Lidar-Based Models of Understory Bird Habitat in a Tropical Forest

Where a poorly understood group of wildlife species seems to be declining quickly, a rapid assessment of the species’ habitat requirements may be needed in order to make the most optimal management decisions possible. We used bird presence data and a combination of field data and full-waveform lidar data to predict and interpret the distributions of declining insectivorous understory bird species at the La Selva Biological Station in Costa Rica. Raw lidar waveforms were used to create metrics of multi-dimensional forest structure which take into account not only horizontal structure such as patches and their arrangement or fragmentation, but also the vertical structure of vegetation such as canopy height and the distribution of canopy layers. Habitat models for four species of understory insectivore were developed using MaxEnt and validated using a jackknife approach, while guild diversity was estimated across the landscape using multiple logistic regression. Habitat projections for individual species showed high and significant predictive ability in jackknife tests. Results of habitat modeling showed significant differences between species in terms of which habitat variables were most important, but percent cover, distance to forest edge, foliage height diversity, and canopy height were consistently important. Metrics derived from canopy height profiles were consistently more useful predictors than metrics from the raw lidar waveforms. General metrics such as canopy height, elevation, and distance to edge were generally more useful predictors than understory-specific metrics, which could indicate that understory insectivores respond more strongly to climate & habitat patch size than to understory structure at a micro level. Alternatively, large-footprint lidar may be unable to adequately represent the aspects of understory structure which impact understory birds. Overall, however, models which included canopy height profile metrics significantly improved upon models which did not, indicating that inclusion of measures of multi-dimensional forest structure which account for the understory may add value to lidar-based habitat models for many wildlife species.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/88165/1/AGrimm_Thesis_Final.pd

Improving Understanding of Forest Communities and Biodiversity with Multi-Dimensional Landscape Gradients

