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1.
Although landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers
a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units
and then selecting a subset (sample) of these units introduces artificial patch edge and patch truncation effects that may
lead to biased sample-based estimators of landscape pattern metrics. The bias and variance of sample-based estimators of status
and change in landscape pattern metrics were evaluated for four 120-km × 120-km test regions with land cover provided by the
1992 and 2001 National Land-Cover Data of the United States. Bias was generally small for both the estimators of status and
estimators of change in landscape pattern, but exceptions to this favorable result exist and it is advisable to assess bias
for the specific metrics and region of interest in any given application. A 10-km × 10-km sample block generally yielded larger
biases but smaller variances for the estimators relative to a 20-km × 20-km sample block. Stratified random sampling improved
precision of the estimators relative to simple random sampling. The methodology developed to determine properties of sample-based
estimators can be readily extended to evaluate other landscape pattern metrics, regions, and sample block sizes. 相似文献
2.
Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern
analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation
for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns called:
core, edge, perforation, branch, connector and islet. Four forest maps were selected with different forest composition and configuration. The sensitivity of MSPA to scale was
studied by comparing frequencies of pattern classes in total forest area for various combinations of pixel size (P) and size
parameter (S). It was found that the quantification of forest pattern with MSPA is sensitive to scale. Differences in initial
composition and configuration influence the amount but not the general tendencies of the variations of morphological spatial
pattern (MSP) class proportions with scale. Increase of P led to data generalization resulting in either a removal of the
small size features or their potential transformation into other non-core MSP classes, while an increase of S decreases the
MSP core area and this process may transform small core areas into the MSP class islet. We established that the behavior of
the MSPA classes with changing scale can be categorized as consistent and robust scaling relations in the forms of linear,
power, or logarithmic functions over a range of scales. 相似文献
3.
Conservation of populations in fragmented habitats is often based on spatially realistic metapopulation theory, which predicts
negative relationships between patch extinction and area and patch colonization and isolation. Cost-distance metrics have
been developed to integrate habitat quality into measures of connectivity, and thus may improve predictive power of the area-isolation
paradigm. Few studies use empirical data to compare predictive performance of complex cost-distance metrics to simple metrics
relying on Euclidean distances. We used 3 years of presence–absence data to examine relative influence of habitat quality,
habitat area, and connectivity on occupancy and extinction rates for Poliocitellus franklinii (Franklin’s ground squirrel), a rare grassland species of conservation concern. We calculated connectivity using nearest-neighbor
(NN) and incidence function model (IFM) metrics based on Euclidean and cost-distances. Habitat quality, area, and connectivity
were all positive predictors for occupancy, but only isolation was a positive predictor of extinction. P. franklinii does not appear to be a tallgrass prairie obligate, but the species distribution is limited by isolation of suitable grassland
habitat. A simple NN metric measuring Euclidean distance between a target area and nearest occupied source outperformed IFM
(Euclidean and cost-distance) in predicting occupancy and extinction for P. franklinii. Although NN metrics are criticized for considering only the contribution of the source nearest to a target, this simplicity
may be acceptable when measuring connectivity for rare species with few occupied habitat patches within dispersal distance. 相似文献
4.
Current global trends in lake dissolved organic carbon (DOC) concentrations suggest a need for tools to more broadly measure
and predict variation in DOC at regional landscape scales. This is particularly true for more remote subalpine and alpine
regions where access is difficult and the minimal levels of anthropogenic watershed disturbance allow these systems to serve
as valuable reference sites for long-term climate change. Here geographic information system (GIS) and remote sensing tools
are used to develop simple predictive models that define relationships between watershed variables known to influence lake
DOC concentrations and lake water color in the Absaroka-Beartooth Wilderness in Montana and Wyoming, USA. Variables examined
include watershed area, topography, and vegetation cover. The resulting GIS model predicts DOC concentrations at the lake
watershed scale with a high degree of accuracy ( R
2 = 0.92; P ≤ 0.001) by including two variables: vegetation coverage (representing sites of organic carbon fixation) and areas of low
slope (0–5%) within the watershed (wetland sites of DOC production). Importantly, this latter variable includes not only surficially
visible wetlands, but “cryptic” subsurface wetlands. Modeling with Advanced Land Imager satellite remote sensing data provided
a weaker relationship with water color and DOC concentrations ( R
2 = 0.725; P ≤ 0.001). Model extrapolation is limited by small sample sizes but these models show promise in predicting lake DOC in subalpine
and alpine regions. 相似文献
5.
