Influence of high-resolution data on the assessment of forest fragmentation

Context

Remote sensing has been a foundation of landscape ecology. The spatial resolution (pixel size) of remotely sensed land cover products has improved since the introduction of landscape ecology in the United States. Because patterns depend on spatial resolution, emerging improvements in the spatial resolution of land cover may lead to new insights about the scaling of landscape patterns.

Objective

We compared forest fragmentation measures derived from very high resolution (1 m²) data with the same measures derived from the commonly used (30 m?×??30 m; 900 m²) Landsat-based data.

Methods

We applied area-density scaling to binary (forest; non-forest) maps for both sources to derive source-specific estimates of dominant (density ≥?60%), interior (≥?90%), and intact (100%) forest.

Results

Switching from low- to high-resolution data produced statistical and geographic shifts in forest spatial patterns. Forest and non-forest features that were “invisible” at low resolution but identifiable at high resolution resulted in higher estimates of dominant and interior forest but lower estimates of intact forest from the high-resolution source. Overall, the high-resolution data detected more forest that was more contagiously distributed even at larger spatial scales.

Conclusion

We anticipate that improvements in the spatial resolution of remotely sensed land cover products will advance landscape ecology through re-interpretations of patterns and scaling, by fostering new landscape pattern measurements, and by testing new spatial pattern-ecological process hypotheses.

     

Motif: an open-source R tool for pattern-based spatial analysis

Context

Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns.

Objectives

We developed an R package motif as a set of open-source tools for pattern-based spatial analysis.

Methods

This package provides most of the functionality of existing software (except spatial segmentation), but also extends the existing ideas through support for multi-layer raster datasets. It accepts larger-than-RAM datasets and works across all of the major operating systems.

Results

In this study, we describe the software design of the tool, its capabilities, and present four case studies. They include calculation of spatial signatures based on land cover data for regular and irregular areas, search for regions with similar patterns of geomorphons, detection of changes in land cover patterns, and clustering of areas with similar spatial patterns of land cover and landforms.

Conclusions

The methods implemented in motif should be useful in a wide range of applications, including land management, sustainable development, environmental protection, forest cover change and urban growth monitoring, and agriculture expansion studies. The motif package homepage is https://nowosad.github.io/motif.

     

Landscape composition is the strongest determinant of bird occupancy patterns in tropical forest patches

Context

Biodiversity in tropical region has declined in the last decades, mainly due to forest conversion into agricultural areas. Consequently, species occupancy in these landscapes is strongly governed by environmental changes acting at multiple spatial scales.

Objectives

We investigated which environmental predictors best determines the occupancy probability of 68 bird species exhibiting different ecological traits in forest patches.

Methods.

We conducted point-count bird surveys in 40 forest sites of the Brazilian Atlantic forest. Using six variables related to landscape composition and configuration and local vegetation structure, we predicted the occupancy probability of each species accounting for imperfect detections.

Results

Landscape composition, especially forest cover, best predicted bird occupancy probability. Specifically, most bird species showed greater occupancy probability in sites inserted in more forested landscapes, while some species presented higher occurrence in patches surrounded by low-quality matrices. Conversely, only three species showed greater occupancy in landscapes with higher number of patches and dominated by forest edges. Also, several species exhibited greater occupancy in sites harbouring either larger trees or lower number of understory plants. Of uttermost importance, our study revealed that a minimum of 54% of forest cover is required to ensure high (> 60%) occupancy probability of forest species.

Conclusions

We highlighted that maintaining only 20% of native vegetation in private property according to Brazilian environmental law is insufficient to guarantee a greater occupancy for most bird species. We recommend that policy actions should safeguard existing forest remnants, expand restoration projects, and curb human-induced disturbances to minimise degradation within forest patches.

     

Modeling a cross-ecosystem subsidy: forest songbird response to emergent aquatic insects

Context

Resource movements across ecosystem boundaries are important determinants of the diversity and abundance of organisms in the donor and recipient ecosystem. However the effects of cross-ecosystem movements of materials at broader spatial extents than a typical field study are not well understood.

Objectives

We tested the hypotheses that (1) variation in abundance of 57 forest songbird species within four foraging guilds is explained by modeled emergent aquatic insect biomass inputs from adjacent lakes and streams and (2) the degree of association varies across foraging guilds and species within guilds. We also sought to determine the importance of emergent aquatic insects while accounting for variation in local forest cover and edge.