This dissertation was motivated by a desire to understand the effects of habitat degradation and urbanization on a single species in a single study system in western Massachusetts, the red-backed salamander (Plethodon cinereus), but along the way unexpected conceptual and methodological hurdles caused the work to grow into a multi-species, multi-region, and multi-scale endeavor. As I designed my dissertation research and began considering approaches to quantifying heterogeneity and human influence in my study landscape, I recognized inconsistencies in methods used to define and quantify landscape metrics, particularly in urban systems. To investigate further, I conducted a critical review of the literature to describe the current practices of landscape quantification in urban systems and to identify any patterns or trends. The review highlighted the fact that variability among definitions of ‘urban’ stems from inconsistent decision making around a set of core principles in landscape ecology, and I used these to establish a standardizing framework for landscape gradient quantification. I then applied this framework to 10 ecologically distinct metro-regions across the United States and revealed a consistent pair of gradients that offer an updated multi-dimensional perspective of landscape heterogeneity that intuitively advances the one-dimension perspective dominating exiting approaches to studying ecological responses across gradients of human influence. Having developed a framework for gradient definition, and extending the single-axis lens through which ecological enquiry is made, I applied these approaches to first investigate environmental drivers of avian community size and structure, and second, to critically evaluate the validity of the red-backed salamander as an indicator for biodiversity in human-dominated landscapes. Inconsistencies in definitions of “urbanization” are commonly attributed to the lack of general theory describing ecosystem function in urban landscapes. In Chapter 1, I review the literature on urban landscape quantification to identify patterns and best practices that could improve the process by which urban landscape gradients are defined and quantified. This review of 250 research articles revealed striking methodological consistency that aligns with the best practices of gradient definition in landscape ecology, these are: (1) selection of features to represent the urban landscape, (2) identification of associated spatial data to characterize these features, and (3) selection of an ecologically appropriate spatial scale. However, the review also highlighted apparent inconsistencies in urban gradient definition that arise from ad-hoc and ambiguous decision making at each of these stages, and demonstrated that ecologically justified and transparent decision making can standardize gradient definition and contribute to improved understanding of ecosystem processes in human-dominated landscapes (Padilla & Sutherland, 2019). In Chapter 2, I address the lack of standardized heterogeneity metrics that can be used to jointly measure multi-regional ecological responses that has hindered the generalization of urban stressors on ecological communities. I coupled the transparent methodological framework developed in Chapter 1 with a multivariate statistical analysis of land use data to quantify landscape structure in 10 medium sized cities representing the dominant ecoregions of the United States to determine whether consistent and biologically meaningful landscape metrics emerge across spatial domains. This work revealed two dominant axes of spatial variation that are intuitively consistent with the characteristics of human-dominated landscape mosaics but are overlooked when defining landscapes along a single axis of variation. In the context of representative landscapes in the United States, these gradients describe variation in the characteristic physical (soft to hard) and natural (brown to green) structure of landscapes influences by human activity. To develop the ecological relevance of the dual-axis landscape definition, I explored the response of American robin (Turdus migratorius) occupancy to these gradients across the 10 cities. This case study demonstrated that robins generally respond similarly and strongly to both landscape axes and that a multi-dimensional perspective reveals ecological nuance that may otherwise be overlooked. In Chapter 3, I apply the concepts developed in the previous two chapters to my study system in western Massachusetts. I tested two leading theories regarding how habitat fragmentation in human-dominated landscapes impacts species communities: island biogeography theory, and spatial heterogeneity. In the case of island biogeography, I expected species diversity to linearly decline as the degree of fragmentation and human-modification to the landscape increased, whereas, spatial heterogeneity would result in a quadratic response where species diversity is greatest in moderately disturbed landscape mosaics. These hypotheses were evaluated with data on the bird communities collected at 42 sites in a 3-year field study that were analyzed using a hierarchical model that allows for estimation of site-specific abundance of each species and species richness while simultaneously accounting for imperfect detection. This analysis revealed a strong non-linear community response to both axes of the multi-dimensional landscape (soft-hard and brown-green) that suggested increased heterogeneity promotes higher species abundance as well as species richness. At the species level, there was variation that corresponded with variation in known habitat preferences and life history traits. These results suggest that variation in species richness follows expectations of the spatial heterogeneity hypothesis that predicts greatest diversity in moderately disturbed landscape mosaics. I hypothesize that this process results from a greater diversity of habitat types available in landscape mosaics, and greater structural complexity within forest fragments that are characteristic of heterogenous mosaics. Finally, in Chapter 4 I provide a rare empirical assessment of the indicator species concept. Specifically, I evaluate the red-backed salamander (Plethodon cinereus) as an indicator of forest biodiversity in human-dominated landscapes. During my 3-year field study, in addition to avian community data, I collected occurrence and abundance data for trees, soil invertebrates and red-backed salamanders at each of the 42 sites. These data were analyzed using a joint-species distribution model to evaluate the salamander’s indicator potential under the premise that species within a community will generally exhibit a shared response to gradients of human influence, and that an ideal indicator species represents an exemplar of the shared community response. I compared this novel approach to indicator species selection with a commonly used metric for identifying indicator species. Despite the frequency with which salamanders are promoted as indicators of forest condition, my results provided no evidence that they are effective indicators for biodiversity based on established conceptual underpinnings of indicator species. As with the avian community, biodiversity showed a non-linear response to the dual axes of human influence where richness is highest in heterogenous landscape. Species that were identified as candidate indicators were species characteristic of edge habitat and dense forests which are common in human-dominated landscape mosaics. In summary, my dissertation provides much needed methodological improvements to landscape gradient quantification in human-dominated systems and demonstrates the applicability of this framework both at a national scale, as demonstrated across the United States, and the local scale as demonstrated in my field system in Western Massachusetts. This framework results in a multi-dimensional perspective of landscape heterogeneity that extends does a better job of representing complex landscapes beyond single-axis measures that confound two intuitive gradients of human influence. I have demonstrated how such a multi-dimensional perspective sheds light on the processes driving the landscape scale patterns of biodiversity and can be used to build evaluate process-based conceptual models for identifying indicator species. In doing so, this work presents a standardizing framework for landscape gradient quantification in human dominated landscapes, an identification of the existence of unifying measures of human influence, and a demonstration of how coupling this approach and a multi-dimensional perspective offers an general framework for understanding spatial variation in ecological communities that exist in human dominated landscape mosaics