The purpose of this study was to observe the effects of changing the grain (the first level of spatial resolution possible with a given data set) and extent (the total area of the study) of landscape data on observed spatial patterns and to identify some general rules for comparing measures obtained at different scales. Simple random maps, maps with contagion ( i.e., clusters of the same land cover type), and actual landscape data from USGS land use (LUDA) data maps were used in the analyses. Landscape patterns were compared using indices measuring diversity ( H), dominance ( D) and contagion ( C). Rare land cover types were lost as grain became coarser. This loss could be predicted analytically for random maps with two land cover types, and it was observed in actual landscapes as grain was increased experimentally. However, the rate of loss was influenced by the spatial pattern. Land cover types that were clumped disappeared slowly or were retained with increasing grain, whereas cover types that were dispersed were lost rapidly. The diversity index decreased linearly with increasing grain size, but dominance and contagion did not show a linear relationship. The indices D and C increased with increasing extent, but H exhibited a variable response. The indices were sensitive to the number ( m) of cover types observed in the data set and the fraction of the landscape occupied by each cover type ( P
k); both m and P
kvaried with grain and extent. Qualitative and quantitative changes in measurements across spatial scales will differ depending on how scale is defined. Characterizing the relationships between ecological measurements and the grain or extent of the data may make it possible to predict or correct for the loss of information with changes in spatial scale. 相似文献
6.
This paper addresses the challenge of measuring spatial heterogeneity in categorical map data. Spatial heterogeneity is a
complex notion that involves both spatial variability and attribute variability, and metrics to capture this are a product
of their developers’ simplifying assumptions about both spatial and attribute dimensions. We argue that the predominantly
binary treatment of categorical data is frequently an unnecessary oversimplification that can be replaced by ordered measures
based on semantic similarity evaluations. We develop a typology of autocorrelation metrics for categorical data that identifies
a critical gap: existing measures are limited in their ability to capture variability of both spatial and attribute dimensions
simultaneously. We demonstrate an approach to formally characterize the semantic similarity between pairs of categorical data
classes as a continuous numeric variable. A series of experiments on synthetic and actual land cover data contrasts the information
content provided by metrics representative of all portions of the typology: the recently proposed semantic variogram, the
indicator variogram, the contagion index, and the edge contrast index. Experimental results suggest that the typology captures
essential qualities of metric information richness. Among our findings is that the commonly used contagion index is directly
correlated with Moran’s I for 2-class maps but it fails to distinguish between negatively and positively autocorrelated patterns.
We identify the semantic variogram as the only metric that can simultaneously detect both spatial and semantic attribute aspects
of categorical autocorrelation. The semantic variogram is also relatively robust to attribute scale changes and therefore
less sensitive to class aggregation than the other metrics. 相似文献
7.
We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover
pattern is classified as ‘perforated,’ ‘edge,’ ‘patch,’ and ‘core’ with higher spatial precision and thematic accuracy compared
to a previous approach based on image convolution, while retaining the capability to label these features at the pixel level
for any scale of observation. The implementation of morphological image processing is explained and then demonstrated, with
comparisons to results from image convolution, for a forest map of the Val Grande National Park in North Italy. 相似文献
8.
