Local and Regional Landscape Characteristics Driving Habitat Selection by Greater Sage-Grouse Along a Fragmented Range Margin

In response to ongoing landscape change, wildlife species are likely to respond in varied ways. By studying habitat specialists, we are able to better understand the most likely ways in which the denizens of threatened ecosystems will react to those changes. Among the most threatened ecosystem types in North America are sagebrush ecosystems of the Intermountain West, where one of its most well-known residents, greater sage grouse (hereafter, “sage-grouse), have lost more than 50% of their habitat due to fire, invasive species, climate change, encroachment by coniferous forests and avian predators using it, and human-caused landscape conversion. Sage-grouse rely on sagebrush throughout their lives, and there are ongoing efforts to protect them as emblems of vulnerable species and to preserve a changing landscape. The purpose of my dissertation, as part of the ongoing efforts, was to improve understanding of how sage-grouse select habitat along their southern distribution edge in southern Utah and Nevada, where habitat tends to be fragmented and of poorer quality. In this research, I used more than six years of location data from GPS transmitters on sage-grouse across four study areas to address how sage-grouse respond to the threats they face and by what means of data analysis we are best able to detect those threats and inform effective conservation. My research shows that, despite the risk posed by avian predators, sage-grouse in these study areas select habitat closer to trees than expected and do so when they are likely able to also use dense sagebrush cover and a rugged landscape to be concealed from predators. I also found that sage-grouse may use habitat near to trees for shade and escape from extreme heat and cold when the sagebrush in their habitat is not enough to provide shelter, suggesting that sage-grouse must often make risky decisions to balance the many threats they face. Finally, I found that random forests, an intuitive machine learning method, are able to detect important effects of sagebrush and tree cover on habitat selection, able to predict those effects in new areas, and should be considered among the useful and important tools for measuring wildlife-habitat associations

SAGE-GROUSE AND THE HUMAN FOOTPRINT: IMPLICATIONS FOR CONSERVATION OF SMALL AND DECLINING POPULATIONS

Implementing conservation in the face of unprecedented landscape change requires an understanding of processes and scales that limit wildlife populations. We assessed landscape-level processes influencing sage-grouse (Centrocercus urophasianus), to a migratory population in the Milk River Basin (MRB), northeast Montana, USA, and south-central Saskatchewan, Canada. A regional analysis of leks (e.g., communal breeding sites) documented that populations impacted by the increasing extent of agricultural tillage, roads, and energy development out to spatial scales larger than previously known. Using bird abundance as a novel way to evaluate human impacts revealed relationships that would have been missed had we not incorporated lek size into analyses. For example, large leks are 4.5 times less likely to occur than small leks when agricultural tillage fragments 21% of land within 1.0km of breeding sites. Sage-grouse in the MRB met or exceeded demographic rates of stable or increasing populations, and thus, are not likely the cause for annual declines. Spring and summer survival of radio-marked females was higher in 2008 (0.91), than in 2007 (0.55), the year we documented an outbreak of West Nile virus. Nest sites in the MRB had lower shrub cover (15%) than range-wide estimates (15-56%), and overall shrub cover instead of sagebrush cover, was a better predictor of nest-site selection. Plains silver sagebrush (Artemesia cana cana) made up half of total shrub cover (7.1%) at nest sites, suggesting that other shrubs compensate for lower sagebrush densities in the MRB. We discovered the longest migratory event observed for sage-grouse, with females travelling 40km to120km from breeding to wintering areas in Wyoming big sagebrush (A. tridentata wyomingensis) habitats in Montana. Habitat may be sufficient to maintain a small population in the MRB, but its ability to persist through time and to buffer against stochasticity is depressed now that this once-large population has become small and isolated. For example, impacts of disease are compounded when acting on fewer individuals and working synergistically with fluctuations in growth rates. Consequently, conservation of sage-grouse in the MRB will depend on maintaining the current habitat base, and on restoring sagebrush-dominated grasslands currently occupied by agricultural tillage

Spatio-temporal population dynamics of Nevada greater sage-grouse from 2000-2018

Dynamic spatio-temporal models, interfaced with long-term time-series data permit a better understanding of population dynamics across large spatial scales. The Greater Sage-Grouse (Centrocercus urophasianus) population appears to be declining across much of their range. However, there is considerable uncertainty in the spatial drivers of this decline. I developed and applied contemporary dynamic spatio-temporal statistical models to 19 years of Greater Sage-Grouse lek count data to examine spatially-explicit drivers of sage grouse population dynamics. Mean expected lek counts in Nevada declined 2.84 birds per lek between 2000 and 2018, however trends varied substantially over space, with northwestern Nevada and the Bi-State (Nevada and California) region experiencing the steepest declines (up to 6 birds per lek), and northeastern Nevada experiencing increased lek attendance. I found that elevation, total precipitation, normalized difference vegetation index, and percent sagebrush were positively correlated with expected lek counts and that drought, slope, percent bare ground, wildfire, and maximum temperatures were negatively correlated with expected lek counts. I also found that sage grouse population dynamics were closely correlated with mean precipitation the preceding 8 years. Specifically, expected lek counts tracked an eight-year precipitation average with lek attendance declining 3-4 years following 8 years of low precipitation. These results support the hypothesis that long-term mean inter-annual precipitation drives sage grouse habitat quality, and ultimately, sage grouse survival and reproduction, affecting the number of birds visiting leks the subsequent years. Finally, I provide spatially explicit maps of population trends from 2000--2018 that can support future sage grouse management and conservation

