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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing :
    Keywords: Landscape ecology. ; Environment. ; Environmental education. ; Conservation biology. ; Ecology . ; Environmental monitoring. ; Landscape Ecology. ; Environmental Sciences. ; Environmental and Sustainability Education. ; Conservation Biology. ; Environmental Monitoring.
    Description / Table of Contents: The Physical Template of Landscapes -- 1.1. Introduction -- 1.2. Gradient Analysis -- 1.2.1. Gradient Complexes -- 1.3. The Water Balance -- 1.3.1. A Simple Model: PET = AET + Deficit -- 1.4. Estimating Elements of the Template -- 1.4.1. Temperature -- 1.4.2. Radiation -- 1.4.3. Precipitation -- 1.4.4. Soils -- 1.5. Case Study: the Sierra Nevada -- 1.5.1. The Physical Template of the Sierra Nevada -- 1.6. Summary and Conclusions -- References -- Biotic Processes as Agents of Pattern -- 2.1. Introduction -- 2.2. The “Pattern and Process” Paradigm -- 2.3. Coupling of Demographic Processes -- 2.4. Interaction with the Physical Template -- 2.4.1. Coupling Demography and the Physical Template -- 2.4.2. Competition along Environmental Gradients -- 2.4.3. Illustration: Gradient Response in the Sierra Nevada -- 2.4.4. The Unit Pattern Revisited -- 2.5. Dispersal as an Agent of Pattern -- 2.6. Animals, Pests, and Pathogens -- 2.6.1. Animals, Pests and Pathogens as Subtle Agents -- 2.6.2. Animals as Dramatic Agents -- 2.7. Summary and Conclusions -- References -- Disturbances and Disturbance Regimes -- 3.1. Introduction -- 3.1.1 Context and Definitions -- 3.2. Perspectives and Lessons -- 3.2.1. Are Disturbances “Part of the System”? -- 3.2.2. Interactions, Synergies, and Indirect Effects -- 3.2.3. Disturbances and Positive Feedbacks -- 3.2.4. Overlapping Disturbances and Legacies -- 3.2.5. Heterogeneity in Disturbance and Response -- 3.3. Disaggregating Disturbance toward Generality. 3.3.1 A Not-too-General Model -- 3.3.2. The Fire Regime in the Sierra Nevada -- 3.4. Characteristic Dynamics -- 3.5. Humans and Disturbance Regimes -- 3.5.1. Human Impacts on Natural Disturbances - 3.5.2. Novel Disturbance Regimes -- 3.5.3 Human Perception and Landscape Change -- 3.6. Agents of Pattern: Reprise -- 3.7. Summary and Conclusions -- References 78 -- 4. Scale and Scaling - 4.1. Introduction -- 4.2. The Importance of Scale in Ecology -- 4.2.1. Observational Scale as a Filter on Nature -- 4.2.2. Characteristic Scaling -- 4.2.3. Sampling Grain and Extent, and Statistical Behavior -- 4.3. Scaling Techniques -- 4.3.1. Scaling Techniques for Geostatistical Data -- 4.3.2. Illustration: Scaling of the Sierran Physical Template -- 4.4. Tactical Scaling -- 4.4.1. Tactical Targeting of Sampling Scale(s) -- 4.4.2. Avoid or Embrace Space? -- 4.5. Summary and Conclusions -- References -- 5. Inferences on Landscape Pattern -- 5.1. Introduction -- 5.2. Patchiness and Patches -- 5.2.1. Patch Definition -- 5.3. Landscape Pattern Metrics -- 5.3.1. Levels of Analysis -- 5.3.2. Components of Pattern -- 5.3.2 Correlation and Redundancy -- 5.3.4. Alternative Framings for Landscape Pattern -- 