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Janet L. Rachlow

Publications and source records attributed to Janet L. Rachlow.

6 recordsLinked to original sources

Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter

Collared pikas ( Ochotona collaris ) are cold adapted alpine lagomorphs of western Canada and Alaska, USA, that are vulnerable to direct and indirect effects of climate change. However, how and to what extent such changes influence persistence for this species is not well understood, particularly at fine spatial scales. Our goal was to evaluate how microclimate and microhabitat characteristics influence occupancy of collared pikas. We quantified thermal conditions during both summer and winter to test hypotheses about potential drivers of pika persistence. We recorded den occupancy and territory characteristics, including in situ measurements of den microclimate, across three study areas with contrasting climate gradients in southcentral and interior Alaska during 2017–2022. We examined changes in pika den occurrence by estimating annual colonization and extinction rates with a Bayesian dynamic occurrence model with forage availability, rock size, and multiple den temperature metrics as the explanatory variables. Our top model indicated that daily maximum temperature during both summer and winter best predicted den persistence and larger rocks had a moderating effect on warm summer den temperatures. This information helps to advance understanding about the mechanistic links between climate and population persistence for small mammal species under a rapidly changing arctic climate.

Alaska

Leveraging rangeland monitoring data for wildlife: From concept to practice

Available rangeland data, from field-measured plots to remotely sensed landscapes, provide much needed information for mapping and modeling wildlife habitats. Better integration of wildlife habitat characteristics into rangeland monitoring schemes is needed for most rangeland wildlife species at varying spatial and temporal scales. Here, we aim to stimulate use of and inspire ideas about rangeland monitoring data in the context of wildlife habitat modeling and species conservation.

Colorado, Kansas, Montana, Nebraska, New Mexico, N

Effects of body size on estimation of mammalian area requirements

Accurately quantifying species’ area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.

Conservation Biology

Transition of vegetation states positively affects harvester ants in the Great Basin, United States

Invasions by non-native plants can alter ecosystems such that new ecological states are reached, but less is known about how these transitions influence animal populations. Sagebrush (Artemisia tridentata) ecosystems are experiencing state changes because of fire and invasion by exotic annual grasses. Our goal was to study the effects of these state changes on the Owyhee and western harvester ants ( Pogonomyrmex salinus Olsen and P. occidentalis Cresson, respectively). We sampled 358 1-ha plots across the northern Great Basin, which captured unburned and burned conditions across 1 −≥31 years postfire. Our results indicated an immediate and consistent change in vegetation states from shrubland to grassland between 1 and 31 years postfire. Harvester ant occupancy was unrelated to time since fire, whereas we observed a positive effect of fire on nest density. Similarly, we discovered that fire and invasion by exotic annuals were weak predictors of harvester ant occupancy but strong predictors of nest density. Occupancy of harvester ants was more likely in areas with finer-textured soils, low precipitation, abundant native forbs, and low shrub cover. Nest density was higher in arid locations that recently burned and exhibited abundant exotic annual and perennial (exotic and native) grasses. Finally, we discovered that burned areas that received postfire restoration had minimal influence on harvester ant occupancy or nest density compared with burned and untreated areas. These results suggest that fire-induced state changes from native shrublands to grasslands dominated by non-native grasses have a positive effect on density of harvester ants (but not occupancy), and that postfire restoration does not appear to positively or negatively affect harvester ants. Although wildfire and invasion by exotic annual grasses may negatively affect other species, harvester ants may indeed be one of the few winners among a myriad of losers linked to vegetation state changes within sagebrush ecosystems.

Great Basin

Sampling animal sign in heterogeneous environments: how much is enough?

Animal ecologists often use animal sign as a surrogate for direct observation of organisms, especially when species are secretive or difficult to observe. Spatial heterogeneity in arid environments makes it challenging to consistently detect and precisely characterize animal sign, which can bias estimates of animal abundance or habitat use. Piute ground squirrels ( Urocitellus mollis ) and Owyhee harvester ants ( Pogonomyrmex salinus ) live in arid environments and are fossorial, which can make them difficult to observe directly. Their relative abundance can be assessed using sign (i.e., burrows and nests). We implemented an over-sampling framework (i.e., recorded an excessive amount of information) with two observers to 1) identify a sampling intensity that balanced precision with our resource constraints, and 2) assess classification and detection of squirrel burrows and ant nests across vegetation conditions. We sampled 20 1-ha plots for ground squirrel burrows and ant nests using six 4 m × 100 m belt transects. Analyses of precision and sampling effort indicated that three belt transects covering 1200 m 2 per ha provided sufficient precision, while minimizing effort. Regardless of vegetation conditions, counts by two observers were strongly correlated for ground squirrel burrows ( r = 0.99, P < 0.001, df = 18; slope = 0.92) and harvester ant nests ( r = 0.99, P < 0.001, df = 18; slope = 1.01) indicating observer consistency and perhaps high detection probability. These findings illustrate an approach for evaluating sampling designs in many ecological contexts.

Journal of Arid Environments