HIGH-RESOLUTION MAPPING OF HIERARCHICAL GREATER SAGE-GROUSE NESTING HABITAT: A GRAIN-SPECTRUM APPROACH IN NORTHWESTERN WYOMING

Our overall objective was to create a probabilistic nesting-habitat map for the Jackson Hole sage-grouse population that would have utility as a tool for future research, conservation, and management. The models that we developed for this purpose were specified to evaluate whether sage-grouse may be selecting nesting-habitat characteristics simultaneously at various spatial scales. Our spatially-explicit landscape-scale research was implemented primarily with readily available National Agriculture Imagery Program (NAIP) data. All nesting data was collected from 2007-2010. We tested how a broad range of grain sizes (spatial resolution) of covariate values affected the fit to logistic regression models used to estimate parameters for resource selection functions (RSFs). We analyzed habitat response signatures at three scales (extents) of analysis: (1) the nesting-patch scale, (2) the nesting-region scale, and (3) the nest-site scale. Akaike\u27s information criterion corrected for small sample sizes (AICc) and 5-fold cross validation were used to identify the most well-supported and predictive models at each scale. The RSF models were examined separately and then combined into a weighted scale-integrated conditional RSF (SRSF) integrating habitat selection signatures across all three scales. At the nesting-patch scale we determined that sage-grouse nesting occurrence was positively associated with the size of a patch, and the average cover for the patch. At the nesting-region scale, shrub cover of a 769-m-radius grain size was positively associated with nesting-region selection. Distance to tall objects and terrain ruggedness also appeared to influence nesting-region selection at this scale. At the nest-site scale shrub cover and landscape greenness were positively associated with nest-site selection. There was also noteworthy AICc support for terrain ruggedness at the nest-site scale. The SRSF provided a single high-resolution probabilistic GIS surface that mapped out areas that represent attractive sage-grouse nesting habitat

Habitat Suitability Modeling for Wildlife Management Objectives by Using Maximum Entropy Method

Habitat suitability models are useful tools for a variety of wildlife management objectives. Distributions of wildlife species can be predicted for geographical areas that have not been extensively surveyed. The basis of these models' work is to minimize the relationship between species distribution and biotic and abiotic environments. For some species, there is information about presence and absence that allows the use of a variety of standard statistical methods. However, absence data is not available for most species. Nowadays, the methods that need presence-only data have been expanded. One of these methods is the Maximum Entropy (MaxEnt) model. The purpose of this study is to model the habitat of Urial (Ovis orientalis arkal) in the Samelghan plain in the North East of Iran with the MaxEnt method. This algorithm uses the Jackknife plot and percent contribution values to determine the significance of the variables. The results showed that variables such as southern aspects, Juniperus-Acer, Artemisia-Perennial plants, slope 0-5%, and asphalt road were the most important factors affecting the species' habitat selection. The area under the curve (AUC) Receiver Operating Characteristic (ROC) showed excellent model performance. Suitable habitat was classified based on the threshold value (0.0513) and the ROC, which, based on the results, 28% of the area was a suitable habitat for Urial. Doi: 10.28991/HEF-2021-02-04-05 Full Text: PD

Using presence-only and presence–absence data to estimate the current and potential distributions of established invasive species

1.Predicting the current and potential distributions of established invasive species is critical for evaluating management options, but methods for differentiating these distributions have received little attention. In particular, there is uncertainty among invasive species managers about the value of information from incidental sightings compared to data from designed field surveys. This study compares the two approaches, and develops a unifying framework, using the case of invasive sambar deer Cervus unicolor in Victoria, Australia

Unveiling the factors shaping the distribution of widely distributed alpine vertebrates, using multi-scale ecological niche modelling of the bat Plecotus macrobullaris

