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1.
Ramesh Krishnamurthy Samuel A. Cushman Mriganka S. Sarkar Manjari Malviya Moorthy Naveen Jeyaraj A. Johnson Subharanjan Sen 《Landscape Ecology》2016,31(6):1355-1368
Context
Connectivity models for animal movement frequently use resistance surfaces, but rarely incorporate actual movement data and multiple scale drivers of landscape resistance.Objectives
Using GPS data, we developed a multi-scale model of landscape resistance for tiger (Panthera tigris) dispersal in central India and evaluated the performance, interpretation and predictions against single scale models.Methods
Six dispersing tiger paths were subjected to a path level analysis with conditional logistic regression to parameterize a resistance surface. We evaluated for 21 scales of available habitat and selected the best scale for each variable. We derived a scale-optimized multivariate path selection function and predicted landscape resistance across the landscape.Results
The tigers preferred to move along areas with forest cover at relatively high elevations along the ridges with rugged topography at broad scale, while avoiding areas with agriculture-village matrix at fine scale. We found that the scale that was most supported by Akaike’s information criterion was not always the scale that maximized the magnitude (effect size) of the relationship. Further, the multi-scale optimized model differed substantially from the single scale models in terms of variable importance, magnitude of coefficients and predictions of connectivity.Conclusions
Our results demonstrate that the variables in landscape resistance models produce markedly different predictions of population connectivity depending on the scales of analyses and interpretation. Thus, scale optimization in parameterization is critical for appropriate inferences and sound management strategies.2.
Context
In response to predominantly local and private approaches to landscape change, landscape ecologists should critically assess the multiscalar influences on landscape design.Objectives
This study develops a governance framework for Nassauer and Opdam’s “Design-in-Science” model. Its objective is to create an approach for examining hierarchical constraints on landscape design in order to investigate linkages among urban greening initiatives, patterns of landscape change, and the broader societal values driving those changes. It aims to provide an integrative and actionable approach for landscape sustainability science.Methods
This framework is examined through an ethnographic study of public policy processes surrounding the urban tree initiatives in Boston, MA; Philadelphia, PA; and Baltimore, MD.Results
These initiatives demonstrate the impact of political and economic decentralization on urban landscape patterns. Their collaborative governance approach incorporates diverse resources to implement programming at a fine-scale. The predominant tree giveaway program fragments the urban and regional forest.Conclusion
Spatial and temporal fragmentation undermines the long-term security of urban greening programs, and it suggests reconsideration of the role of state regimes in driving broad scale spatial planning.3.
Context
Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering approach does not acknowledge that the influence of surrounding landscape features should diminish with distance, and it does not yield an estimate of the unknown scale parameters.Objectives
The purpose of this paper is to present an approach that allows for statistical inference about the scales at which landscape variables affect abundance.Methods
Our method uses smoothing kernels to average landscape variables around focal sites and uses maximum likelihood to estimate the scale parameters of the kernels and the effects of the smoothed variables on abundance. We assessed model performance using a simulation study and an avian point count dataset.Results
The simulation study demonstrated that estimators are unbiased and produce correct confidence interval coverage except in the rare case in which there is little spatial autocorrelation in the landscape variable. Canada warbler abundance was more highly correlated with site-level measures of NDVI than landscape-level NDVI, but the reverse was true for elevation. Canada warbler abundance was highest when elevation in the surrounding landscape, defined by an estimated Gaussian kernel, was between 1300 and 1400 m.Conclusions
Our method provides a rigorous way of formally estimating the scales at which landscape variables affect abundance, and it can be embedded within most classes of statistical models.4.
Paul Miguet Heather B. Jackson Nathan D. Jackson Amanda E. Martin Lenore Fahrig 《Landscape Ecology》2016,31(6):1177-1194
Context
Landscape ecologists are often interested in measuring the effects of an environmental variable on a biological response; however, the strength and direction of effect depend on the size of the area within which the environmental variable is measured. Thus a central objective is to identify the optimal spatial extent within which to measure the environmental variable, i.e. the “scale of effect”.Objectives
Our objectives are (1) to provide a comprehensive summary of the hypotheses concerning what determines the scale of effect, (2) to provide predictions that can be tested in empirical studies, and (3) to show, with a review of the literature, that most of these predictions have so far been inadequately tested.Methods
We propose 14 predictions derived from five hypotheses explaining what determines the scale of effect, and review the literature (if any) supporting each prediction. These predictions involve five types of factors: (A) species traits, (B) landscape variables, (C) biological responses (e.g. abundance vs. occurrence), (D) indirect influences, and (E) regional context of the study. We identify methodological issues that hinder estimation of the scale of effect.Results
Of the 14 predictions, only nine have been tested empirically and only five have received some empirical support. Most support is from simulation studies. Empirical evidence usually does not support predictions.Conclusions
The study of the spatial scale at which landscape variables influence biological outcomes is in its infancy. We provide directions for future research by clarifying predictions concerning the determinants of the scale of effect.5.
