

“…Ditmer et al observed bears at the edge of their range within a sparsely-forested area of Minnesota (considered atypical bear habitat) and used short time windows of habitat use by collared bears to try to predict the minimum amount of forest that they could tolerate; they used this to gauge how far west across a gradient of decreasing forest the population could expand [205]. Gantchoff et al argued that habitat models could over-estimate the potential range if the sexes are pooled, because females in their expanding population in Missouri were observed to be more constrained to less human-developed areas than males [221]. However, their frame of reference for what females could tolerate was based on where females lived currently.…”