Collapse of a desert bird community over the past century driven by climate change

Climate change has caused deserts, already defined by climatic extremes, to warm and dry more rapidly than other ecoregions in the contiguous United States over the last 50 years. Desert birds persist near the edge of their physiological limits, and climate change could cause lethal dehydration and hyperthermia, leading to decline or extirpation of some species. We evaluated how desert birds have responded to climate and habitat change by resurveying historic sites throughout the Mojave Desert that were originally surveyed for avian diversity during the early 20th century by Joseph Grinnell and colleagues. We found strong evidence of an avian community in collapse. Sites lost on average 43% of their species, and occupancy probability declined significantly for 39 of 135 breeding birds. The common raven was the only native species to substantially increase across survey sites. Climate change, particularly decline in precipitation, was the most important driver of site-level persistence, while habitat change had a secondary influence. Habitat preference and diet were the two most important species traits associated with occupancy change. The presence of surface water reduced the loss of site-level richness, creating refugia. The collapse of the avian community over the past century may indicate a larger imbalance in the Mojave and provide an early warning of future ecosystem disintegration, given climate models unanimously predict an increasingly dry and hot future

Identifying infestation probabilities of Emerald Ash Borer (Agrilus planipennis, Fairmaire) in the Mid-Atlantic region

Emerald Ash Borer (EAB) impacts all species of North American ash trees, and has caused several million dollars (U.S.) in damage to trees across the affected region. EAB is primarily spread through the movement of trees and wood products, such as nursery stock and firewood. This thesis assessed the potential risk of EAB introduction in the Mid-Atlantic region of the U.S., where the species has not yet been as widely reported. Using a Geographic Information Systems-based approach, a risk prioritization framework was developed to assess and rank various mapped factors for EAB introduction. Results indicated high risk areas throughout the study region with approximately 30 counties being cited for potential risk. From an analysis of risk versus ash basal area for all counties, three management strategies were derived; quarantine, plan harvest, public outreach and monitoring

Non-invasive methods for obtaining occupancy probabilities and density estimates of Interior Alaska's mesocarnivore populations

Thesis (M.S.) University of Alaska Fairbanks, 2015Mesocarnivore species worldwide have been shown to be significant drivers of ecological communities. Changes in their abundance and distributions are known to cause cascading effects throughout ecosystems, and changes to the landscape and climate will likely lead to shifts in mesocarnivore population sizes and distributions. However, the current status of these species in some of the world's most susceptible landscapes is not known. I assessed the impacts of abiotic factors on the distributional patterns and abundance of boreal mesocarnivores and evaluated methods commonly used to estimate density and occupancy. I conducted non-invasive winter surveys of coyotes (Canis latrans), red foxes (Vulpes vulpes), lynx (Lynx canadensis), wolverines (Gulo gulo), and marten (Martes americana) in the interior of Alaska. Overall, mesocarnivore occupancy was most strongly influenced by snow depth and snow compaction as well as habitat type. Canid species used areas with shallow and compact snow while mustelid species used deeper and fluffier snow conditions most often, and lynx used areas with shallow and fluffy snow. Forested habitat types were used most commonly across all mesocarnivores. Prey abundance and the presence of human activity were less influential to mesocarnivore occupancy patterns than snow conditions and habitat, suggesting that a changing boreal climate may have a strong, direct influence on the distribution of these mesocarnivores. Estimating current population status of these species is particularly important in areas that are most susceptible to change, and I used two occupancy-modeling methods and a spatially explicit capture-recapture density estimator to assess coyote and red fox populations. Occupancy and density are two distinct parameters, however, the simplicity of occupancy (both in terms of sampling and modeling) makes its use as a proxy for density an appealing possibility. I found that occupancy and density estimates were not consistent and led to significantly different inference about coyote and red fox populations. Coyotes and red fox occupancy probabilities were similar to each other (range: 0.34-0.48), but red fox density was nearly four times greater than coyote density. While both methods produced precise parameter estimates, top-ranking occupancy and density models were different. I suggest that managers use caution when using occupancy as a proxy for density. Occupancy is best used to address questions related to spatial use, while density should be used to assess population size. Together, these findings provide valuable information about the current status of a previously unstudied mesocarnivore community and provide managers with useful insight into study design and management actions that should be taken to best protect this guild

Modeling Range Dynamics In Heterogeneous Landscapes: Invasion Of The Hemlock Woolly Adelgid In Eastern North America

Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951–2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.Organismic and Evolutionary Biolog

Modeling Tree Species Distribution and Dynamics Under a Changing Climate, Natural Disturbances, and Harvest Alternatives in the Southern United States

Forests in the southern United States with diverse forest ownership entities are facing threats associated with climate change and natural disturbances. This study represented the relationship between climate and species dominance, predicted future species distribution probability under a changing climate, and projected forest dynamics under ownership-based management regimes. Correlative statistics and mechanistic modeling approaches are implemented. Temporal scale includes the recent past 40 years and the future 60 years; spatial scale downscaled from southern United States to the coastal region of the northern Gulf of Mexico. In the southern United States, dominance of four major pine species experienced shifts from 1970 to 2000; quantile regression models built on the relationships among pine dominance and climatic variables can be used to predict future southern pine dominance. Furthermore, multiple climate envelope models (CEMs) were constructed for nineteen native and one invasive tree species (Chinese tallow, Triadica sebifera) to predict species establishment probabilities (SEPs) on the various land types from 2010 to 2070. CEMs achieved both predictive consistency and ecological conformity in estimating SEPs. Chinese tallow was predicted to have the highest invasionability in longleaf/slash pine and oak/gum/cypress forests during the next 60 years. Forest dynamics, in the coastal region, was projected by linking CEMs and forest landscape model (LANDIS) to evaluate ownership-based management regimes under climate change and natural disturbances. The dominance of forest species will diminish due to climate change and natural disturbances at both spatial scales—in the coastal region and non-industrial private forest (NIPF). No management on NIPF land was predicted to substantially increase the ratio of occupancy area between pines and oaks, but moderate and intensive management regimes were not significantly different. Pines are expected to be more resistant than oaks by maintaining stable age structures, which matched the forest inventory records. Overall, this study projected a future of southern forests on climate-species relationship, invasion risks, and forest community dynamics under multiple scenarios in the United States. Such knowledge could assist forest managers and landowners in foreseeing the future and making effective management prescriptions to mitigate potential threats

