Wayne E. Thogmartin

Predicting Regional Abundance of Rare Grassland Birds with a Hierarchical Spatial Count Model

Abstract Grassland birds are among the most imperiled groups of birds in North America. Unfortunately, little is known about the location of regional concentrations of these birds, thus regional or statewide conservation efforts may be inappropriately applied, reducing their effectiveness. We identified environmental covariates associated with the abundance of five grassland birds in the upper midwestern United States (Bobolink [Dolichonyx oryzivorus], Grasshopper Sparrow [Ammodramus savannarum], Henslows Sparrow [A. henslowii], Sedge Wren [Cistothorus platensis], and Upland Sandpiper [Bartramia longicauda]) with a hierarchical spatial count model fitted with Markov chain Monte Carlo methods. Markov chain Monte Carlo methods are well suited to this task because they are able to incorporate effects associated with autocorrelated counts and nuisance effects associated with years and observers, and the resulting models can be used to map predicted abundance at a landscape scale. Environmental covariates were derived from five suites of variables: landscape composition, landscape configuration, terrain heterogeneity and physiognomy, climate, and human influence. The final models largely conformed to our a priori expectations. Bobolinks and Henslows Sparrows were strongly sensitive to grassland patch area. All of the species except Henslows Sparrows exhibited substantial negative relations with forest composition, often at multiple spatial scales. Climate was found to be important for all species, and was the most important factor influencing abundance of Grasshopper Sparrows. After mapping predicted abundance, we found no obvious correspondence in the regional patterns of the five species. Thus, no clearly defined areas exist within the upper midwestern United States where management plans can be developed for a whole suite of grassland birds. Instead, a larger, region-wide initiative setting different goals for different species is recommended.

Scaling Local Species-habitat Relations to the Larger Landscape with a Hierarchical Spatial Count Model

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species.

Current and Future Land Use around a Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Services National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our “restricted-urban-growth” scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S.

Population-level impact of white-nose syndrome on the endangered Indiana bat

Abstract Establishing status and trend for an endangered species is critical to recovery, especially when it is faced with a nascent extinction agent. We calculated, with hierarchical log-linear change-point models, hibernaculum-level population trends between 1983 and 2009 for the endangered Indiana bat (Myotis sodalis) now subjected to the fast-spreading fungal disease white-nose syndrome. We combined trends from 222 wintering populations before and after onset of the disease to determine trend for clusters of interacting wintering populations, recovery units, and the species. Before onset of the disease, a west-to-east gradient in trends existed, with westernmost populations declining and easternmost populations increasing in abundance. The species as a whole, however, was stationary between 1983 and 2005 (−0.5% mean annual change; 95% confidence interval [CI] = −2.8, +1.8%). Estimated mean population size in 2009 was 377,124 bats (195,398–957,348), with large variance apparently caused by white-nose syndrome. With the onset of white-nose syndrome (2006–2009), the species exhibited a 10.3% annual decline (95% CI = −21.1, +2.0%). White-nose syndrome is having an appreciable influence on the status and trends of Indiana bat populations, stalling and in some cases reversing population gains made in recent years.

A cautionary tale regarding use of the National Land Cover Dataset 1992

Abstract Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grassland-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.

Landscape attributes and nest-site selection in Wild Turkeys

Rates of nesting participation, renesting, and nesting success for Wild Tur- keys (Meleagris gallopavo) in the Ouachita Mountains, Arkansas, are among the lowest re- corded in the eastern United States. I studied spatial attributes of 113 Wild Turkey nests to determine landscape-scale habitat characteristics that were important for nest placement and survival. Hens generally nested close to roads in large pine patches that occurred on southeast-facing slopes. Hens selected shortleaf pine (Pinus echinata; 68.1%) over mixed hard- wood (23.9%), hardwood (0.9%), and open areas (7.1%). Most of the hens (57.5%) placed their nests in edge habitat, but placement in these areas did not influence nesting success. Rather, female turkeys appeared to respond to a high risk of predation by placing nests in large patches, away from areas of high edge density favored by nest predators. Mean patch size chosen by nesting females (6,912.6 + SE of 634.5 ha) was considerably larger than the mean patch size for the study area (31.4 + 7.8 ha). Although most hens nested close to roads, this association appeared to be detrimental to nesting success because all nests close to roads were unsuccessful. In general, habitat characteristics examined at the level of patch and stand were good predictors of nest location but poor predictors of nesting success, possibly due to a high abundance of edge habitat in the landscape. This large amount of edge apparently sustained predator populations that made even the largest patches hazardous for nesting by Wild Turkeys. Therefore, the lack of suitable nest sites may limit population size of Wild Turkeys in the Ouachita Mountains. Received 10 July 1998, accepted 25 January 1999.

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.

Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies ( Danaus plexippus )

The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.

Home-range Size and Habitat Selection of Female Wild Turkeys (Meleagris gallopavo) in Arkansas

Abstract Eastern wild turkeys (Meleagris gallopavo silvestris) in the Ouachita Highland Province of westcentral Arkansas have some of the largest reported home ranges for this subspecies. Previous research on wild turkeys has generally attributed large home-range size to forage abundance or quality. However, limitations in reproduction by wild turkeys in the Ouachitas may influence home-range size and habitat selection. To discern factors governing home-range size, I examined habitat use by 54 female wild turkeys from 1993 to 1996. Shortleaf pine (Pinus echinata) and mixed pine–hardwood sawtimber were selected over other overstory cover types, whereas blackgum (Nyssa sylvatica), red maple (Acer rubrum) and white oak (Quercus alba) were favored in the understory. Mean fixed kernel home-range size during the breeding season was 18.9 km2, the largest reproductive period home range reported for the eastern subspecies. Home-range size varied as a function of age, body mass, reproductive status and the structure of selected habitats. Subadult females occupied larger home ranges (x̄ = 32.0 km2, se = 7.0) than adult females (16.3 ± 1.7 km2) and moved greater distances between nest sites in subsequent years (8.9 ± 1.8 km vs. 2.4 ± 1.1 km, respectively). After removing effects of age, heavier females occupied smaller home ranges than lighter females. Nesting individuals occupied less area than non-nesters, and female turkeys that occupied smaller areas avoided stands of seedlings and saplings in favor of mature poletimber. Taken together, effects of physiological condition and experience influenced home-range size in female wild turkeys in westcentral Arkansas.

Spring plant phenology and false springs in the conterminous US during the 21st century

The onset of spring plant growth has shifted earlier in the year over the past several decades due to rising global temperatures. Earlier spring onset may cause phenological mismatches between the availability of plant resources and dependent animals, and potentially lead to more false springs, when subsequent freezing temperatures damage new plant growth. We used the extended spring indices to project changes in spring onset, defined by leaf out and by first bloom, and predicted false springs until 2100 in the conterminous United States (US) using statistically-downscaled climate projections from the Coupled Model Intercomparison Project 5 ensemble. Averaged over our study region, the median shift in spring onset was 23 days earlier in the Representative Concentration Pathway 8.5 scenario with particularly large shifts in the Western US and the Great Plains. Spatial variation in phenology was due to the influence of short-term temperature changes around the time of spring onset versus season-long accumulation of warm temperatures. False spring risk increased in the Great Plains and portions of the Midwest, but remained constant or decreased elsewhere. We conclude that global climate change may have complex and spatially variable effects on spring onset and false springs, making local predictions of change difficult.