Landscape composition and configuration, often termed as habitat loss and fragmentation, are predicted to reduce species population
viability, partly due to the restriction of movement in the landscape. Unfortunately, measuring the effects of habitat loss
and fragmentation on functional connectivity is challenging because these variables are confounded, and often the motivation
for movement by target species is unknown. Our objective was to determine the independent effects of landscape connectivity
from the perspective of a mature forest specialist—the northern flying squirrel ( Glaucomys sabrinus). To standardize movement motivation, we translocated 119 squirrels, at varying distances (0.18–3.8 km) from their home range
across landscapes representing gradients in both habitat loss and fragmentation. We measured the physical connectedness of
mature forest using an index of connectivity (landscape coincidence probability). Patches were considered connected if they
were within the mean gliding distance of a flying squirrel. Homing success increased in landscapes with a higher connectivity
index. However, homing time was not strongly predicted by habitat amount, connectivity index, or mean nearest neighbour and
was best explained as a simple function of sex and distance translocated. Our study shows support for the independent effects
of landscape configuration on animal movement at a spatial scale that encompasses several home ranges. We conclude that connectivity
of mature forest should be considered for the conservation of some mature forest specialists, even in forest mosaics where
the distinction between habitat and movement corridors are less distinct. 相似文献
9.
Mathematical morphology encompasses methods for characterizing land-cover patterns in ecological research and biodiversity
assessments. This paper reports a neutral model analysis of patterns in the absence of a structuring ecological process, to
help set standards for comparing and interpreting patterns identified by mathematical morphology on real land-cover maps.
We considered six structural classes (core, perforated, edge, connector, branch, and patch) on randomly generated binary (forest,
non-forest) maps in which the percent occupancy (P) of forest varied from 1% to 99%. The maps were dominated by the patch
class for low P, by the branch and connector classes for intermediate P, and by the edge, perforated, and core classes for
high P. Two types of pattern phase changes were signaled by abrupt transitions among the six structural classes, at critical
P thresholds that were indicated by increased variance among maps for the same P. A phase change from maps dominated by the
patch class to maps dominated by the branch and connector classes was related to the existence of a percolating cluster of
forest, and the P threshold varied depending on the co-existence of the core class. A second phase change from the edge class
to the perforated class was related to the existence of a percolating cluster of non-core (including non-forest) and represents
a change of context from exterior to interior. Our results appear to be the first demonstration of multiple phase changes
controlling different aspects of landscape pattern on random neutral maps. Potential applications of the results are illustrated
by an analysis of ten real forest maps.
The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged. 相似文献
10.
The focus of biodiversity conservation is shifting to larger spatial scales in response to habitat fragmentation and the need
to integrate multiple landscape objectives. Conservation strategies increasingly incorporate measures to combat fragmentation
such as ecological networks. These are often based on assessment of landscape structure but such approaches fail to capitalise
on the potential offered by more ecologically robust assessments of landscape function and connectivity. In this paper, we
describe a modelling approach to identifying functional habitat networks and demonstrate its application to a fragmented landscape
where policy initiatives seek to improve conditions for woodland biodiversity including increasing woodland cover. Functional
habitat networks were defined by identifying suitable habitat and by modelling connectivity using least-cost approaches to
account for matrix permeability. Generic focal species (GFS) profiles were developed, in consultation with stakeholders, to
represent species with high and moderate sensitivity to fragmentation. We demonstrated how this form of analysis can be used
to aid the spatial targeting of conservation actions. This ‘targeted’ action scenario was tested for effectiveness against
comparable scenarios, which were based on random and clumped actions within the same landscape. We tested effectiveness using
structural metrics, network-based metrics and a published functional connectivity indicator. Targeting actions within networks
resulted in the highest mean woodland area and highest connectivity indicator value. Our approach provides an assessment of
landscape function by recognising the importance of the landscape matrix. It provides a framework for the targeting and evaluation
of alternative conservation options, offering a pragmatic, ecologically-robust solution to a current need in applied landscape
ecology. 相似文献
11.
