Revisiting the Landscape Mosaic model.

The landscape mosaic model quantifies and maps the spatial juxtaposition of different land uses. It provides a landscape perspective of anthropic threats posed by agriculture and urban development, and the spatial-temporal shifting of the landscape mosaic indicates landscapes where anthropic intensity has changed. We use the U.S. Geological Survey provided National Land Cover Database (NLCD) for the years 2001 and 2021 to derive the landscape mosaic at five analysis scales. To improve earlier implementations of the model, we introduce the heatmap, a flexible scheme providing more thematic reporting opportunities and allowing for better quantitative summary reporting across analysis scales as well as for temporal trends. The results are exemplified at regional scale for the Atlanta metropolitan area. We use the improved model to investigate the land cover context over time and at different analysis scales and show how custom color tables detail different thematic features of the landscape mosaic, including the degree and change of anthropic intensity. We conclude with a discussion of potential applications in ecology, landscape planning, and restoration to illustrate the benefits of the revised landscape mosaic model. All assessment tools are now available in open-source software packages.

Mapping landscape ecological patterns using numeric and categorical maps.

The reciprocal relationships between ecological process and landscape pattern are fundamental to landscape ecology. Landscape ecologists traditionally use raster maps portraying classified features such as land use or land cover categories, and metrics suggested by the patch-corridor-matrix conceptual model of pattern. Less attention has been given to the landscape gradient conceptual model and raster maps portraying numeric features such as greenness or percent vegetation cover. We introduce the open-source tool GraySpatCon to calculate and map a variety of landscape pattern metrics from both conceptual models using either categorical or numeric maps. The 51 metrics, drawn mostly from the landscape ecology and image processing literatures, are calculated from the frequencies of input pixel values and/or the pixel value adjacencies in an analysis region. GraySpatCon conducts either a moving window analysis which produces a continuous map of a pattern metric, or a global analysis which produces a single metric value. We describe an implementation in the GuidosToolbox desktop application which allows novice users to interactively explore GraySpatCon functionality. In the R desktop environment, we demonstrate several metrics using an example map of percent tree cover and illustrate a multi-scale moving window analysis to identify scale domains. Comparisons of computational efficiency indicate a substantial GraySpatCon advantage over related software in the R environment.

Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns.

Future land use projections are needed to inform long-term planning and policy. However, most projections require downscaling into spatially explicit projection rasters for ecosystem service analyses. Empirical demand-allocation algorithms input coarse-level transition quotas and convert cells across the raster, based on a modeled probability surface. Such algorithms typically employ contagious and/or random allocation approaches. We present a hybrid seeding approach designed to generate a stochastic collection of spatial realizations for distributional analysis, by 1) randomly selecting a seed cell from a sample of n cells, then 2) converting patches of neighboring cells based on transition probability and distance to the seed. We generated a collection of realizations from 2001-2011 for the conterminous USA at 90m resolution based on varying the value of n, then computed forest area by fragmentation class and compared the results with observed 2011 forest area by fragmentation class. We found that realizations based on values of n ≤ 256 generally covered observed forest fragmentation at regional scales, for approximately 70% of assessed cases. We also demonstrate the potential of the seeding algorithm for distributional analysis by generating 20 trajectories of realizations from 2020-2070 from a single example scenario. Generating a library of such trajectories from across multiple scenarios will enable analysis of projected patterns and downstream ecosystem services, as well as their variation.

Conterminous United States land cover change patterns 2001-2016 from the 2016 National Land Cover Database.

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001 to 2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error (SE) was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001 and 2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this period. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001-2006 at twice the rate of 2011-2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database.

Determining the size of a complete disturbance landscape: multi-scale, continental analysis of forest change.

The scale of investigation for disturbance-influenced processes plays a critical role in theoretical assumptions about stability, variance, and equilibrium, as well as conservation reserve and long-term monitoring program design. Critical consideration of scale is required for robust planning designs, especially when anticipating future disturbances whose exact locations are unknown. This research quantified disturbance proportion and pattern (as contagion) at multiple scales across North America. This pattern of scale-associated variability can guide selection of study and management extents, for example, to minimize variance (measured as standard deviation) between any landscapes within an ecoregion. We identified the proportion and pattern of forest disturbance (30 m grain size) across multiple landscape extents up to 180 km2. We explored the variance in proportion of disturbed area and the pattern of that disturbance between landscapes (within an ecoregion) as a function of the landscape extent. In many ecoregions, variance between landscapes within an ecoregion was minimal at broad landscape extents (low standard deviation). Gap-dominated regions showed the least variance, while fire-dominated showed the largest. Intensively managed ecoregions displayed unique patterns. A majority of the ecoregions showed low variance between landscapes at some scale, indicating an appropriate extent for incorporating natural regimes and unknown future disturbances was identified. The quantification of the scales of disturbance at the ecoregion level provides guidance for individuals interested in anticipating future disturbances which will occur in unknown spatial locations. Information on the extents required to incorporate disturbance patterns into planning is crucial for that process.

