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Mountain social‐ecological systems (MtSES) are vital to humanity, providing ecosystem services to over half the planet's human population. Despite their importance, there has been no global assessment of threats to MtSES, even as they face unprecedented challenges to their sustainability. With survey data from 57 MtSES sites worldwide, we test a conceptual model of the types and scales of stressors and ecosystem services in MtSES and explore their distinct configurations according to their primary economic orientation and land use. We find that MtSES worldwide are experiencing both gradual and abrupt climatic, economic, and governance changes, with policies made by outsiders as the most ubiquitous challenge. Mountains that support primarily subsistence‐oriented livelihoods, especially agropastoral systems, deliver abundant services but are also most at risk. Moreover, transitions from subsistence‐ to market‐oriented economies are often accompanied by increased physical connectedness, reduced diversity of cross‐scale ecosystem services, lowered importance of local knowledge, and shifting vulnerabilities to threats. Addressing the complex challenges facing MtSES and catalyzing transformations to MtSES sustainability will require cross‐scale partnerships among researchers, stakeholders, and decision makers to jointly identify desired futures and adaptation pathways, assess trade‐offs in prioritizing ecosystem services, and share best practices for sustainability. These transdisciplinary approaches will allow local stakeholders, researchers, and practitioners to jointly address MtSES knowledge gaps while simultaneously focusing on critical issues of poverty and food security. ISSN:2328-4277

The devastating 2015 earthquakes in Nepal highlighted the need for effective disaster risk reduction (DRR) in mountains, which are inherently subject to hazards and increasingly vulnerable to extreme events. As multiple UN policy frameworks stress, DRR is crucial to mitigate the mounting environmental and socioeconomic costs of disasters globally. However, specialized DRR guidelines are needed for biodiverse, multi-hazard regions like mountains. Ecosystem-based disaster risk reduction (Eco-DRR) emphasizes ecosystem conservation, restoration, and sustainable management as key elements for DRR. We propose that integrating the emerging field of Eco-DRR with community-based DRR (CB-DRR) will help address the increasing vulnerabilities of mountain people and ecosystems. Drawing on a global mountain synthesis, we present paradoxes that create challenges for DRR in mountains and examine these paradoxes through examples from the 2015 Nepal earthquakes. We propose four principles for integrated CB- and Eco-DRR that address these challenges: (1) governance and institutional arrangements that fit local needs; (2) empowerment and capacity-building to strengthen community resilience; (3) discovery and sharing of constructive practices that combine local and scientific knowledge; and (4) approaches focused on well-being and equity. We illustrate the reinforcing relationship between integrated CB- and Eco-DRR principles with examples from other mountain systems worldwide. Coordinated community and ecosystem-based actions offer a potential path to achieve DRR, climate adaptation, sustainable development, and biodiversity conservation for vulnerable ecosystems and communities worldwide.

The International Long Term Ecological Research (ILTER) network can coordinate ecological research to provide observations of the ecosystem changes, and their socio-economic impacts on human societies at different scales. In this paper we demonstrate the importance of the ILTER network in the study and monitoring of environmental changes at a global level. We give examples of how biodiversity and ecosystem service data can be used to study impacts and adaptation options in response to climate change. Analysis of the 107 recent publications from LTER networks representing 21 countries show that LTER studies are often local and heterogeneous. There are some ecosystem types, such as agricultural or coastal ecosystems that are not covered with current ILTER network. Standardized monitoring schemes and techniques should be considered for future steering of ILTER collaboration. Integrating and synthesizing the collected data should be prioritized for future cooperation, and integrated in decision-making.

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fire-prone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS.