5.4. Interpreting Landscape Metrics -- 5.4.1. Neutral Models and Neutral Landscapes -- 5.4.2. Neutral Templates for Landscape Processes -- 5.4.3. Extending Neutral Models: Agents of Pattern -- 5.5. Explanatory Models and Inferences -- 5.5.1. Approaches to Inferences on Pattern -- 5.5.2. Illustrations -- 5.5. Explanatory Models and Inferences -- -- 5.5.1. Approaches to Inferences on Pattern -- 5.5.2. Illustrations -- 5.5.3. Inferences on Pattern: Area versus Configuration -- 5.5.4 Inferences on Pattern: the State-of-the-Art -- 5.6. Summary and Conclusions. References -- Implications of Pattern: Metapopulations -- 6.1. Introduction -- 6.2. Metapopulations in Theory -- 6.2.1. The Levins Model -- 6.2.2. The Spreading-of-Risk Model -- 6.2.3. The Source-Sink Model -- 6.2.4. The Incidence Function Model -- 6.2.5. Commonalities among Metapopulation Models -- 6.2.6. Characteristic Behaviors of (Model) Metapopulations -- 6.3. Metapopulations in Practice -- 6.3.1. Are there Real Metapopulations in Nature? -- 6.3.2. Macroscopic Approaches to Metapopulations -- 6.4. Network Models of Metapopulations -- 6.4.1. Graphs and Metapopulations -- 6.5. Metapopulations and Connectivity Conservation -- 6.5.1. Structural and Functional Connectivity -- 6.5.2. Metapopulations and Landscape Genetics -- 6.6. A Model Template for Applications -- 6.7. Summary and Conclusions -- References -- Supplement 6.1. Details on the Metapopulation Models -- S6.1.1. The Levins Model -- S6.1.2. The Spreading-of-Risk Model -- S6.2.3. The Source-Sink Model -- S6.2.4. The Incidence Function Model -- S6.2.5. Notes on the Individual-based Simulators Metapop1 -- Communities and Patterns of Biodiversity -- 7.1. Introduction -- 7.2. Island Biogeography and Landscapes -- 7.2.1. Area and Isolation Effects -- 7.2.2. Island Biogeographic Theory and the SLOSS Debate -- 7.2.3. A Diversity of Diversities -- 7.3. Perspectives on Metacommunities -- 7.3.1. A General Framing -- 7.3.2. Inferences and Limits to Inference -- 7.4. Approaches and Lines of Evidence -- 7.4.1. The Incidence Matrix and Community Assembly -- 7.4.2. Metacommunity Models: Variations on a Theme -- 7.4.3. Species Distribution Models -- 7.4.4. Multvariate Approaches to Partitioning Beta-diversity -- 7.4.5. Lines of Evidence and Complementary Analyses -- 7.5. Illustration: Sierran Forests -- 7.5.1. The Perspective of Ordination and Gradient Analysis -- 7.5.2. Partitioning Beta-diversity -- 7.6. Managing Metacommunities -- 7.7. Summary and Conclusions -- References -- Supplement 7.1. Disciplinary Approaches (Details) -- S7.1.1. Incidence Matrices and Community Assembly -- S7.1.2. Metacommunity Models: Variations -- S7.1.3. Species Distribution Models -- S7.1.4. Ordination Techniques -- IImplications of Pattern for Ecosystems -- 8.1. Introduction -- 8.2. Spatial Heterogeneity and Ecosystems -- 8.2.1. Spatial Heterogeneity in the Physical Template -- 8.2.2. Lateral Fluxes on Landscapes -- 8.2.3. Landform and Landscape Processes -- 8.2.4. Ecosystem Processes and Positive Feedbacks -- 8.2.5. Ecosystems are both Fast and Slow -- 8.3. Ecosystems and Landscape Legacies -- 8.4. Patch Juxtaposition