Surface metrics for landscape ecology: a comparison of landscape models across ecoregions and scales
Peter J. Kedron Amy E. Frazier Gustavo A. Ovando-Montejo Jing Wang 《Landscape Ecology》2018,33(9):1489-1504
Context
The patch-mosaic model is lauded for its conceptual simplicity and ease with which conventional landscape metrics can be computed from categorical maps, yet many argue it is inconsistent with ecological theory. Gradient surface models (GSMs) are an alternative for representing landscapes, but adoption of surface metrics for analyzing spatial patterns in GSMs is hindered by several factors including a lack of meaningful interpretations.Objectives
We investigate the performance and applicability of surface metrics across a range of ecoregions and scales to strengthen theoretical foundations for their adoption in landscape ecology.Methods
We examine metric clustering across scales and ecoregions, test correlations with patch-based metrics, and provide ecological interpretations for a variety of surface metrics with respect to forest cover to support the basis for selecting surface metrics for ecological analyses.Results
We identify several factors complicating the interpretation of surface metrics from a landscape perspective. First, not all surface metrics are appropriate for landscape analyses. Second, true analogs between surface metrics and patch-based, landscape metrics are rare. Researchers should focus instead on how surface measures can uniquely measure spatial patterns. Lastly, scale dependencies exist for surface metrics, but relationships between metrics do not appear to change considerably with scale.Conclusions
Incorporating gradient surfaces into landscape ecological analyses is challenging, and many surface metrics may not have patch analogs or be ecologically relevant. For this reason, surface metrics should be considered in terms of the set of pattern elements they represent that can then be linked to landscape characteristics.6.
Kevin McGarigal Ho Yi Wan Kathy A. Zeller Brad C. Timm Samuel A. Cushman 《Landscape Ecology》2016,31(6):1161-1175
Context
Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.Objectives
Our goals in this review are to describe the conceptual origins of multi-scale habitat selection modeling, evaluate the current state-of-the-science, and suggest ways forward to improve analysis of scale-dependent habitat selection.Methods
We reviewed more than 800 papers on habitat selection from 23 major ecological journals published between 2009 and 2014 and recorded a number of characteristics, such as whether they addressed habitat selection at multiple scales, what attributes of scale were evaluated, and what analytical methods were utilized.Results
Our results show that despite widespread recognition of the importance of multi-scale analyses of habitat relationships, a large majority of published habitat ecology papers do not address multiple spatial or temporal scales. We also found that scale optimization, which is critical to assess scale dependence, is done in less than 5 % of all habitat selection modeling papers and less than 25 % of papers that address “multi-scale” habitat analysis broadly defined.Conclusions
Our review confirms the existence of a powerful conceptual foundation for multi-scale habitat selection modeling, but that the majority of studies on wildlife habitat are still not adopting multi-scale frameworks. Most importantly, our review points to the need for wider adoption of a formal scale optimization of organism response to environmental variables.7.
Context
Understanding how rare species are distributed can be difficult due to heterogeneity between landscape units. Lack of statistical replication of landscapes can make it difficult to carry out testing. Model systems may be a solution.Objectives
We test whether lichen thalli along the trunk of a tree are analogous to habitat patches in a kilometers-extent landscape and hence can function as a model system. This model system allows for increased statistical power. We use this system to test whether landscapes with rare species are different from those without.Methods
We sampled macrolichen diversity along the trunk of 24 balsam fir trees in a stand on the Avalon Peninsula, Newfoundland, Canada, along with microclimate variables. We analysed difference in pattern by aspect and along the gradient of 1 m up the trunk as well as between trees containing the rare Erioderma pedicellatum and those without.Results
We found no difference in total patch richness or abundance between the micro-landscapes. We found significantly consistent patterns in lichen patches along the trunk. These patterns were similar on the trees with the rare species. Lichen species richness did not differ between trees containing the rare species versus those that did not.Conclusions
Lichen patch pattern is statistically similar between trees and as such, these can be considered as replicate landscape units. Thus, landscape ecologists can use micro-landscapes as model systems to conduct observational and manipulative experiments to test questions about spatial pattern and process, such as those concerning distribution of rare species.8.