Methods

We spatially modeled the degree to which distribution and abundance of songbirds in different foraging guilds was explained by modeled emergent aquatic insect biomass. We used multilevel models to simultaneously estimate the responses of species in four different insectivorous guilds. Bird abundance was summarized from point counts conducted over 24 years at 317 points.

Results

Aerial insectivores were more abundant in areas with high estimated emergent insect biomass inputs to land (regression coefficient 0.30, P?<?0.05) but the overall abundance of gleaners, bark-probers, and ground-foragers was not explained by estimated emergent insect abundance. The coursing aerial insectivores had the strongest association with emergent insects followed by willow flycatcher, olive-sided flycatcher, and alder flycatcher.

Conclusions

Modeling cross-ecosystem movements of materials at broad spatial extents can effectively characterize the importance of this ecological process for aerial insectivorous songbirds.

     

Landscape-scale effects of forest degradation on insectivorous birds and invertebrates in austral temperate forests

Context

Insectivorous birds are sensitive to forest disturbances that may limit the availability of food consisting mainly of invertebrates. However, birds and invertebrates may be differently affected by forest disturbances while invertebrates may interact with disturbances.

Objectives

We aim to determine: (i) the effects of forest degradation on invertebrates and insectivorous birds; (ii) the effect of the availability of invertebrates as a food source on birds; (iii) interactions between food availability and forest degradation.

Methods

We selected 34 1-km radius landscape units, where the abundance of birds and invertebrates was sampled in the canopy and understory. Bird density as well as the abundance and richness of invertebrates were considered as dependent variables and analysed using Generalized Linear Mixed Model and Structural Equation Models. Remote-sensing indices of forest degradation were included as predictors.

Results

Eight indices of forest degradation affected canopy and understory invertebrates differently. Unlike invertebrates, bird abundance was affected by a smaller number of degradation indices, forest amounts as well as the cover of understory and canopy. Only two forest degradation indices had a comparable effect on bird abundance and invertebrates. We found causal relationships between understory invertebrates and the abundance of understory birds (all species and the small-sized ones), but also invertebrate abundance × forest cover interactions affected the abundance of a bird species.

Conclusions

Our results indicate that birds and invertebrates respond differently to forest degradation, but also provide evidence for bottom-up control by forest degradation and suggest food limitation varies with forest amounts.

     

Forest proximity rather than local forest cover affects bee diversity and coffee pollination services

Context

As agricultural demands for land continues to expand, strategies are urgently needed to balance agricultural production with biodiversity conservation and ecosystem service provision in agricultural landscapes.

Objectives

We used a factorial landscape design to assess the relative contributions of forest proximity and local forest cover to bee diversity and the provision of coffee pollination services.

Methods

We quantified bee diversity and fruit set in 24 sun-grown coffee fields in Southeast Region of Brazil that were selected following a factorial sampling design to test the independent effects of local forest cover (in a radius of 400 m) and proximity to forest fragments. To assess the impact of landscape simplification, we also evaluated local coffee cover.

Results

Bee richness and abundance were higher in the proximity of forest fragments, but only bee abundance decreased when the coffee cover dominated the surrounding landscapes. Coffee fruit set was 16% higher overall with bee visitations compared with bee exclusion and increased to 20% when coffee bushes were near forest fragments, and the coffee cover was low. Surprisingly, local forest cover did not affect the bee community or coffee fruit set.

Conclusion

Our results provide clear evidence that the proximity of coffee crops to forest fragments can affect the abundance and richness of bees visiting the coffee flowers and thereby facilitate the provision of pollination services. The positive association between forest proximity and fruit set reinforces the importance of natural vegetation in enhancing bee diversity and, therefore, in the provision of pollination services. The negative effect of coffee cover on fruit set at the local scale suggests that the service demand can surpass the capacity of pollinators to provide it. These effects were independent of the local forest cover, although all studied landscapes had more than 20% remaining forest cover (within a 2 km radius), which is considered the extinction threshold for Atlantic Forest species. Interspersion of forest fragments and coffee plantations in regions with more than 20% of forest cover left could thus be a useful landscape management target for facilitating pollinator flows to coffee crops and thus for increasing coffee yields.