and Edge Effects -- 8.4.1. Edge Effects, Revisited -- 8.4.2. Edges and Ecosystem Processes: Forest Carbon -- 8.5. Ecosystems and Meta-ecosystems -- 8.5.1. Couplings between Systems -- 8.5.2. Meta-ecosystems, Revisited -- 8.5.3. Implications of Meta-ecosystem Structure -- 8.6. Summary and Conclusions -- References -- Urban Landscapes -- 9.1. Introduction -- 9.2. Social-Environmental Systems -- 9.2.1. Approaches to Studying Cities -- 9.3. Agents and Implications of Pattern -- 9.3.1. Agents of Pattern -- 9.3.2. Scale and Pattern -- 9.3.3. Implications of Pattern -- 9.3.4. Revisiting the Agents-and-Implications Framing -- 9.4. Urban Landscapes as Laboratories -- 9.4.1. The Urban Stream Syndrome -- 9.4.2. Cities as Mesocosms for Global Change -- 9.5. Summary and Conclusions -- References -- 10. Climate Change: Adapting for Resilience -- 10.1 Introduction -- 10.2. Framing Adaptation -- 10.2.1. Components of Climate Change -- 10.2.2. The Perspective of Risk Management -- 10.2.3. Options for Response and Adaptation -- 10.2.4. Resilience Planning: the Tasks at Hand -- 10.3. Approaches to Adaptation Planning -- 10.3.1. Levels of Activity and Currency of Assessments -- 10.3.2. Elements of Adaptation -- 10.3.3. A Template for Applications -- 10.4. Illustrations of Approaches -- 10.4.1. NatureServe’s HCCVI -- 10.4.2. Species Range Shifts implied by Climate Change -- 10.4.3. TNC’s Resilient Landscapes Initiative -- 10.4.4. The ACT Framework -- 10.4.5. Complementarity of Approaches -- 10.5. Collateral Benefits and Leverage -- 10.5.1. Adaptation Planning and Conservation Practice -- 10.5.2. Collateral Benefits -- 10.5.3. Adaptation and Mitigation -- 10.6. Summary and Conclusions -- References -- Index.. .
    Abstract: This is an ecology textbook focused on key principles that underpin research and management at the landscape scale. It covers (1) agents of pattern (the physical template, biotic processes, and disturbance regimes); (2) scale and pattern (why scale matters, how to ‘scale’ with data, and inferences using landscape pattern metrics); and (3) implications of pattern (for metapopulations, communities and biodiversity, and ecosystem processes). The last two chapters address emerging issues: urban landscapes, and adapting to climate change. This book stems from two graduate-level courses in Landscape Ecology taught at the Nicholas School of the Environment at Duke University. The subject has evolved over time, from a concepts-based overview of what landscape ecology is, to a more applied practicum on how one does landscape ecology. As landscape ecology has matured as a discipline, its perspectives on spatial heterogeneity and scale have begun to permeate into a wide range of other fields including conservation biology, ecosystem management, and ecological restoration. Thus, this textbook will bring students from diverse backgrounds to a common level of understanding and will prepare them with the practical knowledge for a career in conservation and ecosystem management.
    Type of Medium: Online Resource
    Pages: XIX, 327 p. 20 illus. , online resource.
    Edition: 1st ed. 2023.