An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context.

Landscape context is an important factor in restoration ecology, but the use of landscape context for site prioritization has not been as fully developed. We used morphological image processing to identify candidate ecological restoration areas based on their proximity to existing natural vegetation. We identified 1,102,720 candidate ecological restoration areas across the continental United States. Candidate ecological restoration areas were concentrated in the Great Plains and eastern United States. We populated the database of candidate ecological restoration areas with 17 attributes related to site content and context, including factors such as soil fertility and roads (site content), and number and area of potentially conjoined vegetated regions (site context) to facilitate its use for site prioritization. We demonstrate the utility of the database in the state of North Carolina, U.S.A. for a restoration objective related to restoration of water quality (mandated by the U.S. Clean Water Act), wetlands, and forest. The database will be made publicly available on the U.S. Environmental Protection Agency's EnviroAtlas website (http://enviroatlas.epa.gov) for stakeholders interested in ecological restoration.

Towards the planning and design of disturbance patterns across scales to counter biological invasions.

The way in which disturbances from human land use are patterned in space across scales can have important consequences for efforts to govern human/environment with regard to, but not only, invasive spread-dispersal processes. In this context, we explore the potential of disturbance patterns along a continuum of scales as proxies for identifying the geographical regions prone to spread of invasive plant species. To this end, we build on a previous framework of cross-scale disturbance patterns, exercising the approach for the Apulia region (South Italy). We first review procedures and results introducing disturbance maps and sliding windows to measure composition (amount) and configuration (contagion) of disturbance patterns both for real and simulated landscapes from random, multifractal and hierarchical neutral models. We introduce cross-scale disturbance profiles obtained by clustering locations from real and simulated landscapes, which are used as foils for comparison to the real landscapes on the same pattern transition space. Critical percolation thresholds derived from landscape observations and theoretical works are discussed in order to identify critical scale domains. With reference to the actual land use and invasive alien flora correlates of disturbance patterns, a cross-scale "invasibility" map of the Apulia region is derived, which shows sub-regions and scale domains with different potentials for the invasive spread of undesirable species. We discuss the potential effect of contagious and non-contagious disturbances like climate change and why multifractal-like disturbance patterns might be more desirable than others to counter biological invasions in a multi-scale and multi-level context of adaptive planning, design and management of disturbance.

Decline of forest interior conditions in the conterminous United States.

Forest fragmentation threatens the sustainability of forest interior environments, thereby endangering subordinate ecological attributes and functions. We analyzed the spatial patterns of forest loss and gain for the conterminous United States from 2001 to 2006 to determine whether forest interior environments were maintained at five spatial scales. A 1.1% net loss of total forest area translated to net losses of 3.2% to 10.5% of forest interior area over spatial scales of 4.41 ha to 5,310 ha. At the 65.6-ha scale, the reduction of forest interior area was 50,000 km²--almost double the net loss of total forest area. The pervasive discrepancy between total forest loss and forest interior loss indicates a widespread shift of the extant forest to more fragmented conditions, even in regions exhibiting small net changes in extant forest area. In the conterminous United States, trends in total forest area underestimate threats to forest from forest fragmentation.

Global survey of anthropogenic neighborhood threats to conservation of grass-shrub and forest vegetation.

The conservation value of natural vegetation is degraded by proximity to anthropogenic land uses. Previous global assessments focused primarily on the amount of land protected or converted to anthropogenic uses, and on forest vegetation. Comparative assessments of extant vegetation in terms of proximity to anthropogenic land uses are needed to better inform conservation planning. We conducted a novel comparative survey of global forest and grass-shrub vegetation at risk of degradation owing to proximity of anthropogenic land uses. Using a global land cover map, risks were classified according to direct adjacency with anthropogenic land cover (adjacency risk), occurrence in anthropogenic neighborhoods (neighborhood risk), or either (combined risk). The survey results for adjacency risk and combined risk were summarized by ecoregions and biomes. Adjacency risk threatens 22 percent of global grass-shrub and 12 percent of forest vegetation, contributing to combined risk which threatens 31 percent of grass-shrub and 20 percent of forest vegetation. Of 743 ecoregions examined, adjacency risk threatens at least 50 percent of grass-shrub vegetation in 224 ecoregions compared to only 124 ecoregions for forest. The conservation threats posed by proximity to anthropogenic land cover are higher for grass-shrub vegetation than for forest vegetation.