ContextConservation for the Indiana bat (Myotis sodalis), a federally endangered species in the United States of America, is typically focused on local maternity sites; however, the species is a regional migrant, interacting with the environment at multiple spatial scales. Hierarchical levels of management may be necessary, but we have limited knowledge of landscape-level ecology, distribution, and connectivity of suitable areas in complex landscapes. ObjectivesWe sought to (1) identify factors influencing M. sodalis maternity colony distribution in a mosaic landscape, (2) map suitable maternity habitat, and (3) quantify connectivity importance of patches to direct conservation action. MethodsUsing 3 decades of occurrence data, we tested a priori, hypothesis-driven habitat suitability models. We mapped suitable areas and quantified connectivity importance of habitat patches with probabilistic habitat availability metrics. ResultsFactors improving landscape-scale suitability included limited agriculture, more forest cover, forest edge, proximity to medium-sized water bodies, lower elevations, and limited urban development. Areas closer to hibernacula and rivers were suitable. Binary maps showed that 30% of the study area was suitable for M. sodalis and 29% was important for connectivity. Most suitable patches were important for intra-patch connectivity and far fewer contributed to inter-patch connectivity. ConclusionsWhile simple models may be effective for small, homogenous landscapes, complex models are needed to explain habitat suitability in large, mixed landscapes. Suitability modeling identified factors that made sites attractive as maternity areas. Connectivity analysis improved our understanding of important areas for bats and prioritized areas to target for restoration. 相似文献
12.
Landscape metric scalograms (the response curves of landscape metrics to changing grain size) have been used to illustrate the scale effects of metrics for real landscapes. However, whether they detect the characteristic scale of hierarchically structured landscapes remains uncertain. To address this question, the scalograms of 26 class-level metrics were systematically examined for a simple random landscape, seven hierarchical neutral landscapes, and the real landscape of the Xilin River Basin of Inner Mongolia, China. The results show that when the fraction of the focal patch type (P) is below a critical value (P
c), most metric scalograms are sensitive to change in single-scale and lower-level hierarchical structure and insensitive to change in higher-level hierarchical structure. The scalograms of only a few metrics measuring spatial aggregation and connectedness are sensitive to change in intermediate-level hierarchical structure. Most metric scalograms explicitly identify the characteristic scale of a single-scale landscape and fine or intermediate characteristic scales of a multi-scale landscape for both simulated and real landscapes. When P exceeds P
c, only some metrics detect scale and change in structure. The scalograms of total class area and Euclidean nearest-neighbor distance cannot detect scale or change in structure in either case. Landscape metric scalograms are useful for addressing scale issues, including illustrating the scale effects of spatial patterns, detecting multi-scale patterns, and developing possible scaling relations. 相似文献
13.
ContextMany connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity. ObjectivesA number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results. MethodsThe behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (meff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity. ResultsWe found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using meff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT. ConclusionsApplying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes. 相似文献
14.
Habitat fragmentation is expected to disrupt dispersal, and thus we explored how patch metrics of landscape structure, such as percolation thresholds used to define landscape connectivity, corresponded with dispersal success on neutral landscapes. We simulated dispersal as either a purely random process (random direction and random step lengths) or as an area-limited random walk (random direction, but movement limited to an adjacent cell at each dispersal step) and quantified dispersal success for 1000 individuals on random and fractal landscape maps across a range of habitat abundance and fragmentation. Dispersal success increased with the number of cells a disperser could search (m), but poor dispersers (m<5) searching via area-limited dispersal on fractal landscapes were more successful at locating suitable habitat than random dispersers on either random or fractal landscapes. Dispersal success was enhanced on fractal landscapes relative to random ones because of the greater spatial contagion of habitat. Dispersal success decreased proportionate to habitat loss for poor dispersers (m=1) on random landscapes, but exhibited an abrupt threshold at low levels of habitat abundance (p<0.1) for area-limited dispersers (m<10) on fractal landscapes. Conventional metrics of patch structure, including percolation, did not exhibit threshold behavior in the region of the dispersal threshold. A lacunarity analysis of the gap structure of landscape patterns, however, revealed a strong threshold in the variability of gap sizes at low levels of habitat abundance (p<0.1) in fractal landscapes, the same region in which abrupt declines in dispersal success were observed. The interpatch distances or gaps across which dispersers must move in search of suitable habitat should influence dispersal success, and our results suggest that there is a critical gap-size structure to fractal landscapes that interferes with the ability of dispersers to locate suitable habitat when habitat is rare. We suggest that the gap structure of landscapes is a more important determinant of dispersal than patch structure, although both are ultimately required to predict the ecological consequences of habitat fragmentation. 相似文献
15.