REGIONAL IMPACTS OF INVASIVE SPECIES AND CLIMATE CHANGE ON BLACK ASH WETLANDS

For more than a decade intensive research on the ecohydrology of black ash wetland ecosystems has been performed to understand these systems before they are drastically altered by the invasive species, emerald ash borer (EAB). In that time there has been little research aimed at the scale and persistence of the alterations. Three distinct but related research articles will be presented to demonstrate a method for moderate resolution mapping of black ash across its entire range, understand the relative impacts of EAB and climate change on probable future wetland conditions, and develop an experimental and modeling approach to quantify and reduce uncertainty around water level measurements that underpin much of our understanding in these systems. Results from this research demonstrate that the scale and persistence of these impacts will be dependent not only on the immediate impacts of EAB, but also on vegetative response, the true extent of black ash wetlands on the landscape, and the compounding influence of a changing climate. Major findings from this research include 1) the effects of EAB and climate in the study area are counteracting, generally with a larger drying climate impact, 2) across its range black ash can be distinguished from other forest types using a combination of unsupervised and supervised learning on satellite imagery, and 3) over larger spatial scales and time periods uncertainty of our results is critical for interpretation and should be considered at the lowest level of data collection. At a higher level, this research is intended to serve as a bridge between study-site level changes and the spatial and temporal extent of those changes, opening new research questions to better understand these relatively rapid shifts in regional forested wetlands

Using Species Distribution Models to Assess Invasion Theory and Provide Management Recommendations for Riparian Areas in the Eastern Columbia and Western Missouri River Basins

Invasive plant species impact ecosystems by altering native plant community composition and modifying ecosystem properties such as fire and nutrient cycles. We used species distribution models to address both theoretical and applied questions regarding invasive plants in an ecosystem particularly vulnerable to invasion, riparian areas. In our first study, we asked whether a native species is closer to equilibrium than a functionally similar invasive species and determined drivers of invasion for an aggressive invader of riparian areas, Phalaris arundinacea (reed canarygrass). We modeled the presence of P. arundinacea and a comparable native species using four techniques and compared model fit between species and between models with and without dispersal processes incorporated. Non-dispersal model fit for our invasive species was lower than for the native species and improvement in fit with the addition of the dispersal constraint was greater for the invasive species than the native species. These results provide evidence that invasive species are further from equilibrium than native species and suggest that dispersal processes should be considered when modeling invasive species. In our second study, we addressed whether there was a set of site traits that make some sites more prone to invasion by non-native plants than others. We used Random Forests to individually model the presence of 11 invasive plant species that are designated as noxious weeds in our study area. We used model results to identify general patterns of invasion and to provide management recommendations for the study area. We found that a particular site type was more likely to be invaded by the majority of study species: hot, dry sites with high grass or shrub cover near roads with high nutrient levels and high stream baseflow values. Management recommendations to combat invasion by P. arundinacea in particular and invasive species in general are the same: limiting species’ spread along roads, lowering site nutrient levels, and anticipating increased spread with climate change

MODELING FIRE OBSERVATIONS, IGNITION SOURCES, AND NOVEL FUELS TO UNDERSTAND HUMAN IMPACTS ON FIRE REGIMES ACROSS THE U.S.

Fire is a natural, and necessary, component of many ecosystems. However, people are changing the spatial and temporal distribution of wildfires in the U.S. at great economic and ecological costs. My dissertation addresses the impacts of humans on U.S. fires both through the introduction of ignition sources and flammable grasses. Further, I evaluate fire datasets that are widely used to investigate these phenomena over large spatial and temporal scales. Finally, I create an aboveground carbon map that can be used to estimate the potential carbon loss consequences in western U.S. ecosystems most at risk to fire. My work shows that humans ignited more than 77% of fires in seven western U.S. ecoregions, and when modeling human ignited fires, I found that the importance of ignition proxies varied considerably among ecoregions. In 21 ecoregions across the U.S., I found that eight species of non-native invasive grasses increased rates of fire occurrence by 27%-230%, and six species increased rates of fire frequency by 24%-150%. I also quantified differences in commonly used satellite derived and agency recorded fire records and found they were disparate across the U.S., suggesting that great care should be taken when deciding which fire database to use when analyzing human impacts on fire regimes. Finally, the new estimates I provide for aboveground carbon in semi-arid western U.S. ecosystems are roughly double that of previous estimates; indicating that potential carbon losses from fire in these ecosystems are much larger than originally thought. I conclude that fire ignitions from human sources, and the alteration of fuels through the introduction of non-native, invasive grasses, have already dramatically impacted fire regimes across the U.S. These impacts are presently and will continue to be compounded by climate change. My dissertation suggests that we must consider human impacts on ignitions, vegetation, and their interaction with climate to most effectively manage, predict, and live with fire