Detecting temporal change in watershed nutrient yields.

Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.

Hot spots of perforated forest in the eastern United States.

National assessments of forest fragmentation satisfy international biodiversity conventions, but they do not identify specific places where ecological impacts are likely. In this article, we identify geographic concentrations (hot spots) of forest located near holes in otherwise intact forest canopies (perforated forest) in the eastern United States, and we describe the proximate causes in terms of the non-forest land-cover types contained in those hot spots. Perforated forest, defined as a 0.09-ha unit of forest that is located at the center of a 7.29-ha neighborhood containing 60-99% forest with relatively low connectivity, was mapped over the eastern United States by using land-cover maps with roads superimposed. Statistically significant (P < 0.001) hot spots of high perforation rate (perforated area per unit area of forest) were then located by using a spatial scan statistic. Hot spots were widely distributed and covered 20.4% of the total area of the 10 ecological provinces examined, but 50.1% of the total hot-spot area was concentrated in only two provinces. In the central part of the study area, more than 90% of the forest edge in hot spots was attributed to anthropogenic land-cover types, whereas in the northern and southern parts it was more often associated with semi-natural land cover such as herbaceous wetlands.

A preliminary assessment of the Montreal process indicators of air pollution for the United States.

Air pollutants pose a risk to forest health and vitality in the United States. Here we present the major findings from a national scale air pollution assessment that is part of the United States' 2003 Report on Sustainable Forests. We examine trends and the percent forest subjected to specific levels of ozone and wet deposition of sulfate, nitrate, and ammonium. Results are reported by Resource Planning Act (RPA) reporting region and integrated by forest type using multivariate clustering. Estimates of sulfate deposition for forested areas had decreasing trends (1994-2000) across RPA regions that were statistically significant for North and South RPA regions. Nitrate deposition rates were relatively constant for the 1994 to 2000 period, but the South RPA region had a statistically decreasing trend. The North and South RPA regions experienced the highest ammonium deposition rates and showed slightly decreasing trends. Ozone concentrations were highest in portions of the Pacific Coast RPA region and relatively high across much of the South RPA region. Both the South and Rocky Mountain RPA regions had an increasing trend in ozone exposure. Ozone-induced foliar injury to sensitive species was recorded in all regions except for the Rocky Mountain region. The multivariate analysis showed that the oak-hickory and loblolly-shortleaf pine forest types were generally exposed to more air pollution than other forest types, and the redwood, western white pine, and larch forest types were generally exposed to less. These findings offer a new approach to national air pollution assessments and are intended to help focus research and planning initiatives related to air pollution and forest health.

A preliminary assessment of Montréal process indicators of forest fragmentation for the United States.

As part of the U.S. 2003 National Report on Sustainable Forests, four metrics of forest fragmentation--patch size, edge amount, inter-patch distance, and patch contrast--were measured within 137744 non-overlapping 5625 ha analysis units on land-cover maps derived from satellite imagery for the 48 conterminous States. The perimeter of a typical forest patch is about 100 m from the perimeter of its nearest neighbor, except when there is not much forest, in which case that distance is 200 to 300 m. A typical analysis unit has from 10 to 40% as much forest edge as it could possibly have, given the amount of forest present. Most analysis units contain a large number of patches that are less than one hectare in size, and about 10% contain one or more 2000 to 5000 ha patches. Forest often defines the background landscape, and patch contrast is generally either very high or very low in eastern regions and intermediate in western regions. Many research needs were identified by this experimental analysis of available data and metrics.

Geographic analysis of forest health indicators using spatial scan statistics.

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.

Fuzzy decision analysis for integrated environmental vulnerability assessment of the mid-Atlantic Region.

A fuzzy decision analysis method for integrating ecological indicators was developed. This was a combination of a fuzzy ranking method and the analytic hierarchy process (AHP). The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic region, we were able to point out areas that were in relatively poor condition and/or vulnerable to future deterioration. The method offered an easy and comprehensive way to combine the strengths of fuzzy set theory and the AHP for ecological assessment. Furthermore, the suggested method can serve as a building block for the evaluation of environmental policies.