Several alpine vertebrates share a distribution pattern that extends across the South-western Palearctic but is limited to the main mountain massifs. Although they are usually regarded as cold-adapted species, the range of many alpine vertebrates also includes relatively warm areas, suggesting that factors beyond climatic conditions may be driving their distribution. In this work we first recognize the species belonging to the mentioned biogeographic group and, based on the environmental niche analysis of Plecotus macrobullaris, we identify and characterize the environmental factors constraining their ranges. Distribution overlap analysis of 504 European vertebrates was done using the Sorensen Similarity Index, and we identified four birds and one mammal that share the distribution with P. macrobullaris. We generated 135 environmental niche models including different variable combinations and regularization values for P. macrobullaris at two different scales and resolutions. After selecting the best models, we observed that topographic variables outperformed climatic predictors, and the abruptness of the landscape showed better predictive ability than elevation. The best explanatory climatic variable was mean summer temperature, which showed that P. macrobullaris is able to cope with mean temperature ranges spanning up to 16°C. The models showed that the distribution of P. macrobullaris is mainly shaped by topographic factors that provide rock-abundant and open-space habitats rather than climatic determinants, and that the species is not a cold-adapted, but rather a cold-tolerant eurithermic organism. P. macrobullaris shares its distribution pattern as well as several ecological features with five other alpine vertebrates, suggesting that the conclusions obtained from this study might be extensible to them. We concluded that rock-dwelling and open-space foraging vertebrates with broad temperature tolerance are the best candidates to show wide alpine distribution in the Western Palearctic. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12983-014-0077-6) contains supplementary material, which is available to authorized users

Assessment of the effect of climate changes in the Late Pleistocene and Holocene on niche conservatism of an arvicolid specialist

Climate change is not only evident, but its implications on biodiversity are already patent. The scientific community has delved into the limitations and capabilities of species to face changes in climatic conditions through experimental studies and, primarily, Species Distribution Models (SDMs). Nevertheless, the widespread use of SDMs comes with some intrinsic assumptions, such as niche conservatism, which are not always true. Alternatively, the fossil record can provide additional data to solve the uncertainties of species’ responses to climate change based on their history. Using a combined environmental (niche overlap indices) and geographical approach (temporal transferability of SDMs), we assessed the niche conservatism of Microtus cabrerae throughout its evolutionary history: the Late Pleistocene and the Holocene. The set of analyses performed within this timeframe provides a broad view pointing to a shift in the realized climatic niche of the species. Specifically, M. cabrerae exhibited a broader niche during glacial times than interglacial times, expanding towards novel conditions. Hence, the species might have developed an adaptive ability, as a consequence of mechanisms of local adaptation or natural pressures, or just be preadapted to cope with the novel environment, due to expansion into an unfilled portion of the niche. Nevertheless, the more restricted realized niche during last interglacial times reveals that the species could be close to its physiological limits

Evaluation of multi-hazard map produced using MaxEnt machine learning technique

Natural hazards are diverse and uneven in time and space, therefore, understanding its complexity is key to save human lives and conserve natural ecosystems. Reducing the outputs obtained after each modelling analysis is key to present the results for stakeholders, land managers and policymakers. So, the main goal of this survey was to present a method to synthesize three natural hazards in one multi-hazard map and its evaluation for hazard management and land use planning. To test this methodology, we took as study area the Gorganrood Watershed, located in the Golestan Province (Iran). First, an inventory map of three different types of hazards including flood, landslides, and gullies was prepared using field surveys and different official reports. To generate the susceptibility maps, a total of 17 geo-environmental factors were selected as predictors using the MaxEnt (Maximum Entropy) machine learning technique. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic-ROC curves and calculating the area under the ROC curve-AUCROC. The MaxEnt model not only implemented superbly in the degree of fitting, but also obtained significant results in predictive performance. Variables importance of the three studied types of hazards showed that river density, distance from streams, and elevation were the most important factors for flood, respectively. Lithological units, elevation, and annual mean rainfall were relevant for detecting landslides. On the other hand, annual mean rainfall, elevation, and lithological units were used for gully erosion mapping in this study area. Finally, by combining the flood, landslides, and gully erosion susceptibility maps, an integrated multi-hazard map was created. The results demonstrated that 60% of the area is subjected to hazards, reaching a proportion of landslides up to 21.2% in the whole territory. We conclude that using this type of multi-hazard map may be a useful tool for local administrators to identify areas susceptible to hazards at large scales as we demonstrated in this research

Modeling relative habitat suitability and movement behavior of invasive Burmese pythons in southern Florida

Invasive Burmese pythons are established in the Everglades and are altering the ecology of southern Florida. Their distribution in Florida is expanding northward into more urbanized and fragmented habitats. An understanding of the suitability of habitat throughout southern Florida for Burmese pythons and their interaction with Florida’s landscapes through movement behavior is vital for predicting the python’s ability to persist in habitats outside of the Everglades. In this thesis, we use ecological modeling to predict habitat suitability and to investigate personality-dependent dispersal. First, we used presence-only ecological niche modeling with correction for sampling bias to identify the key landscape variables in predicting habitat suitability for pythons at the present stage of the invasion. We found estuarine habitat and freshwater wetlands to be the important variables to contribute to python habitat suitability when considered at the scale of a Burmese python’s home range. Then we used an individual based model to explore risk-taking behavior on a shy-bold continuum of animal personality of dispersing juvenile Burmese pythons on the leading edge of the population’s expansion from the Everglades into Homestead and south Miami, Florida. We observed that a behaviorally plastic strategy best resembled empirically derived patterns of the python’s expansion into increasingly urbanized landscapes