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Context: Forest type (FT) classification provides useful information to ecologists and forest managers by representing similar sites based on species dominance. Various methods have been developed using stand-level or plot-level information, however, these classifications are not always effective at representing broader landscape patterns of species diversity. Objectives: We classified landscape-level FTs from species habitat models and compared against classifications intended for stand-level information. We used a departure score to assess potential changes to current FT from projected changes in climate and habitat suitability (HS). Methods: We applied a text mining algorithm, latent Dirichlet allocation (LDA), to 125 species HS models within the eastern United States to define 11 FTs under current conditions. We compared the LDA model against two summations of relative abundance. We then developed a departure score to characterize potential changes to current FTs under projected climate change. Results: The LDA model showed broad spatial agreement with summations of species relative abundance. However, LDA's landscape-level dominance of species differed from stand-level classifications of species summations. Varying degrees of pressure from climate change and HS indicated that future FTs could face conditions that result in departures. However, the overall departure scores tended to be lower due to reduced pressure from modeled changes in HS for much of the eastern US. Conclusions: LDA results are promising for classifying landscape-level FTs. Portraying potential changes in future FTs with departure scores may facilitate better management by aligning the spatial scales of information and not attributing changes to specific species or conditions. [ABSTRACT FROM AUTHOR]

Highlights • Herbicide followed by fire was effective in killing Ailanthus saplings and trees. • Immediately after fire, Ailanthus germinant numbers increased dramatically. • Four years post-fire, germinants and small seedlings did not persist. • A single prescribed fire does not appear to facilitate the spread of Ailanthus. Abstract Ailanthus altissima ((Mill.) Swingle, tree-of-heaven, Chinese sumac, stink tree) is a nonnative invasive tree that is common throughout much of the eastern United States. It can invade and expand dramatically when forests are disturbed. Anecdotal evidence suggests that fire might facilitate its spread, but the relationship between fire and this prolific invasive tree is poorly understood. To better understand the impacts of fire on Ailanthus , we conducted a study at Tar Hollow State Forest in southeastern Ohio, USA where Ailanthus is widely distributed. Our objective was to quantify the direct effects of prescribed fire on the demography of Ailanthus populations, with and without the pre-burn application of the stem-injected herbicide, imazapyr. We quantified demographic attributes (survival, density, and sprouting) of Ailanthus germinants, seedlings, saplings, and trees in a field experiment with four treatment combinations: (1) no fire and no herbicide, (2) herbicide, (3) fire, and (4) herbicide plus fire. Ailanthus stems >3 cm dbh were stem-injected with the herbicide, imazapyr in late summer to early fall followed by prescribed fire in April. We determined that herbicide plus prescribed burn treatment was highly effective in killing large saplings and trees, with no resprouting evident after four growing seasons. In the season immediately after the burn with and without herbicide treatment, small Ailanthus sapling and seedling abundance increased, but did not persist. Over time, Ailanthus germinants and sprouts from top-killed stems were poor competitors with faster-growing post-fire woody regeneration as forest floor shading increased. In addition, the late growing season application of imazapyr was highly effective in killing Ailanthus and subsequent sprouts. This study, the first to quantify the direct effects of fire on Ailanthus , demonstrates that prescribed fire alone does not appear to facilitate the spread of Ailanthus. [ABSTRACT FROM AUTHOR]

We synthesize insights from current understanding of drought impacts at stand-to-biogeographic scales, including management options, and we identify challenges to be addressed with new research. Large stand-level shifts underway in western forests already are showing the importance of interactions involving drought, insects, and fire. Diebacks, changes in composition and structure, and shifting range limits are widely observed. In the eastern US, the effects of increasing drought are becoming better understood at the level of individual trees, but this knowledge cannot yet be confidently translated to predictions of changing structure and diversity of forest stands. While eastern forests have not experienced the types of changes seen in western forests in recent decades, they too are vulnerable to drought and could experience significant changes with increased severity, frequency, or duration in drought. Throughout the continental United States, the combination of projected large climate-induced shifts in suitable habitat from modeling studies and limited potential for the rapid migration of tree populations suggests that changing tree and forest biogeography could substantially lag habitat shifts already underway. Forest management practices can partially ameliorate drought impacts through reductions in stand density, selection of drought-tolerant species and genotypes, artificial regeneration, and the development of multistructured stands. However, silvicultural treatments also could exacerbate drought impacts unless implemented with careful attention to site and stand characteristics. Gaps in our understanding should motivate new research on the effects of interactions involving climate and other species at the stand scale and how interactions and multiple responses are represented in models. This assessment indicates that, without a stronger empirical basis for drought impacts at the stand scale, more complex models may provide limited guidance. [ABSTRACT FROM AUTHOR]