The International Long-Term Ecological Research (ILTER) network comprises > 600 scientific groups conducting site-based research within 40 countries. Its mission includes improving the understanding of global ecosystems and informs solutions to current and future environmental problems at the global scales. The ILTER network covers a wide range of social-ecological conditions and is aligned with the Programme on Ecosystem Change and Society (PECS) goals and approach. Our aim is to examine and develop the conceptual basis for proposed collaboration between ILTER and PECS. We describe how a coordinated effort of several contrasting LTER site-based research groups contributes to the understanding of how policies and technologies drive either toward or away from the sustainable delivery of ecosystem services. This effort is based on three tenets: transdisciplinary research; cross-scale interactions and subsequent dynamics; and an ecological stewardship orientation. The overarching goal is to design management practices taking into account trade-offs between using and conserving ecosystems toward more sustainable solutions. To that end, we propose a conceptual approach linking ecosystem integrity, ecosystem services, and stakeholder well-being, and as a way to analyze trade-offs among ecosystem services inherent in diverse management options. We also outline our methodological approach that includes: (i) monitoring and synthesis activities following spatial and temporal trends and changes on each site and by documenting cross-scale interactions; (ii) developing analytical tools for integration; (iii) promoting trans-site comparison; and (iv) developing conceptual tools to design adequate policies and management interventions to deal with trade-offs. Finally, we highlight the heterogeneity in the social-ecological setting encountered in a subset of 15 ILTER sites. These study cases are diverse enough to provide a broad cross-section of contrasting ecosystems with different policy and management drivers of ecosystem conversion; distinct trends of biodiversity change; different stakeholders' preferences for ecosystem services; and diverse components of well-being issues.

1 Ecologist, Plymouth State University, Center for the Environment, Russell House, Plymouth, NH 03264, USA 2 Ecologist, University of Colorado at Boulder, Institute of Arctic and Alpine Research, UCB 450, 1560 30th St., Boulder, CO 80309, USA 3 Evolutionary biologist, Universite Rene-Descartes Paris V, Centre de recherches interdisciplinaires (CRI), INSERM U571, Faculte de medecine, Site Cochin Port-Royal, 75014 Paris, France

The process of selecting candidate areas for inclusion in a regional conservation network should include not only delineating appropriate land units for selection and defining targets for representing features of interest, but also determining the suitability of land units for conservation purposes. We developed an explicit rating of conservation suitability by applying fuzzy-logic functions in a knowledge base to ecological condition and socio-economic attributes of land units in the interior Columbia River basin, USA. Suitability was converted to unsuitability to comprise a cost criterion in selecting regional conservation networks. When unsuitability was the sole cost criterion or was combined with land area as cost, only about one-third of the area selected was rated suitable, due to inclusion of unsuitable land to achieve representation of conservation targets (vegetation cover-type area). Selecting only from land units rated suitable produced networks that were 100% suitable, reasonably efficient, and most likely to be viable and defensible, as represented in our knowledge-based system. However, several conservation targets were not represented in these networks. The tradeoff between suitability and effectiveness in representing targets suggests that a multi-stage process should be implemented to address both attributes of candidate conservation networks. The suitability of existing conservation areas was greater than that of most alternative candidate networks, but 59% of land units containing conservation areas received a rating of unsuitable, due in part to the presence of units only partially occupied by conservation areas, in which unsuitability derived from conditions in non-conserved areas.

Although the ecological dynamics of the alpine treeline ecotone are influenced by climate, it is an imperfect indicator of climate change. Mechanistic processes that shape the ecotone—seed rain, seed germination, seedling establishment and subsequent tree growth form, or, conversely tree dieback—depend on microsite patterns. Growth forms affect wind and snow, and so develop positive and negative feedback loops that create these microsites. As a result, complex landscape patterns are generated at multiple spatial scales. Although these mechanistic processes are fundamentally the same for all forest-tundra ecotones across western North America, factors such as prior climate, underlying geology and geomorphology, and genetic constraints of dominant tree species lead to geographic differences in the responses of particular ecotones to climate change.