Context
An increasing number of studies have investigated the impact of environmental heterogeneity on faunal assemblages when measured at multiple spatial scales. Few studies, however, have considered how the effects of heterogeneity on fauna vary with the spatial scale at which the response variable is characterised.Objectives
We investigated the relationship between landscape properties in a region characterised by diverse fire mosaics, and the structure and composition of avian assemblages measured at both the site- (1 ha) and landscape-scale (100 ha).Methods
We surveyed birds and calculated spatial landscape properties in sub-tropical woodlands of central Queensland, Australia.Results
Environmental heterogeneity, as measured by topographic complexity, was consistently important for bird species richness and composition. However, the explanatory power of topographic complexity varied depending on the spatial scale and the component of diversity under investigation. We found different correlates of richness within particular foraging guilds depending on the scale at which richness was measured. Extent of long-unburnt habitat (>10 years since fire) was the most important variable for the landscape-scale richness of frugivores, insectivores and canopy feeders, whereas environmental heterogeneity in the surrounding landscape was more important for site-scale richness of these foraging guilds.Conclusions
The response of species richness to landscape characteristics varies among scales, and among components of diversity. Thus, depending on the scale at which a biodiversity conservation goal is conceptualised—maximising richness at a site, or across a landscape—different landscape management approaches may be preferred.9.
Context
Despite the key role of biological control in agricultural landscapes, we still poorly understand how landscape structure modulates pest control at different spatial scales.Objectives
Here we take an experimental approach to explore whether bird and bat exclusion affects pest control in sun coffee plantations, and whether this service is consistent at different spatial scales.Methods
We experimentally excluded flying vertebrates from coffee plants in 32 sites in the Brazilian Atlantic Forest, encompassing a gradient of forest cover at landscape (2 km radius) and local (300 m) spatial scales, and quantified coffee leaf loss, as an indicator of herbivory, and fruit set.Results
Leaf loss decreased with higher landscape forest cover, but this relation was significantly different between treatment and control plants depending on local forest cover. On the other hand, fruit set responded to the interaction between treatment and local forest cover but was not affected by landscape forest cover. More specifically, fruit set increased significantly with local forest cover in exclusion treatments and showed a non-significant decrease in open controls.Conclusions
These results suggest that services provided by flying vertebrates are modulated by processes occurring at different spatial scales. We posit that in areas with high local forest cover flying vertebrates may establish negative interactions with predaceous arthropods (i.e. intraguild predation), but this would not be the case in areas with low local forest cover. We highlight the importance of employing a multi-scale analysis in systems where multiple species, which perceive the landscape differently, are providing ecosystem services.10.
Hilda A. Sánchez-de-Jesús Víctor Arroyo-Rodríguez Ellen Andresen Federico Escobar 《Landscape Ecology》2016,31(4):843-854
Context
Identifying the drivers shaping biological assemblages in fragmented tropical landscapes is critical for designing effective conservation strategies. It is still unclear, however, whether tropical biodiversity is more strongly affected by forest loss, by its spatial configuration or by matrix composition across different spatial scales.Objectives
Assessing the relative influence of forest patch and landscape attributes on dung beetle assemblages in the fragmented Lacandona rainforest, Mexico.Methods
Using a multimodel inference approach we tested the relative impact of forest patch size and landscape forest cover (measures of forest amount at the patch and landscape scales, respectively), patch shape and isolation (forest configuration indices at the patch scale), forest fragmentation (forest configuration index at the landscape scale), and matrix composition on the diversity, abundance and biomass of dung beetles.Results
Patch size, landscape forest cover and matrix composition were the best predictors of dung beetle assemblages. Species richness, beetle abundance, and biomass decreased in smaller patches surrounded by a lower percentage of forest cover, and in landscapes dominated by open-area matrices. Community evenness also increased under these conditions due to the loss of rare species.Conclusions
Forest loss at the patch and landscape levels and matrix composition show a larger impact on dung beetles than forest spatial configuration. To preserve dung beetle assemblages, and their key functional roles in the ecosystem, conservation initiatives should prioritize a reduction in deforestation and an increase in the heterogeneity of the matrix surrounding forest remnants.11.