The degree to which tree species will shift in response to climate change is uncertain yet critical to understand for assessing ecosystem vulnerability. We analyze results from recent studies that model potential tree species habitat across the eastern United States during the coming century. Our goals were to quantify and spatially analyze habitat projections and their congruence under multiple climate scenarios and to assess the implications of habitat change for forest vulnerability and adaptation to climate change in and around protected areas. We assessed habitat projections of species habitat extent and forest composition for 35 tree species under climate change from 2000 to 2100 within National Park Service management units in the Appalachian Landscape Conservation Cooperative (ALCC), spanning an approximately 1,500 km latitudinal gradient. Our results show that forest composition and species ranges could change substantially under all greenhouse gas emissions scenarios and that model correspondence was stronger for projections of habitat declines than increases. Model correspondence generally increased at finer spatial scales, but varied by tree species and focal area. In the ALCC, forest composition was projected to change the most in protected area centered ecosystems (PACEs). Northeastern PACEs were projected to be suitable for tree species currently in southeastern PACEs, suggesting that intermediate suitable habitat regions could promote tree species persistence and mitigate the impacts of climate change on eastern forests. These results suggest that climate-specific management of eastern U.S. forest ecosystems will be critical but challenging, requiring integrated assessment and management of PACEs and protected areas as well as higher-resolution monitoring and modeling to inform spatially explicit management decisions within eastern U.S. parks. [ABSTRACT FROM AUTHOR]

Forests provide key ecosystem services (ES) and the extent to which the ES are realized varies spatially, with forest composition and cultural context, and in breadth, depending on the dominant tree species inhabiting an area. We address the question of how climate change may impact ES within the temperate and diverse forests of the eastern United States. We quantify the vulnerability to changes in forest habitat by 2100, based on the overall pressures of community change from an aggregation of current and potential future habitats for 134 tree species at each of 149 US Department of Defense installations. To do so, we derive an index, Forest-Related Index of Climate Vulnerability, composed of several indicators of vulnerability for each site. Further, a risk matrix (likelihood × consequences) provides a visual cue to compare vulnerabilities among species (example from Pennsylvania) or among sites [example for Acer saccharum (sugar maple) in Vermont vs. Kentucky]. Potential changes in specific ES can then be qualitatively examined. For example in Pennsylvania, the loss of the provisioning services (wood products) of Prunus serotina (black cherry) and Fraxinus americana (white ash) habitat projected for the future will not likely be compensated for by concomitant increases in Juniperus virginiana (redcedar) and Pinus echinata (shortleaf pine) habitat. Taken together, this approach provides a conceptual framework that allows for consideration of how potential changes in tree species habitats, as impacted by climate change, can be combined to explore relative changes in important ES that forests provide. [ABSTRACT FROM AUTHOR]

The author reflects on the secular perspectives on the landscape ecology research in the U.S. from the U.S. Chapter of the International Association of Landscape Ecology (US-IALE) annual meeting. The author states he and his colleagues classified every oral presentation from the abstract books prepared for each meeting. He adds that they categorized posters and talks according to 17 nonmutually exclusive categories which include climate change, fragmentation, and natural resource management.

We present an approach to assess and compare risk from climate change among multiple species through a risk matrix, in which managers can quickly prioritize for species that need to have strategies developed, evaluated further, or watched. We base the matrix upon earlier work towards the National Climate Assessment for potential damage to infrastructures from climate change. Risk is defined here as the product of the likelihood of an event occurring and the consequences or impact of that event. In the context of species habitats, the likelihood component is related to the potential changes in suitable habitat modeled at various times during this century. Consequences are related to the adaptability of the species to cope with the changes, especially the increasing intensity and/or frequency of disturbance events that are projected. We derived consequence scores from nine biological and 12 disturbance characteristics that were pulled from literature for each species. All data were generated from an atlas of climate change for 134 trees of the eastern United States (). We show examples which depict a wide range of risk for tree species of northern Wisconsin, including species that may gain substantial habitat as well as lose substantial habitat, both of which will require the development of strategies to help the ecosystems adapt to such changes. [ABSTRACT FROM AUTHOR]