Applications of Airborne and Portable LiDAR in the Structural Determination, Management, and Conservation of Southeastern U.S. Pine Forests

Active remote sensing techniques, such as Light Detection and Ranging (LiDAR), have transformed the field of forestry and natural resource management in the last decade. Intensive assessments of forest resources and detailed structural assessments can now be accomplished faster and at multiple landscape scales. The ecological applications of having this valuable information at-hand are still only being developed. This work explores the use of two active remote sensing techniques, airborne and portable LiDAR for forestry applications in a rapidly changing landscape, Southeastern Coastal Pine woodlands. Understanding the strengths and weaknesses of airborne and portable LiDAR, the tools used to extract structural information, and how to apply these to managing fire regimes are key to conserving unique upland pine ecosystems. Measuring habitat structure remotely and predicting habitat suitability through modeling will allow for the management of specific species of interest, such as threatened and endangered species. Chapter one focuses on the estimation of canopy cover and height measures across a variety of conditions of secondary upland pine and hardwood forests at Tall Timbers Research Station, FL. This study is unique since it uses two independent high resolution small-footprint LiDAR datasets (years 2002 and 2008) and extensive field plot and transect sampling for validation. Chapter One explores different tools available for metric derivation and tree extraction from discrete return airborne LiDAR data, highlighting strengths and weaknesses of each. Field and LiDAR datasets yielded better correlations for stand level comparisons, especially in canopy cover and mean height data extracted. Individual tree crown extraction from airborne LiDAR data significantly under-reported the total number of trees reported in the field datasets using either Fusion/LVD and LiDAR Analyst (Overwatch). Chapter two evaluates stand structure at the site of one of the longest running fire ecology studies in the US, located at Tall Timbers Research Station (TTRS) in the southeastern U.S. Small footprint high resolution discrete return LiDAR was used to provide an understanding of the impact of multiple disturbance regimes on forest structure, especially on the 3-dimensional spatial arrangement of multiple structural elements and structural diversity indices. LiDAR data provided sensitive detection of structural metrics, diversity, and fine-scale vertical changes in the understory and mid-canopy structure. Canopy cover and diversity indices were shown to be statistically higher in fire suppressed and less frequently burned plots than in 1- and 2-year fire interval treated plots, which is in general agreement with the increase from 2- to 3-year fire return interval being considered an ecological threshold for these systems (Masters et al. 2005). The results from this study highlight the value of the use of LiDAR in evaluating disturbance impacts on the three-dimensional structure of pine forest systems, particularly over large landscapes. Chapter three uses an affordable portable LiDAR system, first presented by Parker et al. (2004) and further modified for extra portability, to provide an understanding of structural differences between old-growth and secondary-growth forests in the Red Hills area of southwestern Georgia and North Florida. It also provides insight into the strengths and weaknesses in structural determination of ground-based portable systems in contrast to airborne LiDAR systems. Structural plot metrics obtained from airborne and portable LiDAR systems presented some similarities (i.e. canopy cover), but distinct differences appeared when measuring canopy heights (maximum and mean heights) using these different methods. Both the airborne and portable systems were able to provide gap detection and canopy cover estimation at the plot level. The portable system, when compared to the airborne LiDAR sensor, provides an underestimation of canopy cover in open forest systems ([less than]50% canopy cover), but is more sensitive in detection of cover in hardwood woodland plots ([greater than]60% canopy cover). The strength of the portable LiDAR system lies in the detection of 3-dimensional fine structural changes (i.e. recruitment, encroachment) and with higher sensitivity in detecting lower canopy levels, often missed by airborne systems. Chapter four addresses a very promising application for fine-scale airborne LiDAR data, the creation of habitat suitability models for species of management and conservation concerns. This Chapter uses fine scale LiDAR metrics, such as canopy cover at various height strata, canopy height information, and a measure of horizontal vegetation distribution (clumped versus dispersed) to model the preferences of 10 songbirds of interest in southeast US woodlands. The results from this study highlight the rapidly changing nature of habitat conditions and how these impact songbird occurrence. Furthermore, Chapter four provides insight into the use of airborne LiDAR to provide specific management guidance to enhance the suitable habitat for 10 songbird species. The collection of studies presented here provides applied tools for the use of airborne and portable LiDAR for rapid assessment and responsive management in southeastern pine woodlands. The advantages of detecting small changes in three-dimensional vegetation structure and how these can impact habitat functionality and suitability for species of interest are explored throughout the next four chapters. The research presented here provides an original and important contribution in the application of airborne and portable LiDAR datasets in forest management and ecological studies