Forest–alpine tundra ecotones (FTEs) are dynamic transition zones between forest and alpine tundra ecosystems that play an important role in regulating ecological processes, which are in turn directly influenced by the spatial patterns of trees and environmental constraints such as topography and climate. Our objectives were to characterize the spatial patterns of tree species and size classes, determine whether spatial patterns of trees differed among three FTE types, and examine FTE- and tree-environmental relationships in our study area on Niwot Ridge, CO, USA. Overall, spatial aggregation was more extensive for seedlings than saplings or trees. Distributions were largely random in limber pine but were highly aggregated in Engelmann spruce and especially subalpine fir, reflecting these species’ relative shade tolerance and expected sequence of establishment following disturbance. Fragmented and patchy tree distributions were observed in the FTE with the most heterogeneous topography, characterized by high relief and associated physical disturbances. The least patchy distributions were associated with the FTE containing a relative absence of disturbance. Intermediate levels of tree aggregation were associated with low topographic relief and presence of meadows and wetlands. Our results emphasize the importance of spatial structure as an initial controlling factor of vegetation pattern in FTEs occurring in the same landscape.

Background: Current understanding of treeline or forest-alpine ecotone (FAE) dynamics does not fully explain past and present FAE patterns and their underlying processes, nor allow prediction of their response to climate change. Aims: We address the overarching hypothesis that the FAE is a mosaic of distinct landscape units of vegetation and landforms that result in differential responses to climate change. We focus on climate-related, landscape and vegetation characteristics, but also consider the effect of landscape heterogeneity on biogeochemistry and overall resilience of the FAE to climate change. Results: There are three distinct FAE land units at Niwot Ridge, generated by different interactions of climate with vegetation, landforms and topography. Within these FAEs, a process of self-organisation takes place from organism to patch to landscape scales, and is modulated by positive and negative feedback loops along an elevation gradient. The underlying controls cannot be attributed solely to temperature, but to a combination of interactions along a physical/biotic gradient. Conclusions: FAE dynamics result from interactions among mechanisms and processes at the microsite, patch and landscape scales: (1) tree persistence; (2) forest patch establishment; (3) drivers of patch forest configurations and (4) resilience, increasing along a gradient of biotic control.

Aim We addressed four objectives: (1) Determine the regional responses of species, size classes and a vegetation type to climate and parent material predictors, including their distributions in environmental space and the relative contributions of the predictors to explained variation. (2) Determine whether size classes of a species respond similarly to climate and parent material. (3) Assess the extent to which the predicted regional distribution of a vegetation type can be approximated by the distribution of its diagnostic species and vice versa. The establishment of a consistent relationship between the distribution of a vegetation type and its diagnostic species would facilitate change detection, management and conservation planning by allowing the use of one distribution to generate the other when data availability is limited. (4) Examine landscape-scale environmental variability in predicted species and vegetation type distributions. Location South-western USA (Arizona, New Mexico and southern Colorado). Methods Ecological response surface models were developed using a data base of 1409 vegetation plots to analyse biotic–environmental relationships of (1) Pinus ponderosa P. & C. Lawson and Abies concolor (Gord. & Glend.) Lindl. Ex Hildebr. size classes, (2) P. ponderosa, A. concolor and Quercus gambelii Nutt. combined size classes, and (3) a P. ponderosa forest type widely distributed in the south-western USA. Results and main conclusions Pinus ponderosa and A. concolor models generally were judged to be successful. Quercus gambelii models were judged unsuccessful, which may result from the influence of variables not modelled, such as soil moisture, disturbance, biotic factors and other site limiting factors. Size classes differed in the range of environmental conditions associated with high occurrence probabilities within and between species, reflecting differences in the effects of climate variability and anthropogenic changes, such as fire suppression, on the distribution of each size class. Pinus ponderosa alliance was predicted to be distributed over a narrower range of environmental conditions than P. ponderosa species models, therefore limiting the use of this vegetation type as a surrogate for the distribution of the dominant species, and vice versa. Maps of combinations of environmental variables that produced a high probability of P. ponderosa occurrence showed that some landscapes predicted to contain the species exhibited diverse environmental conditions over short distances. The use of regional environmental relationships to characterize areas with high local environmental variability may facilitate identification of areas of potential rapid biotic change.

Core design components of the Ecosystem Management Decision Support system were used to develop and implement the integrated restoration and protection strategy of the Northern Region of the U.S. Department of Agriculture Forest Service. Scenarios that spatially optimized hazardous fuel reduction, protected developed recreation values, and improved watershed conditions are presented to illustrate how the evaluation and decision modeling capabilities of the decision support system can be used sequentially in both strategic and tactical planning.