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134 tree and 147 bird species. We produced lists of species for which suitable habitat tends to increase, decrease, or stay the same for any region. Independent assessments of trends of large trees versus seedlings across the eastern U.S. show that 37 of 40 species in common under both studies are currently trending as modeled. We developed a framework, ModFacs, in which we used the literature to assign default modification factor scores for species characteristics that cannot be readily assessed in such models, including 12 disturbance factors (for example, drought, fire, insect pests), nine biological factors (for example, dispersal, shade tolerance), and assessment scores of novel climates, long-distance extrapolations, and output variability by climate model and emission scenario. We also used a spatially explicit cellular model, SHIFT, to calculate colonization potentials for some species, based on their abundance, historic dispersal distances, and the fragmented nature of the landscape. By combining results from the three efforts, we can create projections of potential climate change impacts over the next 100 years or so. Here we emphasize some of the lessons we have learned over 16 years in hopes that they may help guide future experiments, modeling efforts, and management. [ABSTRACT FROM AUTHOR]

The article focuses on the development of two atlases of 134 trees and 147 bird species in the U.S. It outlines the purpose of the atlases which aim to provide distributional, ecological and biological information of the species, and to help managers and restoration ecologists get clear vision on their restoration efforts. It mentions the use of the Forest Service's Forest Inventory Analysis (FIA) and data from the Breeding Bird Survey (BBS) to derive relative abundances of the species.

We evaluated 134 tree species from the eastern United States for potential response to several scenarios of climate change, and summarized those responses for nine northeastern United States. We modeled and mapped each species individually and show current and potential future distributions for two emission scenarios (A1fi [higher emission] and B1 [lower emission]) and three climate models: the Parallel Climate, the Hadley CM3, and the Geophysical Fluid Dynamics Laboratory model. Climate change could have large impacts on suitable habitat for tree species in this region, especially under a high emissions trajectory. Results indicate that while species with potentially increasing areas of suitable habitat in the Northeastern US substantially outnumber those with decreasing areas of habitat, there are key species that show diminishing habitat area: balsam fir (Abies balsamea), paper birch (Betula papyrifera), red spruce (Picea rubens), bigtooth and quaking aspen (Populus grandidentata and P. tremuloides), and black cherry (Prunus serotina). From these results we identified the top 10 losers and gainers for each US state in the region by scenario and emissions trajectory. By combining individual species importance maps and developing assembly rules for various classes, we created maps of potential forest types for the Northeast showing a general loss of the spruce-fir zone with advancing oak-hickory type. Further data, maps, and analysis can be found at http://www.nrs.fs.fed.us/atlas. [ABSTRACT FROM AUTHOR]

The task of modeling the distribution of a large number of tree species under future climate scenarios presents unique challenges. First, the model must be robust enough to handle climate data outside the current range without producing unacceptable instability in the output. In addition, the technique should have automatic search mechanisms built in to select the most appropriate values for input model parameters for each species so that minimal effort is required when these parameters are fine-tuned for individual tree species. We evaluated four statistical models—Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)—for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model. To test, we applied these techniques to four tree species common in the eastern United States: loblolly pine ( Pinus taeda), sugar maple ( Acer saccharum), American beech ( Fagus grandifolia), and white oak ( Quercus alba). When the four techniques were assessed with Kappa and fuzzy Kappa statistics, RF and BT were superior in reproducing current importance value (a measure of basal area in addition to abundance) distributions for the four tree species, as derived from approximately 100,000 USDA Forest Service’s Forest Inventory and Analysis plots. Future estimates of suitable habitat after climate change were visually more reasonable with BT and RF, with slightly better performance by RF as assessed by Kappa statistics, correlation estimates, and spatial distribution of importance values. Although RTA did not perform as well as BT and RF, it provided interpretive models for species whose distributions were captured well by our current set of predictors. MARS was adequate for predicting current distributions but unacceptable for future climate. We consider RTA, BT, and RF modeling approaches, especially when used together to take advantage of their individual strengths, to be robust for predictive mapping and recommend their inclusion in the ecological toolbox. [ABSTRACT FROM AUTHOR]