Lidar Remote Sensing Of Forest Canopy Structure: An Assessment Of The Accuracy Of Lidar And Its Relationship To Higher Trophic Levels

Light detection and ranging (LiDAR) data can provide detailed information about three-dimensional forest horizontal and vertical structure that is important to forest productivity and wildlife habitat. Indeed, LiDAR data have been shown to provide accurate estimates to forest structural parameters and measures of higher trophic levels (e.g., avian abundance and diversity). However, links between forest structure and tree function have not been evaluated using LiDAR. This study was designed and scaled to assess the relationship of LiDAR to multiple aspects of forest structure and higher trophic levels (arthropod and bird populations), which included the ground-based collection of percent crown and understory closure, as well as arthropod and avian abundance and diversity data. Additional plot-based measures were added to assess the relationship of LiDAR to forest health and productivity. High-resolution discrete-return LiDAR data (flown summer of 2009) were acquired for the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA. LiDAR data were classified into four canopy structural categories: 1) high crown and high understory closure, 2) high crown and low understory closure, 3) low crown and high understory closure, and 4) low crown and low understory closure. Nearby plots from each of the four LiDAR categories were grouped into blocks to assess the spatial consistency of data. Ground-based measures of forest canopy structure, site, stand and individual tree measures were collected on nine 50 m-plots from each LiDAR category (36 plots total), during summer of 2012. Analysis of variance was used to assess the relationships between LiDAR and a suite of tree function measures. Our results show the novel ability of LiDAR to assess forest health and productivity at the stand and individual tree level. We found significant correspondence between LiDAR categories and our ground-based measures of tree function, including xylem increment growth, foliar nutrition, crown health, and stand mortality. Furthermore, we found consistent reductions in xylem increment growth, decreases in foliar nutrition and crown health, and increases in stand mortality related to high understory closure. This suggests that LiDAR measures can reflect competitive interactions, not just among overstory trees for light, but also interactions between overstory trees and understory vegetation for resources other than light (e.g., nutrients). High-resolution LiDAR data show promise in the assessment of forest health and productivity related to tree function

