Identification and characterization of nine polymorphic microsatellite loci in the North American pika,Ochotona princeps

Nine polymorphic microsatellite loci were developed for the North American pika (Ochotona princeps) from di‐ and tetranucleotide repeat‐enriched genomic libraries. Polymorphism was assessed for 165 individuals from eight geographical locations in the western United States. All loci were polymorphic. The number of alleles per locus ranged from three to 14, with observed heterozygosity between 0.189 and 0.822. All loci were in Hardy–Weinberg equilibrium (< 0.05). Regional differences were evident with unique alleles at multiple loci in six of eight populations.     

American pika in a low‐elevation lava landscape: expanding the known distribution of a temperature‐sensitive species

In 2010, the American pika (Ochotona princeps fenisex) was denied federal protection based on limited evidence of persistence in low‐elevation environments. Studies in nonalpine areas have been limited to relatively few environments, and it is unclear whether patterns observed elsewhere (e.g., Bodie, CA) represent other nonalpine habitats. This study was designed to establish pika presence in a new location, determine distribution within the surveyed area, and evaluate influences of elevation, vegetation, lava complexity, and distance to habitat edge on pika site occupancy. In 2011 and 2012, we conducted surveys for American pika on four distinct subalpine lava flows of Newberry National Volcanic Monument, Oregon, USA. Field surveys were conducted at predetermined locations within lava flows via silent observation and active searching for pika sign. Site habitat characteristics were included as predictors of occupancy in multinomial regression models. Above and belowground temperatures were recorded at a subsample of pika detection sites. Pika were detected in 26% (2011) and 19% (2012) of survey plots. Seventy‐four pika were detected outside survey plot boundaries. Lava complexity was the strongest predictor of pika occurrence, where pika were up to seven times more likely to occur in the most complicated lava formations. Pika were two times more likely to occur with increasing elevation, although they were found at all elevations in the study area. This study expands the known distribution of the species and provides additional evidence for persistence in nonalpine habitats. Results partially support the predictive occupancy model developed for pika at Craters of the Moon National Monument, another lava environment. Characteristics of the lava environment clearly influence pika site occupancy, but habitat variables reported as important in other studies were inconclusive here. Further work is needed to gain a better understanding of the species’ current distribution and ability to persist under future climate conditions.     

Variation in subsurface thermal characteristics of microrefuges used by range core and peripheral populations of the American pika (Ochotona princeps)

Microrefuges provide microclimates decoupled from inhospitable regional climate regimes that enable range‐peripheral populations to persist and are important to cold‐adapted species in an era of accelerated climate change. However, identifying and describing the thermal characteristics of microrefuge habitats is challenging, particularly for mobile organisms in cryptic, patchy habitats. We examined variation in subsurface thermal conditions of microrefuge habitats among different rock substrate types used by the American pika (Ochotona princeps ), a climate‐sensitive, rock‐dwelling Lagomorph. We compared subsurface temperatures in talus and lava substrates in pika survey sites in two US national park units; one park study area on the range periphery and the other in the range core. We deployed paired sensors to examine within‐site temperature variation. We hypothesized that subsurface temperatures within occupied sites and structurally complex substrates would be cooler in summer and warmer in winter than unoccupied and less complex sites. Although within‐site variability was high, with correlations between paired sensors as low as 47%, we found compelling evidence that pikas occupy microrefuge habitats where subsurface conditions provide more thermal stability than in unoccupied microhabitats. The percentage of days in which microhabitat temperatures were between ?2.5 and 25.5°C was significantly higher in occupied sites. Interestingly, thermal conditions were substantially more stable (p  < .05) in the lava substrate type identified to be preferentially used by pikas (pahoehoe vs. a'a) in a previous study. Our study and others suggest that thermal stability appears to be the defining characteristic of subsurface microrefuges used by American pikas and is a likely explanation for enigmatic population persistence at the range periphery. Our study exemplifies an integrated approach for studying complex microhabitat conditions, paired with site use surveys and contextualized with information about gene flow provided by complementary studies.     

Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat

Aim

Citizen science is a cost-effective potential source of invasive species occurrence data. However, data quality issues due to unstructured sampling approaches may discourage the use of these observations by science and conservation professionals. This study explored the utility of low-structure iNaturalist citizen science data in invasive plant monitoring. We first examined the prevalence of invasive taxa in iNaturalist plant observations and sampling biases associated with these data. Using four invasive species as examples, we then compared iNaturalist and professional agency observations and used the two datasets to model suitable habitat for each species.

Location

Hawai'i, USA.

Methods

To estimate the prevalence of invasive plant data, we compared the number of species and observations recorded in iNaturalist to botanical checklists for Hawai'i. Sampling bias was quantified along gradients of site accessibility, protective status and vegetation disturbance using a bias index. Habitat suitability for four invasive species was modelled in Maxent, using observations from iNaturalist, professional agencies and stratified subsets of iNaturalist data.

Results

iNaturalist plant observations were biased towards invasive species, which were frequently recorded in areas with higher road/trail density and vegetation disturbance. Professional observations of four example invasive species tended to occur in less accessible, native-dominated sites. Habitat suitability models based on iNaturalist versus professional data showed moderate overlap and different distributions of suitable habitat across vegetation disturbance classes. Stratifying iNaturalist observations had little effect on how suitable habitat was distributed for the species modelled in this study.

Main Conclusions

Opportunistic iNaturalist observations have the potential to complement and expand professional invasive plant monitoring, which we found was often affected by inverse sampling biases. Invasive species represented a high proportion of iNaturalist plant observations, and were recorded in environments that were not captured by professional surveys. Combining the datasets thus led to more comprehensive estimates of suitable habitat.     

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current,past, and future climates

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat‐balance model, to convert macroclimate data to pika‐specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate‐imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.     

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.