Spatial decision support systems (SDSS) are (1) customized software applications that (2) apply analytical constructs to (3) spatial data layers, (4) for the purpose of informing specific decisions and decisions makers. What is special about them is how they enable transparent decision-making processes, effectiveness monitoring, adaptive management, and making better future decisions. Custom SDSS applications can be thought of as snapshots of the logic used to make a decision. As such, they are invaluable to grounding management and its edification through learning. An SDSS clearly reveals the logic and data that decision makers use to derive their best decision to solve a specific set of problems. But at best, it represents the hypothesis—‘this is how we thought to solve these problems, given available information’. Subsequent decisions can be informed by the portions of a decision that worked/did not work, with little effort to reconstruct the evaluation, only to adapt it. EMDS is a SDSS development tool. It was conceived for application to the decision-making process of ecosystem management because these decisions are typically complex, multi-layered, and difficult to track, once made. EMDS uses spatial data layers, and there is no real limit to the number of dimensions it can consider in decision making. Here, we summarize how EMDS has been used to date and discuss new directions for expanding its utility. We also discuss how users and applications have influenced, and continue to influence, EMDS development, and new versions will no doubt reflect the evolution of decision making and technology.

A subwatershed base map of 84 hydrologic subregions within the Columbia River Basin (approximately 58,361,000 ha) was developed following hierarchical principles of ecological unit mapping. Our primary objectives were to inspect the relations between direct and indirect biophysical variables in the prediction of valley bottom and stream type patterns, and to identify hydrologic subregions (based on these results) that had similar aquatic patterns for which consistent management practices could be applied. Realization of these objectives required: (1) stratified subsampling of valley bottom and stream type composition within selected sub-watersheds, (2) identification of direct and indirect biophysical variables that were mappable across the basin and that exerted primary control on the distribution of sampled aquatic patterns, and (3) development of hydrologic subregion maps based on the primary biophysical variables identified. Canonical correspondence analysis indicated that a core set of 15 direct variables (e.g., average watershed slope, drainage density, ten-year peak flow) and 19 indirect variables (i.e., nine subsection groups, four lithology groups, and six potential vegetation settings) accounted for 31 and 30 percent (respectively) of valley bottom/stream type composition variability and 84 and 80 percent (respectively) of valley bottom/stream type environmental variability within subsamples. The 19 indirect biophysical variables identified were used to produce an ecological unit classification of 7,462 subwatersheds within the basin by a hierarchical agglomerative clustering technique (i.e., hydrologic subregions were identified). Discriminant analysis indicated that 13 direct biophysical variables could correctly assign 80 percent of the subwatersheds to their indirect biophysical classification, thus demonstrating the strong relation that exists between indirect biophysical based classifications (ecological units) and the direct biophysical variables that determine finer-level aquatic patterns. Our hydrologic subregion classifications were also effective in explaining observed differences in management hazard ratings across all subwatersheds of the basin. Results of this research indicate that ecological units can be effectively used to produce watershed classifications that integrate the effects of direct biophysical variables on finer-level aquatic patterns, and predict opportunities and limitations for management.

(2000). Antarctic Sea Ice—Physical Processes, Interactions and Variability, Submarines under Ice—The U.S. Navy's Polar Operations, Climate Change and Spatial Diversity of Vegetation during the Late Quaternary of Beringia, Numerical Ecology. By Pierre and Louis Legendre, Tectonic Uplift and Climate Change, Geocryological Map of Russia and Neighbouring Republics: The English Language Edition. Arctic, Antarctic, and Alpine Research: Vol. 32, No. 2, pp. 216-220.