EFFECTS OF ABUNDANT SNOW AND ROSS’S GEESE ON ARCTIC ECOSYSTEM STRUCTURE: PLANTS, BIRDS, AND RODENTS

Migratory animals link and often have profound impacts on geographically distant ecosystems through trophic interactions and transport of nutrients, energy, toxins, parasites and pathogens. Moreover, when seasonally linked ecosystems differ in carrying capacity of migrant species, detrimental effects to biodiversity through trophic cascades can occur in ecosystems with lower carrying capacity. Access to agricultural production has increased carrying capacity of lesser snow (Anser caerulescens caerulescens) and Ross’s geese (Anser rossii, collectively, ‘light geese’) in southern agricultural landscapes where these species winter and stage during migration to and from northern breeding regions. Rapid population growth in response to increased carrying capacity during fall, winter, and spring has caused trophic cascades in less productive subarctic and arctic ecosystems during summer. I investigated changes to plant community structure in direct response to foraging and nesting by abundant and highly concentrated light geese within the Queen Maud Gulf (Ahiak) Migratory Bird Sanctuary, Nunavut, Canada, with particular reference to Karrak Lake, one of the largest nesting goose colonies in the world. I further studied indirect impacts of vegetation change on aspects of sympatric vertebrate response, including resident brown lemmings and ptarmigan, and migratory shorebirds and passerines. Foraging by light geese created spatially heterogeneous landscapes composed of lightly and intensely foraged grazing lawns in the brood-rearing and molting region north of Karrak Lake, within the pre-existing mosaic created by variation in topography, moisture, and soil properties created by geomorphic processes. Although foraging light geese nearly depleted aboveground plant biomass in some areas in the Sanctuary, belowground biomass was largely intact and thus, plant communities have strong potential for aboveground regeneration. Nesting and foraging geese severely reduced aboveground plant biomass within the nesting colony at Karrak Lake. Colonizing plant species established on bare sediment or peat exposed by previous vegetation removal by geese, resulting in shifts in species composition of plant communities. High occupancy by nesting light geese resulted in transition of lowland communities dominated by grasses and sedges (collectively, ‘graminoids’), Sphagnum spp., and willows (Salix spp.) to those comprised of exposed peat, birch (Betula glandulosa), non-Sphagnum mosses, marsh ragwort (Tephroseris palustris), and mare’s tail (Hippuris vulgaris). Community changes were less apparent in upland regions that are naturally less vegetated even in the absence of geese, but fruticose lichens, crowberry (Empetrum nigrum) and white heather (Cassiope tetragona) dominated undisturbed plant communities whereas crustose lichens and bearberry (Arctostaphylos spp.) comprised disturbed communities. Reduction of plant biomass and community shifts from graminoid dominance to those with high proportions of exposed peat and birch had negative effects on abundance of brown lemmings and occupancy by graminoid-specialist shorebirds; however, some open-nesting and generalist cover-nesting avian species showed neutral or positive responses to establishment of birch in altered habitats. Intact graminoid communities are important to ecosystem structure and function and population health of many resident and migratory arctic vertebrates. However, light geese often nest in localized, dense aggregations, and thus negative impacts on sympatric species may be spatially limited and confined to large nesting colonies and severely altered brood-rearing and molting regions. Moreover, altered upland and lowland habitats remained largely vegetated in the Sanctuary, contrasting sharply with altered coastal marshes in subarctic regions

Climate Change, Woodpeckers, and Forests: Current Trends and Future Modeling Needs

The structure and composition of forest ecosystems are expected to shift with climate‐induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate‐driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape‐scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate–woodpecker models and compare the predicted responses to observed climate‐induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad‐scale climate–woodpecker models results in model–data mismatch. As a first step toward improvement, we suggest a conceptual model of climate–woodpecker–forest modeling for integration. The integration model provides climate‐driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling

Impacts of non-renewable resource extraction on shrubland songbird nest success and abundance