    ISBN: 9783031402548
    DDC: 577.5
    Language: English
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Ecosystems 2 (1999), S. 76-87 
    ISSN: 1435-0629
    Keywords: Key words: climatic change; forest gap model; fire regime; spatial pattern; connectivity.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: ABSTRACT In the Sierra Nevada, distributions of forest tree species are largely controlled by the soil-moisture balance. Changes in temperature or precipitation as a result of increased greenhouse gas concentrations could lead to changes in species distributions. In addition, climatic change could increase the frequency and severity of wildfires. We used a forest gap model developed for Sierra Nevada forests to investigate the potential sensitivity of these forests to climatic change, including a changing fire regime. Fuel moisture influences the fire regime and couples fire to climate. Fires are also affected by fuel loads, which accumulate according to forest structure and composition. These model features were used to investigate the complex interactions between climate, fire, and forest dynamics. Eight hypothetical climate-change scenarios were simulated, including two general circulation model (GCM) predictions of a 2 × CO2 world. The response of forest structure,species composition, and the fire regime to these changes in the climate were examined at four sites across an elevation gradient. Impacts on woody biomass and species composition as a result of climatic change were site specific and depended on the environmental constraints of a site and the environmental tolerances of the tree species simulated. Climatic change altered the fire regime both directly and indirectly. Fire frequency responded directly to climate's influence on fuel moisture, whereas fire extent was affected by changes that occurred in either woody biomass or species composition. The influence of species composition on fuel-bed bulk density was particularly important. Future fires in the Sierra Nevada could be both more frequent and of greater spatial extent if GCM predictions prove true.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Landscape ecology 15 (2000), S. 145-154 
    ISSN: 1572-9761
    Keywords: connectivity ; correlation length ; elevation gradient ; fire spread ; forest gap model ; fuel characteristics ; mixed conifer forest ; Sierra Nevada ; surface fire regime
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract The connectivity of a landscape can influence the dynamics of disturbances such as fire. In fire-adapted ecosystems, fire suppression may increase the connectivity of fuels and could result in qualitatively different fire patterns and behavior. We used a spatially explicit forest simulation model developed for the Sierra Nevada to investigate how the frequency of surface fires influences the connectivity of burnable area within a forest stand, and how this connectivity varies along an elevation gradient. Connectivity of burnable area was a function of fuel loads, fuel moisture, and fuel bed bulk density. Our analysis isolated the effects of fuel moisture and fuel bed bulk density to emphasize the influence of fuel loads on connectivity. Connectivity was inversely related to fire frequency and generally increased with elevation. However, certain conditions of fuel moisture and fuel bed bulk density obscured these relationships. Nonlinear patterns in connectivity across the elevation gradient occurred as a result of gradients in fuel loads and fuel bed bulk density that are simulated by the model. Changes in connectivity with elevation could affect how readily fires can spread from low elevation sites to higher elevations.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Landscape ecology 7 (1992), S. 163-180 
    ISSN: 1572-9761
    Keywords: Avian communities ; Eastern Deciduous Forest ; landscape pattern ; life-history traits ; Pacific Northwest Forest
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract We suggest that the life histories of species within communities may differ among geographic locations and that communities from distinct biomes may respond uniquely to a given trajectory of landscape change. This paper presents initial tests relevant to these hypotheses. First, the representation of various life-history guilds in avifaunas from the Eastern Deciduous (EDF) and Pacific Northwest (PNW) forests were compared. Three guilds contained more species in the EDF community (large patch and/or habitat interior guild, small patch and/or edge guild, and fragmentation-sensitive guild). The guild of predators requiring large forest tracts was better represented in the PNW. Next, the relative sensitivity of each community to habitat change was ranked based on the life-history traits of their species. The EDF avifauna had a significantly higher index of sensitivity to both forest fragmentation and to landscape change in general. Among the birds with high scores for sensitivity to landscape change were several species that have received little conservation attention thus far including some associated with open-canopy habitats. Lastly, the validity of using life histories to predict community response to landscape change was supported by the fact that the sensitivity scores for PNW species correlated significantly with independent data on species population trends. While more rigorous analyses are suggested, we conclude that knowledge of life histories is useful for predicting community response to landscape change and that conservation strategies should be uniquely tailored to local communities.
    Type of Medium: Electronic Resource
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  • 5
    ISSN: 1572-9761
    Keywords: gap model ; gradient analysis ; landscape pattern ; sensitivity analysis ; Sierra Nevada ; spatial scale ; water balance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in California's Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the model's sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.