Hugo Valls-Fox Michel De Garine-Wichatitsky Hervé Fritz Simon Chamaillé-Jammes 《Landscape Ecology》2018,33(1):127-140
Context
The spatial distribution of non-substitutable resources implies diverging predictions for animal movement patterns. At broad scales, animals should respond to landscape complementation by selecting areas where resource patches are close-by to minimize movement costs. Yet at fine scales, central place effects lead to the depletion of patches that are close to one another and that should ultimately be avoided by consumers.Objectives
We developed a multi-scale resource selection framework to test whether animal movement is driven by landscape complementation or resource depletion and identify at which spatial scale these processes are relevant from an animal’s perspective.Methods
During the dry season, surface water and forage are non-substitutable resources for African elephants. Eight family herds were tracked using GPS loggers in Hwange National Park, Zimbabwe. We explained habitat selection during foraging trips by mapping surface water at two scales with gaussian kernels of varying widths placed over each waterhole.Results
Unexpectedly, elephants select areas with low waterhole density at both fine scales (< 1 km) and broad scales (5–7 km). Selection is stronger when elephants forage far away from water, even more so as the dry season progresses.Conclusions
Elephant selection of low waterhole density areas suggests that resource depletion around multiple central places is the main driver of their habitat selection. By identifying the scale at which animals respond to waterhole distribution we provide a template for water management in arid and semi-arid landscapes that can be tailored to match the requirements and mobility of free ranging wild or domestic species.12.
Joshua R. van Lier Shaun K. Wilson Martial Depczynski Lucy N. Wenger Christopher J. Fulton 《Landscape Ecology》2018,33(8):1287-1300
Context
In heterogeneous landscapes, local patterns of community structure are a product of the habitat size and condition within a patch interacting with adjacent habitat patches of varying composition and quantity. While evidence for local versus landscape factors have been found in terrestrial biomes, support for such multi-scale effects shaping marine ecological communities is equivocal.Objectives
We investigated whether within-patch habitat condition can override seascape context to explain the community structure of macroalgae-associated reef fishes across a tropical seascape.Methods
We mapped the distribution and abundance of a diverse family of reef fishes (Labridae) occupying macroalgae meadows within a tropical reef ecosystem, and using best-subsets model selection, investigated the potential for habitat structural connectivity and/or local habitat quality for predicting variations in fish community structure across the seascape.Results
Local habitat quality (canopy structure, hard habitat complexity) and area of coral-dominated habitat within 500 m of a macroalgal meadow provided the best predictors of fish community structure. However, the specific importance of a given predictor varied with fish life history stage and functional trophic group. Interestingly, macroalgae meadow area was among the least important predictors.Conclusions
Given the complex interplay between local habitat quality and spatial context effects on fish biodiversity, our study reveals the multi-scale predictors that should be used in spatial conservation and management approaches for tropical fish diversity. Moreover, our findings question the ubiquity of habitat area effects in patchy landscapes, and cautions against a sole reliance on habitat quantity in spatial management.13.
Christina A. Buelow Ronald Baker April E. Reside Marcus Sheaves 《Landscape Ecology》2017,32(3):547-561
Context
Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation.Objectives
This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales.Methods
Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12 km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis.Results
Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale.Conclusions
Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales.14.
Xia-li Luan Alexander Buyantuev Albert Hans Baur Birgit Kleinschmit Haijun Wang Sheng Wei Maosong Liu Chi Xu 《Landscape Ecology》2018,33(7):1211-1224
Context
Emissions of greenhouse gases in urban areas play an important role in climate change. Increasing attention has been given to urban landscape structure–emission relationships (SERs). However, it remains unknown if and to what extent SERs are dependent on observational scale.Objective
To assess how changing observational scales (in terms of spatial and thematic resolutions) of urban landscape structure affect SERs.Methods
We examined correlations between 16 landscape metrics and greenhouse gas emissions across 52 European cities, through (1) systematic manipulation of spatial and thematic resolutions of the urban land use/cover (ULUC) dataset, and (2) comparison between available standard ULUC datasets with different spatial resolutions.Results
Our analyses showed that the observed SERs significantly depend on both thematic and spatial resolutions of the ULUC data. For the 16 landscape metrics, we found diverse spatial/thematic scaling relations exhibiting monotonic, hump-shaped or scale-invariant trends. For different landscape metrics, the SERs were strongest at different spatial scales, suggesting that there is no consistent scaling relation over those observational scales.Conclusions
SERs are highly sensitive to spatial and thematic resolutions of landscape data. To avoid the problem of ‘ecological fallacy,’ important caveats should be taken for interpretations based on single landscape metrics. Particular consideration should be paid to metrics that are easily interpretable, predictable in scaling behaviors, and important for shaping SERs, such as PLAND, ED, and LPI. Systematic investigations on scaling behaviors of SERs over well-defined scale domains are encouraged in future studies linking greenhouse gas emissions and urban landscape structure.15.