As global environmental issues and the impact of global environmental changes attract increasing attention from the public and policymakers, the focus has been on developing indicators of ecosystem health at regional to global scales. This broadening of the scale of assessments has led to a heavy reliance on quantitative tools using an array of technological advances (e.g., GIS, remote sensing). The accuracy and quality of reports on ecosystem integrity or health obtained from broad-scale assessments depend to a large extent on understanding the limits of the data and the technologies used. As the public and policymakers increasingly require rapid, timely evaluation of ecosystem conditions, the use of data and technologies that allow real-time, relatively inexpensive, frequent assessments will increase accordingly. Although the limitations of these data and technologies are broadly understood, the practical implications for specific assessments are not always fully considered. At broad scales, key measures or indicators of ecosystem integrity are usually related to landscape patterns, such as patch abundance, size, and spatial distribution. Therefore, accurate and robust assessments of ecosystem health require a reliable methodology that captures relevant measures of ecosystem health. It is the purpose of this article to document one aspect of the development of reliable characterization and monitoring protocols, namely the appropriateness of the data used to characterize landscape patterns for assessing ecosystem integrity and ecological conditions. We assessed the use of coarse-resolution advanced very high resolution radiometer (AVHRR) derived data for characterizing broad-scale (ecoregions) and fine-scale landscape patterns over the 580,000 km2 of the interior Columbia River basin. We analyzed patch and landscape indices, correlations, principal components, and a statistical comparison of an AVHRR-derived land-cover map with fine-resolution data. Differences in broad-scale landscape patterns among ecoregions were most successfully characterized using combinations of patch and landscape indices. Both classification levels differentiated ecoregion patterns, but the finest level provided increased discriminating ability. Ecoregion and classification levels interacted to produce results specific to particular cover types. AVHRR-derived data did not adequately characterize some important fine-resolution landscape features. We hypothesized that AVHRR-derived data would be in closest agreement with fine-resolution data when landscape texture was coarse. The results indicated that landscape texture influenced the performance of AVHRR-derived data, but in an inconsistent manner, suggesting that coarse-resolution differences from fine-resolution data have limited predictability. Our results have important implications for characterizing and discriminating landscape patterns among and within ecoregions and along ecological gradients. Across areas with varying landscape heterogeneity, changes in relationships among ecoregion levels, classification levels, and data resolutions may increase opportunities for inaccurate representation of landscape patterns. The choice of a specific ecoregion level, classification level, and data resolution should be examined for patterns of inconsistent characterization before use in broad-scale ecological assessments.

Plant species richness and species-area relations were examined for three landscapes (toposequences), each with a summit or upland, a midslope and a toeslope or lowland, in a shortgrass steppe in Colorado. The number of plant species in the largest plot size (0.16 ha) varied from 38 to 53. Neither the exponential relationship: s = a + b log A, nor the power function: S = cAz fit the data equally well in all situations. The processes acting upon species diversity here seem to operate at two spatial scales. The number of species in plots smaller than 3 m 2 was independent of the total number of species in the 0.16-ha plots and was constrained by the presence of the dominant bunchgrasses. Beyond 3 m 2 , species number in each plot size was a function of the total number of species in the 0.16-ha plot.

Ecosystem management is an evolving philosophy that many government agencies have adopted in the multiple-use, sustained-yield management of federal lands. The primary objective of this philosophy is to sustain the integrity of ecosystems (i.e., their function, composition, and structure) for future generations while providing immediate goods and services to an increasingly diverse public. This objective can be achieved through integrated land evaluation and optimal land use planning that promotes the maintenance or development of landscape patterns and processes that meet societal expectations within the limits of the land's ecological potentials. Landscape ecology and conservation biology principles are critical components of this philosophy. This paper describes how some of these principles can be efficiently used in formulating a framework for ecosystem management on federal lands. The role of landscape ecology in ecosystem characterization and description is stressed, and the appropriateness of integrated ecological assessments to ecosystem management is discussed.

A landscape characterization procedure is described as a first step in ecosystem management. Five attributes were used to characterize patterns at different scales of ecological organization from the plot to the region: climatic regions, ecoregions, biophysical environments, floristics, and vegetation. Examples of the characterization of selected attributes are presented for three western U.S. study areas. Other aspects of the characterization process are illustrated with examples from the Northern Region of the Forest Service and from forested locations in the southwestern U.S. Location of a study area within a climatic region provided an understanding of broad-scale climatic constraints operating on the biota. Assessment at the ecoregion level was used to examine finer scale environmental constraints due to landform effects. The ecoregion also provided a context for further analysis of biotic and environment variability in a study area. Biophysical environments (combinations of environmental factors) we...