Two stochastic model formulations, one using pixel-based transitions and the other patch-based, were compared by running simulations where the amount of information on which transitions were based was increased. Both model types adequately represented changes in the proportion of the landscape occupied by different land cover types. However, the pixel-based model underestimated contagion and overestimated the amount of edge. The patch-based model overestimated contagion and underestimated edge. Overall, the estimates more closely approximated the expected and the variances decreased as more information was added to the models. As expected, the model that most closely simulated the spatial pattern of the landscape was a 5-data-layer patch-based model that also included ownership boundaries as an additional layer. The simulation methods described provide a means to integrate socioeconomic and ecological information into a spatially-explicit transition model of landscape change and to simulate change at a scale similar to that occurring in a landscape. 相似文献
16.
This paper documents the analyses that were conducted with regards to investigating an appropriate Minimum Mapping Unit (MMU)
to be used to capture the potential changes in vegetation patterns for a 10,924 square km restoration project being conducted
in south Florida, USA. Spatial landscape and class metrics that were shown to change predictably with increasing grain size
were adopted from previous studies and applied to a multi-scale analysis. Specifically, this study examines the effects of
changing grain size on landscape metrics, utilizing empirical data from a real landscape encompassing 234,913 ha of south
Florida’s Everglades. The objective was to identify critical thresholds within landscape metrics, which can be used to provide
insight in determining an appropriate MMU for vegetation mapping. Results from this study demonstrate that vegetation heterogeneity
will exhibit dissimilar patterns when investigating the loss of information within landscape and class metrics, as grain size
is increased. These results also support previous findings that suggest that landscape metric “scalograms” (the response curves
of landscape metrics to changing grain size), are more likely to be successful for linking landscape pattern to ecological
processes as both pattern and process in ecological systems often operate on multiple scales. This study also incorporates
an economic cost for various grain dependant vegetation mapping scales. A final selection of the 50 × 50 m grain size for
mapping vegetation was based on this study’s investigation of the “scalograms”, the costs, and a composite best professional
judgment of seasoned scientists having extensive experience within these ecosystems. 相似文献
17.
To understand how urbanization has transformed the desert landscape in the central Arizona – Phoenix region of the United States, we conducted a series of spatial analyses of the land-use pattern from 1912–1995. The results of the spatial analysis show that the extent of urban area has increased exponentially for the past 83 years, and this urban expansion is correlated with the increase in population size for the same period of time. The accelerating urbanization process has increased the degree of fragmentation and structural complexity of the desert landscape. To simulate land-use change we developed a Markov-cellular automata model. Model parameters and neighborhood rules were obtained both empirically and with a modified genetic algorithm. Land-use maps for 1975 and 1995 were used to implement the model at two distinct spatial scales with a time step of one year. Model performance was evaluated using Monte-Carlo confidence interval estimation for selected landscape pattern indices. The coarse-scale model simulated the statistical patterns of the landscape at a higher accuracy than the fine-scale model. The empirically derived parameter set poorly simulated land-use change as compared to the optimized parameter set. In summary, our results showed that landscape pattern metrics (patch density, edge density, fractal dimension, contagion) together were able to effectively capture the trend in land-use associated with urbanization for this region. The Markov-cellular automata parameterized by a modified genetic algorithm reasonably replicated the change in land-use pattern. 相似文献
18.