Context
Large datasets that exhibit residual spatial autocorrelation are common in landscape ecology, introducing issues with model inference. Computationally intensive statistical techniques such as simultaneous autoregression (SAR) are used to provide credible inference, yet landscape studies make choices about autocorrelation structure and data reduction techniques without adequate understanding of the consequences for model estimation and inference.Objectives
Our goal is to understand the effects of misspecification of neighborhood size, subsampling, and data partitioning on SAR estimation and inference.Methods
We use remotely sensed burn severity for a large wildfire in north-central Washington State as a case study. First we estimate SAR for remotely sensed burn severity data at multiple subsampling intensities, data partitions, and neighborhood distances. Second, we simulate landscape burn severity data with SAR errors and calculate type I error rates for SAR estimated at the simulation neighborhood distance, and at misspecified neighborhood distances.Results
Subsampling and misspecification of the neighborhood result in spurious inference and modified coefficient estimates. Type I error rates are close to the specified α-level when the model is estimated at both the simulation neighborhood and the distance that minimizes AIC.Conclusions
By evaluating the effectiveness of pre-burn fuel reduction treatments on subsequent wildfire burn severity, we demonstrate that misspecification of the neighborhood distance and subsampling the data compromises inference and estimation. Using AIC to choose the neighborhood distance provides type I error rates near the stated α-level in simulated data.16.
17.
Context
How do young birds achieve spatial knowledge about the environment during the initial stages of their life? They may follow adults, so gaining social information and learning; alternatively, young birds may acquire knowledge of the environment themselves by experiencing habitat and landscape features. If learning is at least partially independent of adults then young birds should respond to landscape composition at finer spatial scale than adults, who possess knowledge over a larger area.Objectives
We studied the responses of juvenile, immature and adult Caspian Gull Larus cachinnans to the same habitat and landscape variables, but at several spatial scales (ranging from 2.5 to 15 km), during post-breeding period.Methods
We surveyed 61 fish ponds (foraging patches) in southern Poland and counted Caspian gulls.Results
Juvenile birds responded at finer spatial scales to the factors than did adults. Immature birds showed complicated, intermediate responses to spatial scale. The abundance of juvenile birds was mostly correlated with the landscape composition (positively with the cover of corridors and negatively with barriers). Adult abundance was positively related to foraging patch quality (fish stock), which clearly required previous spatial experience of the environment. The abundance of all age classes were moderately correlated with each other indicating that social behaviour may also contribute to the learning of the environment.Conclusions
This study shows that as birds mature, they respond differently to components of their environment at different spatial scales. This has considerable ecological consequences for their distribution across environments.18.
Julie Betbeder Marianne Laslier Laurence Hubert-Moy Françoise Burel Jacques Baudry 《Landscape Ecology》2017,32(9):1867-1879
Context
The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.Objectives
The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).Methods
We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.Results
We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.Conclusions
Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.19.
Carol L. Chambers Samuel A. Cushman Arnulfo Medina-Fitoria José Martínez-Fonseca Marlon Chávez-Velásquez 《Landscape Ecology》2016,31(6):1299-1318
Context
Scale dependence of bat habitat selection is poorly known with few studies evaluating relationships among landscape metrics such as class versus landscape, or metrics that measure composition or configuration. This knowledge can inform conservation approaches to mitigate habitat loss and fragmentation.Objectives
We evaluated scale dependence of habitat associations and scaling patterns of landscape metrics in relation to bat occurrence or capture rate in forests of southwestern Nicaragua.Methods
We captured 1537 bats at 35 locations and measured landscape and class metrics across 10 spatial scales (100–1000 m) surrounding capture locations. We conducted univariate scaling across the 10 scales and identified scales and variables most related to bat occurrence or capture rate.Results
Edge and patch density, at both landscape and class levels, were the most important variables across species. Feeding guilds varied in their response to metrics. Certain landscape and configuration metrics were most influential at fine (100 m) and/or broad (1000 m) spatial scales while most class and composition metrics were influential at intermediate scales.Conclusions
These results provide insight into the scale dependence of habitat associations of bat species and the influence of fine and broad scales on habitat associations. The effects of scale, examined in our study and others from fine (100 m) to broad (5 km) indicate habitat relationships for bats may be more informative at larger scales. Our results suggest there could be general differences in scale relationships for different groups of landscape metrics, which deserves further evaluation in other taxonomic groups.20.