    Type of Medium: Electronic Resource
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  • 6
    ISSN: 1573-1480
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract We used an individual-based forest simulator (a gap model) to assess the potential effects of anthropogenic climatic change on conifer forests of the Pacific Northwestern United States. Steady-state simulations suggested that forest zones could be shifted on the order of 500–1000 m in elevation, which could lead to the local extirpation of some high-altitude species. For low-elevation sites, species which currently are more abundant hundreds of kilometers to the south would be favored under greenhouse scenarios. Simulations of transient responses suggested that forest stands could show complex responses depending on initial species composition, stand age and canopy development, and the magnitude and duration of climatic warming. Assumptions about species response to temperature, which are crucial to the model's behaviors, were evaluated using data on species temperature limits inferred from regional distributions. The high level of within-species variability in these data, and other confounding factors influencing species distributions, argue against over-interpreting simulations. We suggest how we might resolve critical uncertainties with further research.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Climatic change 16 (1990), S. 9-29 
    ISSN: 1573-1480
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract A gap model of environmental processes and vegetation patterns in boreal forests was used to examine the sensitivity of permafrost and permafrostfree forests in interior Alaska to air temperature and precipitation changes. These analyses indicated that in the uplands of interior Alaska, the effect of climatic warming on the ecology of boreal forests may not be so much a direct response to increased air temperature as it may be a response to the increased potential evapotranspiration demands that will accompany climatic warmings. On poorlydrained north slopes with permafrost, the drier forest floor reduced the flux of heat into the soil profile. This was offset by increased fire severity, which by removing greater amounts of the forest floor increased the depth of soil thawing and converted the cold black spruce forests to warmer mixed hardwood-spruce forests. On well-drained south slopes, the increased potential water loss reduced available soil moisture, converting these mesic sites to dry aspen forests, or if too dry to steppe-like vegetation. Increases in precipitation offset the effects of increased potential evapotranspiration demands and mitigated these forest changes.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Plant ecology 74 (1988), S. 143-150 
    ISSN: 1573-5052
    Keywords: Aggregation ; Forest-structure ; Gap dynamics ; Landscape ; Succession
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract An individual tree-based forest succession model was modified to simulate a forest stand as a grid of contiguous 0.01-ha cells. We simulated a 9 ha stand for 750 years and sampled the stand at 50 yr intervals, outputting structural variables for each grid cell. Principal components analysis was used to depict temporal patterns in forest structure as observed in 0.01 ha samples (individual grid cells). We then resampled the grid using square aggregates of 4 to 100 grid cells as quadrats. Principal component scores recalculated for the aggregates, using the original (0.01 ha scale) scoring matrix, depict the effects of obervational scale on perceived patterns in forest structure. Larger quadrats reduce the apparent variation in forest structure and decrease the apparent rate of structural dynamics. Results support a scale-dependent conceptualization of forest systems by illustrating the qualitative difference in forest dynamics as viewed at the scale of individual gap elements as compared to the larger scale steady state mosaic. The aggregation exercise emphasizes the relationship between these two observational scales and serves as a general framework for understanding scaling relationships in ecological phenomena.
    Type of Medium: Electronic Resource
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  • 9
    Publication Date: 2005-07-01
    Description: The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. This model is unsatisfying in that elevation is not directly relevant to plants and the ubiquitous "elevation gradient" is composed of multiple intertwined environmental factors. We offer an approach to landscape-scale vegetation analysis that disentangles the elevation gradient into its constituent parts through focused field sampling and statistical analysis. We illustrate the approach for an old-growth watershed in the Oregon Western Cascades. Our initial model of this system supports the common observation that forest community types are highly associated with specific elevation bands. By replacing elevation and other crude environmental proxy variables with estimates of more direct and resource gradients (radiation, temperature, and soil moisture), we create a vegetative model with stronger explanatory power than the proxy model in both cross-validation analysis and validation using an independent data set. The resulting model is also more biologically interpretable, which provides more meaningful insight into potential forest response to environmental change (e.g., global climate change scenarios). Acquiring a better mechanistic understanding of the relationship between plant communities and environmental predictor variables presents the next great challenge to community ecologists conducting gradient studies at landscape scales.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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  • 10
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