The availability of spatially continuous data layers can have a strong impact on selection of land units for conservation purposes. The suitability of ecological conditions for sustaining the targets of conservation is an important consideration in evaluating candidate conservation sites. We constructed two fuzzy logic-based knowledge bases to determine the conservation suitability of land units in the interior Columbia River basin using NetWeaver software in the Ecosystem Management Decision Support application framework. Our objective was to assess the sensitivity of suitability ratings, derived from evaluating the knowledge bases, to fuzzy logic function parameters and to the removal of data layers (land use condition, road density, disturbance regime change index, vegetation change index, land unit size, cover type size, and cover type change index). The amount and geographic distribution of suitable land polygons was most strongly altered by the removal of land use condition, road density, and land polygon size. Removal of land use condition changed suitability primarily on private or intensively-used public land. Removal of either road density or land polygon size most strongly affected suitability on higher-elevation US Forest Service land containing small-area biophysical environments. Data layers with the greatest influence differed in rank between the two knowledge bases. Our results reinforce the importance of including both biophysical and socio-economic attributes to determine the suitability of land units for conservation. The sensitivity tests provided information about knowledge base structuring and parameterization as well as prioritization for future data needs.

International audience; This work addresses the impacts of development at the wildland-urban interface on forest fires that spread to human habitats. Catastrophic fires in the western United States and elsewhere make these impacts a matter of urgency for decision makers, scientists, and the general public. Using a simple fire-spread model, along with housing and vegetation data, we show that fire size probability distributions can be strongly modified by the density and flammability of houses. We highlight a sharp transition zone in the parameter space of vegetation flammability and house density. Many actual fire landscapes in the United States appear to have spreading properties close to this transition. Thus, the density and flammability of buildings should be taken into account when assessing fire risk at the wildland-urban interface. Moreover, our results highlight ways for regulation at this interface to help mitigate fire risk.

Ecological classifications group similar items to provide a framework for organizing our knowledge about ecosystems (Driscoll et al., 1984; Jensen et al., 1991). Examples of such classification schemes include soil taxonomy (USDA-SCS, 1975), potential vegetation types (Driscoll et al., 1984), channel units (Hawkins et al., 1993), stream types (Rosgen, 1994), valley bottom types (USDA, 1978), and watershed types (Jensen et al., 1997). These classifications can be given a spatial component by describing their composition within ecological mapping units (Cleland et al., 1997).

Ecological assessments facilitate understanding of an area’s past, present, and future conditions through comprehensive description of ecosystem patterns, processes, and functions (Lessard et al., 1999). They synthesize our knowledge of ecological Systems and commonly describe the biophysical and social limits of a system, the interrelations of its ecosystem components, and the uncertainties and assumptions that underlie a given assessment effort. Ecological assessments are not decision documents because they do not resolve issues or provide direct solutions to specific policy questions. Instead, they provide the foundation for proposed additions or changes to existing land management plans or regulatory policies and are a critical component for implementing principles of ecosystem management in land management planning (Grossarth and Nygren, 1994; Morrison, 1994; Haynes et al., 1996).

An ecological land classification (ELC) is the product of the formal definition of land-based ecosystems and ecosystem complexes (Rowe and Sheard, 1981; Sims et al., 1996), based on the ecological and mapping principles of ecosystem characterization (see Chapters 2 and 3). In addition to the specific requirements of ecosystem characterization (see Chapter 3), constructing an ELC requires making decisions about the classification concepts to follow and the specific uses of the ELC (Grossman et al., 1999). In practice, the classification process is a balance between science and art (Sims et al., 1996).