Shrubland songbirds are a highly imperiled guild across much of North America due to wide-scale land use changes and resulting loss of shrubland habitat. Land management practices which produce early-successional habitat, namely field abandonment and clearcut timber harvests, have become increasingly uncommon in the eastern United States, and natural maintenance processes such as fires and floods are often suppressed. The Appalachian region is rich in natural resources; it has historically seen high amounts of surface mining for coal and is currently experiencing prolific development of shale gas. Both of these practices alter local habitats and the landscape, and it is essential to understand their impacts on shrubland songbirds in order to inform conservation efforts for this declining guild. Research for this thesis was composed of three studies during the breeding seasons of 2012-2013 on four shrubland sites in southwestern Pennsylvania and the northern panhandle of West Virginia. This work aimed to fill knowledge gaps in shrubland songbird ecology and responses to extractive land uses. In my second chapter I focus on habitat selection patterns and nesting ecology of one species, the Blue-winged Warbler (Vermivora cyanoptera). This species has not been studied much outside of its antagonistic relationship to the closely related and highly imperiled Golden-winged Warbler (Vermivora chrysoptera). A quantitative habitat selection study for the species has never been done, although knowing habitat requirements is key to effective conservation measures. I found significant differences in vegetative structure between territories and random plots using non-parametric MANOVA, indicating strong patterns of territory selection. Blue-winged Warblers placed territories in later stages of succession relative to the sites as a whole, having more woody structure, taller vegetation, more shrub, sapling, and canopy cover, and were closer to forest edge than random points. My third chapter is a study on the impact of unconventional shale gas development on shrubland songbird nest success, abundance, and community composition. The practice of unconventional gas development is new to the eastern United States and has become controversial due to concern over environmental impacts, but few studies have been done on the potential effects to terrestrial biota, especially in the east. My objective was to fill a specific research gap, the impacts of development on shrubland songbirds in an already-fragmented landscape context, because this is where both shale gas development and shrubland songbirds are more likely to occur. During the 2013 breeding season, I determined the effects of gas development presence at different spatial scales on shrubland songbird nest success and community dynamics and quantified noise and light emissions from developed pads. There were no differences in noise or light emissions between impacted and non-impacted shrublands, or at a developed site with increasing distance from the wellpad. The presence of gas wells and related infrastructure were important influences on Field Sparrow (Spizella pusilla) nest success; survival was reduced close to the wellpad and increased near pipelines and roads. However, nest survival was higher site-wide for the Field Sparrow and other early successional species on the impacted site than on non-impacted shrublands in the region. Nest predators were important in explaining nest survival variation at the site-level. Within the developed site, nest abandonment was a more likely force near wells and a paved road, while predation better explained variation in survival by distance to the pipeline and unpaved access road. Avian communities significantly differed between impacted and non-impacted sites but the differences were not extractable from vegetative differences. Shannon\u27s diversity and species richness did not differ between impacted and non-impacted sites and had no significant trend with increasing distance from the developed well. Although unconventional gas extraction is new to the region, surface mining has historically been a common practice in Appalachia. Once mining has ceased, these areas stay in early succession conditions for extended durations due to poor topsoil quality, providing habitat for early-successional species which endures on the landscape much longer than habitats in abandoned fields or recent clearcuts. Reclamation of surface mines to a vegetated state is mandated by federal law, but questions have been raised on the habitat quality of the resulting areas. Many studies have assessed the use of former surface mines by various species and the success of grassland-nesting songbirds in these habitats, but none have quantitatively compared nest survival and avian community composition between former surface mines and non-mined shrublands. In my fourth chapter, I determined the utility of former surface mines as breeding habitat for shrubland songbirds. I performed site-level comparisons of community composition, species abundances, and nest survival of three focal species to determine if these metrics differed between former surface mines and non-mined shrublands and also between a reclaimed and a non-reclaimed former surface mine. Whether a site was mined or not was an important factor influencing nest success, as was whether a mined site was reclaimed or not. Daily survival rates of nests for all three species were higher on mined sites and higher on the reclaimed former surface mine. Avian communities did not differ between mined and non-mined sites. Community composition on the reclaimed and non-reclaimed former surface mine sites differed, but most species were detected on both. Vegetative conditions on mined sites were broader and encompassed the range of structure at non-mined sites, providing similar habitat for species found at unmined shrublands, plus more. All sites significantly differed in vegetative characteristics. Higher nest survival on mined sites may result from the higher vegetative heterogeneity there. The reclaimed site may have had higher nest survival due to lower rodent and corvid nest predator abundances. This research informs conservation efforts of the declining early-successional songbird guild and answers questions about the impacts of common energy extraction practices on these species. Blue-winged Warblers select conditions of later succession for nesting, which demonstrates that the early-successional sere should not be treated as a homogeneous management unit which spans only a few years after disturbance, but maintained over a range of ages on the landscape. Unconventional gas development in an already-fragmented landscape context may not degrade shrubland songbird habitat as much as it does interior forests, but does impact nest success and results in the displacement of large amounts of habitat. Former surface mines provide productive, lasting habitats for breeding shrubland songbirds that accommodate the early-successional songbird guild comparably to unmined shrublands. Shrubland songbirds can coexist with the ever-expanding extraction of fossil fuels from Appalachia if their habitat requirements are met. These species rely upon ephemeral conditions, and the key to retaining them remains management of the landscape in a dynamic fashion to provide ample habitat

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

This is the publisher’s final pdf. The published article is copyrighted by the Public Library of Science and can be found at: http://www.plosone.org/home.action.Background: Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. \ud \ud Methodology and Principal Findings: A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. \ud \ud Conclusion and Significance: Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level

