Current land use is a poor predictor of hellbender occurrence: why assumptions matter when predicting distributions of data‐deficient species

Abstract

Aim Understanding species distributions is fundamental to effective conservation planning. Data deficiency is common among rare and imperiled species and poses challenges for conservation planning because status assessments become reliant on scant data that can introduce bias. We used occupancy modelling to evaluate support for commonly accepted, but previously untested, hypotheses regarding factors that drive the occurrence of an imperiled and data-deficient amphibian, the eastern hellbender (Cryptobranchus alleganiensis). We investigated the potential for mismatch between areas likely to be identified as having high conservation priority based on the common assumption that hellbender occurrence corresponds to areas of high forest cover and those identified by well-informed models.Location South-west Virginia, USA.Methods We conducted triplicate surveys to detect C. alleganiensis in 49 stream reaches stratified across a land use gradient and two major drainages. We used a Bayesian multimodel framework to investigate factors associated with C. alleganiensis occupancy. We used the best-performing models to predict probability of occupancy at the scale of a 50-m stream reach throughout our study area and identify areas most likely to be occupied.Results Occurrence of C. alleganiensis was explained primarily by differences in underlying geology and topography (i.e. physiography) and negative effects of agriculture were only modestly supported. Best-performing models suggested 35% of our study area was occupied. Our findings suggest that predictions from models informed by presence-only data and current land use would likely underestimate C. alleganiensis occupancy by as much as one-third and incorrectly classify over half the currently occupied area to be of little importance to the species.Main conclusion Our study highlights the potential danger of assuming that the distribution of data-deficient species can be approximated using untested, but commonly accepted, species-habitat associations.

Using environmental DNA and occupancy modelling to identify drivers of eastern hellbender (Cryptobranchus alleganiensis alleganiensis) extirpation

“…We used three categories of predictor variables to develop models of hellbender extirpation: hydrogeomorphic, current land cover, and historical mining ( For each site, we calculated tree canopy cover (2015 imagery) at the catchment and riparian scale using a freely available 30 m resolution dataset (Sexton et al, 2013, www.landcover.org). Highly forested catchments that protect in-stream habitat and water quality have been associated with hellbender occurrence, but quantitative evidence is lacking, and the effect of tree cover loss may be time-lagged (Bodinof Jachowski et al, 2016;Wheeler et al, 2003;Williams, Gates, Hocutt, & Taylor, 1981). We chose not to include the National Land Cover Dataset (Homer et al, 2015) classes that are regularly used in catchment-scale ecological studies because of the issues associated with highly correlated land cover classes (King et al, 2005).…”

“…Hellbenders inhabit streams with fast flow, cobble/boulder rock cover, and good water quality (Nickerson & Mays, 1973). Current research has focused on identifying quantitative relationships among suspected land use, habitat, and water quality variables associated with the species presence and changes in population demography (Bodinof Jachowski & Hopkins, 2018;Bodinof Jachowski, Millspaugh, & Hopkins, 2016;Freake & DePerno, 2017;Pitt et al, 2017). Causal agents of population declines are suspected to be habitat loss via siltation and filling of interstitial spaces because of anthropogenic landscape disturbances and water quality declines that impede successful reproduction via a lack of recruitment (Pitt et al, 2017).…”

Decline of a giant salamander assessed with historical records, environmental DNA and multi‐scale habitat data

“…We followed the eDNA survey protocol of Spear et al (2015); a recent study estimated a detection probability of 0.9 for hellbender DNA using this specific protocol (Franklin, 2016). Reported detection probabilities for traditional snorkelling-based survey methods range up to 0.9 (Franklin, 2016;Pugh et al, 2016), but may be dramatically reduced by factors such as low visibility (Bodinof Jachowski et al, 2016). Furthermore, the use of eDNA has consistently identified more hellbender sites than traditional snorkelling-based survey methods alone (Franklin, 2016;Santas et al, 2013;Spear et al, 2015).…”

“…The distribution and status of hellbender populations in large portions of their range remain poorly known (Bodinof Jachowski, Millspaugh, & Hopkins, 2016), in part because traditional survey methods are time-consuming and labour-intensive and hellbenders can be difficult to detect (Nickerson & Mays, 1973;Rossell et al, 2013). Several studies have successfully used eDNA to detect the presence of giant salamanders such as hellbenders (Fukumoto, Ushimaru, & Minamoto, 2015;Olson et al, 2012;Santas, Persaud, Wolfe, & Bauman, 2013;Spear et al, 2015).…”

Environmental gradients in old‐growth Appalachian forest predict fine‐scale distribution, co‐occurrence, and density of woodland salamanders

“…See Appendix S1-S5 for a complete list of models fitted. For examples of studies using similar stepwise procedures, seeGovindan, Kéry, and Swihart (2012),Scherer, Muths, and Noon (2012), Kéry Guillera-Arroita and Lahoz-Monfort (2013),Peterman, Crawford, and Kuhns (2013),Peterman and Semlitsch (2013),and Jachowski, Millspaugh, and Hopkins (2016).…”