A requirement for ecological information to identify, quantify, and evaluate the potential impact of land-use decisions on ecosystems has been recognized for some time (Everett et al. 1994; O’Callaghan 1996;Boyce and Haney 1997; Lyle 1999; Treweek 1999; Jensen et al. 2001). The process of integrated ecological assessment (IEA) has been developed to provide a comprehensive description of the ecosystem patterns, processes, and functions, including relevant socio-political factors, needed to synthesize our knowledge of ecological and human systems. IEA techniques are rooted in ecological, social, and economic sciences. IEAs incorporate evaluation of the implications of human activities, including production of land-management scenarios. They should be part of integrated systems of environmental regulation that include strategic planning, objective setting, performance standards, monitoring, and review of the entire process (Treweek 1999). Recent applications of IEAs (see case studies in [1998] and [2001]) represent the integration of a number of approaches developed in response to specific problems, socio-political contexts, national legislation, and international accords (see review in [1999]; see also [1999]; and [1999]). Various terms have been used to describe all or part of the process of assessing the state of the environment and its relationship to economic development.

Previous chapters have emphasized the dynamic nature of ecosystems, including the occurrence of periodic disturbances. Consequently, current ecosystem composition, structure, and function are likely to operate within ranges of variability that arise from climatic variability, disturbance, and the effects of human activities (Bourgeron and Jensen, 1994; Kaufmann et al., 1994; Morgan et al., 1994; Cissel et al., 1998). Understanding the magnitude and direction of anthropogenic impacts requires knowledge of the range of fluctuations historically experienced by ecosystems as a result of variability in climatic conditions, disturbance regimes, and their interactions (Swetnam and Betancourt, 1998). Therefore, the determination of the historical range of variability (HRV) in key ecosystem patterns and processes is an important part of ecological assessments and results in the characterization of the range of variability in conditions to which ecosystem components (e.g., species) are adapted (Bourgeron and Jensen, 1994; Morgan et al., 1994; Swanson et al., 1994). HRV provides a baseline for evaluating anthropogenic changes and a means for identifying the potential for surprise events to occur (Holling, 1986). Historical conditions serve as a model of the functioning of ecosystems under unmodified disturbance regimes and alternative land-use scenarios. Ecosystem patterns and processes operate at multiple hierarchically structured spatial and temporal scales, and therefore the determination of HRV should be conducted at scales that both meet the objectives of the assessment and are appropriate for the patterns and processes of interest (Bourgeron et al., 1994).

Virtually any aspect of an ecological assessment (EA) is likely to involve the topic of space, including its striking effect on landscapes and the distribution of human populations. For example, a spatially explicit approach is needed to address two policy questions common to many EAs. What is required for maintaining the long-term productivity of ecosystems? What is the impact of maintaining current management scenarios on, for example, major social issues or the maintenance of rural communities and their economies in a given area? Essential tasks of EAs also involve the explicit consideration of space, such as in combining information from various geographic areas and multiple scales. Most measurements of large-scale phenomena, such as the effect of regional carbon and nitrogen cycles, hydrologic regimes, changes in land-use patterns, and demographics, among many others, carry the imprint of spatial variability and scaling. Therefore, explicit consideration of all aspects of space (e.g., spatial variability and its corollary, spatial scaling) is increasingly a central concern in the design and implementation of EAs, whether in map creation or incorporation in predictive modeling (see Chapters 3 and 18; also, Haining, 1990; Ritchie, 1997).

Large-scale data collection is the initial observational phase of integrated regional ecological assessments (IREAs). The data collection methodology determines to a large extent the accuracy and precision of all subsequent analyses, such as pattern recognition (Bourgeron and Jensen, 1994; Bourgeron et al., 1994a; Dale and O’Neill, 1999). The data analysis and interpretative phases of IREAs often tend to be emphasized by scientists over formal data collection procedures (see the case studies in Chapters 30 through 34; for a very formal approach to survey design, see the US-EPA Ecological Monitoring and Assessment Program, O’Neill et al., 1994; Kapner et al., 1995). The lack of formal, consistent data collection protocols for IREAs is unfortunate, because the quality of the characterization of a region and the quality of subsequent interpretations depend on the quality of the data, both in terms of the thoroughness of coverage and the type of information collected.

