Chapter
2.3.6 Data clearing houses
2.4 What we will have soon
2.5 Issues of data quality
2.5.1 Sources of uncertainty in spatial data
2.5.2 Considering uncertainty in landscapemodels
2.6 Needs in data acquisition and quality
2.6.1 Strengthen capacity to collect ground information
2.6.2 Develop key indicators of status and health of landscapes
2.6.3 Design efficient, multi-tiered sampling designs
2.6.4 Design and implement global landscape monitoring programs
2.6.5 Develop efficient tools for strategic ground sampling
2.6.6 Developmethods to share sensitive ground-specific information
2.6.7 Enhance and categorize methods to interpolate/extrapolate point-level data across landscapes
2.6.8 Develop techniques to best acquire and archive information on landscape history
2.6.9 Determine appropriate methods to merge and analyze data acquired at different scales
2.6.10 Efficiently handle increasing volumes of data, with minimal user pre-processing
2.6.11 New GIS technologies needed
2.6.12 Develop and test theory and methods of uncertainty analysis of landscape data
2.6.13 Devise methods so error can be evaluated and broken down into its various components (error budget)
2.6.14 Devise methods to assess the effects of varying data quality and grain size on the outputs of landscape pattern analysis,model simulations, and resultant decisions
2.7 Policy issues related to data acquisition and quality
3
Landscape pattern analysis: key
issues and challenges
3.2 General classification of LPA methods
3.3 Key components of spatial pattern in relation to LPA
3.4 Statistical and ecological assumptions of LPA methods
3.4.1 Statistical assumptions
3.4.2 Relationship between pattern and process
3.4.3 Ecological relevance of categorical data and landscape metrics
3.5 Behavior of LPA methods
3.5.1 Correspondence between landscape measures and pattern attributes
3.5.2 Relationships among LPA methods
3.5.3 Changes of landscape measures with respect to scale
3.6 Limitations and challenges of LPA
3.6.1 Difficulties in interpreting indices
3.6.2 Establishing relationships between pattern and process
3.6.3 Improving prediction based on known spatial heterogeneity
3.6.4 Determining the significance of differences between two landscapes
4
Spatial heterogeneity and
ecosystem processes
4.2 Understanding the spatial heterogeneity of process rates
4.3 Influence of land-use legacies
4.4 Lateral fluxes in landscape mosaics
4.5 Linking species and ecosystems
5
Landscape heterogeneity and
metapopulation dynamics
5.2 Levins’ metapopulation model
5.3 Spatially realistic metapopulation models
5.4 PVA tools based on the metapopulation framework
5.5 Landscape population models
5.5.2 Matrix heterogeneity
5.5.3 When should population models includematrix quality
and heterogeneity?
6
Determining pattern–process relationships
in heterogeneous landscapes
6.2.2 Corridor generation
6.2.5 Simulating invasion
6.2.5.1 Truncation effects for different dispersal kernels
6.2.5.2 Structured landscapes
6.2.5.3 Effect of competition
6.2.5.4 Landscape factorial
6.3.1 Truncation effects for different dispersal kernels
6.3.2 Effect of corridor width and gaps
6.3.3 Effect of competition on invasion
6.3.4 Fractalmaps factorial
6.4 Conclusions and recommendations
7
Scale and scaling: a cross-disciplinary
perspective
7.2 Concepts of scale and scaling
7.3 Scale effects, MAUP, and “ecological fallacy"
7.3.1 Characteristic scales and scale effects
7.3.3 The “ecological fallacy"
7.3.4 Towards a more comprehensive understanding of scale effects
7.4 Theory and methods of scaling
7.4.1.1 Similarity analysis
7.4.1.2 Allometric scaling
7.4.2.1 Upscaling methods
7.4.2.2 Downscaling methods
7.4.3 Uncertainty analysis
7.5 Discussion and conclusions
8
Optimization of landscape pattern
8.2 State-of-the-science in spatial optimization
8.2.1 Adjacency constraints
8.2.2 Spatial enhancement of the natural reserve-selection models
8.2.3 Direct approaches to spatial optimization
8.2.4 Heuristicmanipulation of simulation models
8.3 Critical research questions
8.3.3 Monitoring of spatially explicit plans
8.3.4 Multiple species/community levelmodels
9
Advances in detecting landscape
changes atmultiple scales: examples
from northern Australia
9.2 Examples of detecting landscape changes from
northern Australia
9.2.2 Defining landscape condition
9.3.1 Key challenge 1: detecting changes in landscape condition
at multiple scales
9.3.2 Key challenge 2: flow-on effects at multiple scales
9.3.3 Key challenge 3: ecological processes driving landscape change
10
The preoccupation of landscape research
with land use and land cover
10.4.1 The Internet survey
10.4.2 Dealing with land use, land cover and change
10.4.3 The context of land, landscape, and countryside
10.4.4 Issues not covered by the Internet survey
10.5 Conclusions: key issues for further integration in landscape ecology
11 Applying landscape-ecological principles to regional conservation: the WildCountry Project in Australia
11.2 Foundation principles
11.2.2 TheWildlands Project
11.2.3 Connectivity revisited
11.3 Large-scale connectivity
11.3.1 Trophic relations and interactive species
11.3.3 Long-distance biological movement
11.3.4 Ecologically appropriate fire regimes
11.3.5 Climate change and variability
11.3.6 Coastal zone fluxes
11.4 Research and development issues
11.4.2 Protected-area and off-reserve management
11.4.3 Fire regimemanagement and social values
11.4.4 Whole-of-landscape conservation planning
12
Using landscape ecology to make sense
of Australia’s last frontier
12.2 The north Australian frontier
12.3 This is not a landscape
12.5 Landscape models: but “there is no there there"
12.6 Longing and belonging
12.8 Unexpected insights: confessions of an empiricist
12.8.1 Shooting sacred buffalo
13
Transferring ecological knowledge to
landscape planning: a design method
for robust corridors
13.2 Context of the case study
13.3 The development of robust corridors and the implementation
in the planning process
13.3.1 Step 1: the translation of basic landscape ecological knowledge into
guidelines for single-species corridors
13.3.2 Step 2: integration from single species tomulti-species
robust corridors
13.3.3 Step 3: developing tools for the implementation of flexible design rules in the planning process
13.3.3.1 Defining the ambition level
13.3.3.2 Defining the number of ecosystem types in the robust corridor
13.3.3.3 Finding the preferred location
13.3.3.4 Defining the sequence of corridor elements
13.3.3.5 Combining other functions
13.4.1 Contribution to key issues
13.4.2 Further development of the corridor design method
13.4.2.1 Step 1: translating basic species ecology into spatial conditions
13.4.2.2 Step 2: knowledge integration
13.4.2.3 Step 3: flexible design rules
13.4.3 Impact on the planning process
14
Integrative landscape research:
facts and challenges
14.3 Defining integrative research approaches
14.4 Motivations for integrative landscape studies
14.5 What are we trying to integrate?
14.6 Organizational barriers to integration
14.7 Education and training needs
14.8 Improving the theory base
14.9 Themerit system and the products of integrative research
14.10 Mapping the boundaries of research
14.11 Enhancing integrative landscape ecology research
15
Landscape ecology: the state-of-the-science
15.2 Two dominant approaches to landscape ecology
15.2.1 The European approach
15.2.2 The North American approach
15.3 The elusive goal of a unified landscape ecology
15.4 Ahierarchical and pluralistic framework for landscape ecology
15.5 Discussion and conclusions
Key Topics in Landscape Ecology
( Cambridge Studies in Landscape Ecology )
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