Avian assemblages and Red-eyed Vireo nest survival within mineland forest

Since the passage of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, mined lands have generally been reclaimed to an environment characterized by severely compacted minesoils, a growth medium comprised largely of unweathered materials, and a predominance of aggressive groundcovers that inhibit native species colonization. Under these conditions, succession is arrested. Within landscapes that are fragmented by traditionally reclaimed surface mines, forest patches are smaller and forest cover on the landscape scale is reduced. As a result, forest songbirds that require large, continuous blocks of forest are negatively affected.;Some pre-SMCRA abandoned minelands contain areas of uncompacted minesoils on which hardwood forest has developed in the absence of aggressive groundcovers. Despite potential differences in tree species composition, study of the relationship between habitat structure and the avian assemblage within pre-SMCRA mineland forest could provide insight into the species assemblages that future mineland reforestation efforts might yield. Study of the reproductive success of forest songbirds within pre-SMCRA mineland forest may provide some indication as to whether this habitat is capable of sustaining breeding songbird populations. In chapter two of this thesis, I detail research in which my objectives were to: 1) examine patterns in avian assemblage structure within mineland and reference forest and to link the avian assemblage response to variables describing habitat structure and composition, and 2) contrast nest survival of Red-eyed Vireos (Vireo olivaceus) breeding within mineland and reference forest.;I conducted this research in 2011 within New River Gorge National River in southern West Virginia. I surveyed avian assemblages and sampled stand structure and composition along 28 fixed-width line transects (14 mined and 14 reference) established within four pre-SMCRA abandoned minelands and adjacent, unmined forest. Minelands within these study areas were relatively wide (80-100 m wide on average) and contained mature forest (60-65 years old) that had developed from areas of loose-dumped spoil mounded atop benches and also within outslopes.;Using an information-theoretic approach, I developed a priori models containing habitat and temporal covariates that I hypothesized to influence the nest survival of Red-eyed Vireos. Within the same study area, I monitored vireo nests within three mineland forest plots and three reference forest plots.;Ordination of avian assemblages using non-metric dimensional scaling (NMDS) showed clear discrimination between mineland and reference assemblages. Linear and surface fitting of habitat variables showed strong correlations between the ordination and groundcover gradients, but generally non-significant relationships for gradients describing forest structure. Mineland assemblages were associated with lower levels of litter cover and depth and also had lower abundance of Ovenbirds (Seiurus aurocapillus), a ground-nesting and foraging species. Within mineland assemblages, the absence of a consistent pattern of relationships among species suggested a wider habitat gradient relative to reference forest.;I monitored 45 Red-eyed Vireo nests, 21 within mineland forest and 24 within reference forest. Nest survival for Red-eyed Vireos was similar within mineland and reference forest and nest patch characteristics (overstory cover and vertical foliage density) had minimal effect on nest survival. Classification tree modeling using forest type as the response variable indicated that reference nest sites were characterized by greater vertical heterogeneity.;In chapter three, I report on research initiated with the objective of examining patterns in avian assemblage structure in response to the presence of two broad classes of minelands on the landscape, compacted bench minelands and loose-dumped bench minelands. This research was conducted in 2010 and indicated the approach taken in 2011 (chapter two). I conducted fieldwork within five study sites in New River Gorge National River and Plum Orchard Wildlife Management Area (WMA). Point count transects were classified as loose-dumped benches, unmined plateau, compacted benches, and unmined steep slope. NMDS ordination indicated that minelands with loose-dumped benches had minimal effect on assemblage structure. The assemblage associated with compacted bench minelands was not discrete, but was largely discriminated from the other assemblage types. Species that use the subcanopy and midcanopy for nesting and foraging were discriminating components of compacted bench assemblages. Relative abundance of the closed-canopy guild was lower within mined forest than within unmined forest.;In total, this research has shown that failure to establish mineland stands in which heavy-seeded species are a component has important implications for avian assemblage structure. Within minelands, heterogeneity in edaphic conditions and the corresponding variation in forest structure likely contributed to an inconsistent pattern in avian assemblage structure