Ecological assessments are an important component of any strategy for making or reevaluating land management and regulatory decisions (see Chapters 1, 9, and 35; also Slocombe, 1993; Jensen and Bourgeron, 1994; Bourgeron et al., 1995). An important objective of ecological assessments is the identification, location, and description of the biotic and abiotic features of a landscape. Landscape features exhibit heterogeneity at a variety of scales (Turner et al., 1995). This heterogeneity is characterized by identifying relevant patterns and the processes that produce patterns in a landscape (Bourgeron and Jensen, 1994). Distinct patterns and processes occur at a variety of spatial and temporal scales of organization (see Chapter 2). For ecological assessments, an explicit understanding is needed of the scaled relationships of biological and biophysical characteristics from site to regional scales (Lessard, 1995; Lessard et al., 1999). Therefore, the characterization process is a multiscaled approach conducted within a hierarchical framework (Bourgeron and Jensen, 1994; Hann et al., 1994; Bourgeron et al., 1995; Jensen et al., 1996).

"A guidebook for integrated ecological assessments ... provides a useful and well-organized collection of contributions that may help standardize ecological assessment procedures. ... the chapters are very well written ... the figures and tables efficiently illustrate main points in the chapter. The references and suggested reading sections at the end of each chapter provide a wealth of informative resources ... . This book would be a very useful resource for those participating in, organizing, or just interested in ecological assessment." (Audrey L. Mayer, Ecology, Vol. 82 (12), 2001)

The Little Missouri National Grasslands (LMNG) of western North Dakota support the largest permitted cattle grazing use within all lands administered by the USDA, Forest Service, as well as critical habitat for many wildlife species. This fact, coupled with the need to revise current planning direction for range allotments of the LMNG, necessitated that a broad-level characterization of ecosystem integrity and resource conditions be conducted across all lands within the study area (approximately 800,000 hectares) in a rapid and cost-effective manner. The approach taken in this study was based on ecological classifications, which effectively utilized existing field plot data collected for a variety of previous inventory objectives, and their continuous spatial projection across the LMNG by maps of both existing and potential vegetation. These two map themes represent current and reference conditions (existing vs. potential vegetation); their intersection allowed us to assign various ecological status ratings (i.e., ecosystem integrity and resource condition) based on the degree of departure between current and reference conditions. In this paper, we present a brief review of methodologies used in the development of ecological classifications, and also illustrate their application to assessments of rangeland health through selected maps of ecological status ratings for the LMNG.

Potential vegetation environments (e.g., habitat types, range sites, ecological sites) are important to land managers because they provide a conceptual basis for the description of resource potentials and ecological integrity. Efficient use of potential vegetation classifications in regional or subregional scale assessments of ecosystem health has been limited to date, however, because traditional ecological unit mapping procedures often treat such classifications as ancillary information in the map unit description. Accordingly, it is difficult, if not impossible, to describe the precise location, patch size, and spatial arrangement of potential vegetation environments from most traditional ecological unit maps. Recent advances in remote sensing, geographic information systems (GIS), terrain modeling, and climate interpolation facilitate the direct mapping of potential vegetation through a predictive process based on gradient analysis and ecological niche theory. In this paper, we describe how a predictive vegetation mapping process was used to develop a 30 m raster-based map of 4 grassland, 5 shrubland, and 6 woodland habitat types across the Little Missouri National Grasslands, North Dakota. Discriminant analysis was used in developing this potential vegetation map based on 6 primary geographic information system themes. Geoclimatic subsections and remotely sensed vegetation lifeform maps were used in predictive model stratification. Terrain indices, LANDSAT satellite imagery, and interpolated climate information were used as independent (predictor) variables in model construction. A total of 616 field plots with known habitat type membership were used as dependent variables and assessed by a jackknife discriminant analysis procedure. Accuracy values of our map ranged from 54 to 77% in grasslands, 62 to 100% in shrublands, and 70 to 100% in woodlands dependent on geoclimatic subsection setting. Techniques are also described for generalizing the 30 m pixel resolution habitat type map to appropriate ecological unit maps (e.g., landtype associations) for use in ecosystem health assessments and land use planning. DOI:10.2458/azu_jrm_v54i5_jensen