Investigations of land-cover change often employ metrics designed to quantify changes in landscape structure through time,
using analyses of land cover maps derived from the classification of remote sensing images from two or more time periods.
Unfortunately, the validity of these landscape pattern analyses (LPA) can be compromised by the presence of spurious change, i.e., differences between map products caused by classification error rather than real changes on the ground. To reduce
this problem, multi-temporal time series of land-cover maps can be constructed by updating (projecting forward in time) and
backdating (projecting backward in time) an existing reference map, wherein regions of change are delineated through bi-temporal
change analysis and overlaid onto the reference map. However, this procedure itself creates challenges, because sliver patches can occur in cases where the boundaries of the change regions do not exactly match the land-cover patches in the reference
map. In this paper, we describe how sliver patches can inadvertently be created through the backdating and updating of land-cover
maps, and document their impact on the magnitude and trajectory of four popular landscape metrics: number of patches (NP),
edge density (ED), mean patch size (MPS), and mean shape index (MSI). In our findings, sliver patches led to significant distortions
in both the value and temporal behaviour of metrics. In backdated maps, these distortions caused metric trajectories to appear
more conservative, suggesting lower rates of change for ED and inverse trajectories for NP, MPS and MSI. In updated maps,
slivers caused metric trajectories to appear more extreme and exaggerated, suggesting higher rates of change for all four
metrics. Our research underscores the need to eliminate sliver patches from any study dealing with multi-temporal LPA. 相似文献
19.
Uncertainty in managing forested landscapes arises from many sources, including complexities inherent in forest ecosystems
and their disturbance processes. However, gaining knowledge about forested ecosystems at the landscape level is often impeded
by limitations in collecting comprehensive, representative, as well as accurate data sets. Historical reference data sets
about past disturbances are also mostly lacking. In the case of ground fires, however, records of past fires can be obtained
by analyzing fire scars using dendrochronology. While the temporal series of disturbance can be determined, there is still
uncertainty about the spatial limits of individual forest surface fires. Here, we investigate how a patch-based method (fuzzy
set membership) and a boundary-based uncertainty method (boundary membership) can help determine the spatial uncertainty related
to forest fire events and their boundary locations. We compare these methods using fire scar data from ponderosa pine ( Pinus ponderosa) and Douglas-fir ( Pseudotsuga menziesii) sampled at 33 1-ha plots in a 1500-ha study area within the Stein River watershed (British Columbia). Patch-based fire maps,
using multiple constraints, were derived for years 1785–1937. We compared the resulting total fire event maps with the boundary-based
method, finding that depending on values chosen for the patch-based method, negative correlation was present (though very
modest: r = − 0.1, p ≤ 0.05) between some maps. However, significant positive correlation between maps (though again modest: r = 0.22, p ≤ 0.05) was found under the least constrained patch-based methods, suggesting that fire patches are counted more than once
in riparian zones. Our results suggest that these two methods provide complementary information about historical fire size
and spatial limits. Quantifying spatial uncertainty about fire size and fire boundary location using a boundary membership
method can contribute to not only understanding past fire regimes but also to providing better estimates of area burned. 相似文献
20.
We identified primary habitat and functional corridors across a landscape using Global Positioning System (GPS) collar locations
of brown bears ( Ursus arctos). After deriving density, speed, and angular deviation of movement, we classified landscape function for a group of animals
with a cluster analysis. We described areas with high amounts of sinuous movement as primary habitat patches and areas with
high amounts of very directional, fast movement as highly functional bear corridors. The time between bear locations and scale
of analysis influenced the number and size of corridors identified. Bear locations should be collected at intervals ≤6 h to
correctly identify travel corridors. Our corridor identification technique will help managers move beyond the theoretical
discussion of corridors and linkage zones to active management of landscape features that will preserve connectivity. 相似文献
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