Aim We describe and use a model, SHIFT, to estimate potential migration due to climate change over the next 100 years. Location Eastern United States. Methods Five species, currently confined to the eastern half of the United States and not extending into Canada, were used to assess migration potential: Diospyros virginiana (persimmon), Liquidambar styraciflua (sweetgum), Oxydendrum arhoreum (sourwood), Pinus taeda (loblolly pine), and Quercus falcata var. falcata (southern red oak). SHIFT is a matrix simulation model using simple inverse power functions to provide a distance decay of seed dispersal and is driven primarily by the abundance of the species near the boundary, the forest density within and beyond the boundary, and the distance between cells. For each cell outside the current boundary, the model creates an estimate of the probability that each unoccupied cell will become colonized over a period of 100 years. SHIFT is a `fat-tailed' migration model that allows rare very long distance dispersal events and colonization could occur up to 500 km beyond the current distribution boundary. Model outputs were analysed using transects through sections showing relatively low and high colonization probabilities as a result of low and high densities of target trees (high source strength) as well as high densities of forest (high sink strength). We also assess migration potential for species by concentric rings around the current boundary. Results Model outputs show the generally limited nature of migration for all five species over 100 years. There is a relatively high probability of colonization within a zone of 10-20 km (depending on habitat quality and species abundance) from the current boundary, but a small probability of colonization where the distance from the current boundary exceeds about 20 km. Whether biologically plausible or not, rare very long distance migration events are not sufficient to rescue migration. Species abundance (the source strength of migration) near the range boundary carried relatively more influence than percentage forest cover (sink strength) in determining migration rates. Main conclusion The transect evaluation revealed the importance of abundance of the species near the boundary, indicating that rare species may have much more difficulty in unassisted northward migration due to climate change. The concentric rings analysis of the model outputs showed that only the first 10-20 km of area would have a reasonably high probability of colonization. Rare, long-distance events permit colonization of remote outliers, but much more needs to be understood about the likelihood of these rare events to predict the frequency of outlier establishment. [ABSTRACT FROM AUTHOR]

We modeled and combined outputs for 125 tree species for the eastern United States, using habitat suitability and colonization potential models along with an evaluation of adaptation traits. These outputs allowed, for the first time, the compilation of tree species' current and future potential for each unit of 55 national forests and grasslands and 469 1 × 1 degree grids across the eastern United States. A habitat suitability model, a migration simulation model, and an assessment based on biological and disturbance factors were used with United States Forest Service Forest Inventory and Analysis data to evaluate species potential to migrate or infill naturally into suitable habitats over the next 100 years. We describe a suite of variables, by species, for each unique geographic unit, packaged as summary tables describing current abundance, potential future change in suitable habitat, adaptability, and capability to cope with the changing climate, and colonization likelihood over 100 years. This resulting synthesis and summation effort, culminating over two decades of work, provides a detailed data set that incorporates habitat quality, land cover, and dispersal potential, spatially constrained, for nearly all the tree species of the eastern United States. These tables and maps provide an estimate of potential species trends out 100 years, intended to deliver managers and publics with practical tools to reduce the vast set of decisions before them as they proactively manage tree species in the face of climate change. [ABSTRACT FROM AUTHOR]

Wildfires are a serious threat for land managers and property owners, and over the last few decades this threat has expanded as a result of increased rural development. Most wildfires in the north-eastern US occur in the wildland-urban interface, those regions of intermingling urban and non-developed vegetated lands, where access to firefighting resources can be limited. We created monthly wildfire ignition probability maps from environmental predictors and wildfires occurring between 2000 and 2009 for the states of New Jersey, Ohio and Pennsylvania. Predictor variables included a drought index, long-term soil moisture, percentage forest and wildland-urban interface classifications. Probability maps generated from modelled (Maxent) extrapolations were used to create monthly hazard maps to aid agencies and managers with resource allocation and likelihood projections of wildfires across the region. Our results suggest that monthly hazard assessments provide a better indication of potential wildfires than does a single mean annual probability. Our monthly predictions retain information related to long-term seasonal variability associated with environmental variables and the recorded wildfires providing spatial and temporal information for resource allocation. We modelled the distribution of wildfire ignitions across three eastern states (New Jersey, Ohio and Pennsylvania) for a 12-month period using maximum entropy. Models were parameterised with four integrated landscape variables and observed wildfires between 2000 and 2009 were used to predict the probability of fire occurrence. Monthly models performed better than a 12-month average of ignition probabilities. [ABSTRACT FROM AUTHOR]

Urban forests and herbaceous open space play a vital role in the environmental and aesthetic 'health' of cities, yet they are rarely identified in land-use inventories of urban areas. To provide informationon urban forests and other vegetative land cover in Illinois cities,Landsat Thematic Mapper (TM) data from June 27, 1988, were classified for the Chicago metropolitan region (9,717 km2). Ten land-cover classes were identified, including two types of forestland (occupying 5.8% of the total area), residential land with trees (14.6%)or without trees (7.8%), cropland (37.5%), two types of grassland (7.7%), urban with impervious surfaces (23.1%), water (1.6%), and miscellaneous vegetation (2.1%). Correlation analyses indicated that household income and household density are strongly related to land coversin the region, particularly those with tree cover and urbanized land. Population changes for 1980-1985 and 1985-2010 (projected) show a pattern of increasing density in the urbanized zone concurrent with continued urban sprawl, primarily into current cropland. [ABSTRACT FROM AUTHOR]