     

Linear downscaling from MODIS to landsat: connecting landscape composition with ecosystem functions

Context

The open and free access to Landsat and MODIS products have greatly promoted scientific investigations on spatiotemporal change in land mosaics and ecosystem functions at landscape to regional scales. Unfortunately, there is a major mismatch in spatial resolution between MODIS products at coarser resolution (≥?250 m) and landscape structure based on classified Landsat scenes at finer resolution (30 m).

Objectives

Based on practical needs for downscaling popular MODIS products at 500 m resolution to match classified land cover at Landsat 30 m resolution, we proposed an innovative modelling approach so that landscape structure and ecosystem functions can be directly studied for their interconnections. As a proof-of-concept of our downscaling approach, we selected the watershed of the Kalamazoo River in southwestern Michigan, USA as the testbed.

Methods

MODIS products for three fundamental variables of ecosystem function are downscaled to ensure the approach can be extrapolated to multiple functional measurements. They are blue-sky albedo (0–1), evapotranspiration (ET, mm), and gross primary production (GPP, Mg C ha^?1 year^?1). An object-oriented classification of Landsat images in 2011 was processed to generate a land cover map for landscape structure. The downscaling model was tested for the five Level IV ecoregions within the watershed.

Results

We achieved satisfactory downscaling models for albedo, ET, and GPP for all five ecoregions. The adjusted R² was?>?0.995 for albedo, 0.915–0.997 for ET, and 0.902–0.962 for GPP. The estimated albedo, ET, and GPP values appear different in the region. The estimated albedo was the lowest for water (0.076–0.107) and the highest for cropland (0.166–0.172). Estimated ET was the highest for the built-up cover type (525.6–687.1 mm) and the lowest for forest (209.7–459.7 mm). The estimated GPP was the highest for the build-up cover type (8.65–9.85 Mg C ha^?1 year^?1) and the lowest for forest.

Conclusions

Estimated values for albedo, ET, and GPP appear reasonable for their ranges in the Kalamazoo River region and are consistent with values reported in the literature. Despite these promising results, the downscaling approach relies on strong assumptions and can carry substantial uncertainty. It is only valid at a spatial scale where similar climate, soil, and landforms exist (i.e., values in isolated patches of the same cover type are similar). Plausibly, the uncertainties associated with each estimation, as well as the model residuals, can be explored for other pattern-process relationships within the landscape.

     

Post-disturbance recovery of forest cover and tree height differ with management in Central Europe

Context

Recovery from disturbances is a prominent measure of forest ecosystem resilience, with swift recovery indicating resilient systems. The forest ecosystems of Central Europe have recently been affected by unprecedented levels of natural disturbance, yet our understanding of their ability to recover from disturbances is still limited.

Objectives

We here integrated satellite and airborne Lidar data to (i) quantify multi-decadal post-disturbance recovery of two indicators of forest structure, and (ii) compare the recovery trajectories of forest structure among managed and un-managed forests.

Methods

We developed satellite-based models predicting Lidar-derived estimates of tree cover and stand height at 30 m grain across a 3100 km² landscape in the Bohemian Forest Ecosystem (Central Europe). We summarized the percentage of disturbed area that recovered to >?40% tree cover and >?5 m stand height and quantified the variability in both indicators over a 30-year period. The analyses were stratified by three management regimes (managed, protected, strictly protected) and two forest types (beech-dominated, spruce-dominated).

Results

We found that on average 84% of the disturbed area met our recovery threshold 30 years post-disturbance. The rate of recovery was slower in un-managed compared to managed forests. Variability in tree cover was more persistent over time in un-managed forests, while managed forests strongly converged after a few decades post-disturbance.

Conclusion

We conclude that current management facilitates the recovery of forest structure in Central European forest ecosystems. However, our results underline that forests recovered well from disturbances also in the absence of human intervention. Our analysis highlights the high resilience of Central European forest ecosystems to recent disturbances.

     

Land cover and climate changes drive regionally heterogeneous increases in US insecticide use

Context

Global environmental change is expected to dramatically affect agricultural crop production through a myriad of pathways. One important and thus far poorly understood impact is the effect of land cover and climate change on agricultural insect pests and insecticides.

Objectives

Here we address the following three questions: (1) how do landscape complexity and weather influence present-day insecticide use, (2) how will changing landscape characteristics and changing climate influence future insecticide use, and how do these effects manifest for different climate and land cover projections? and (3) what are the most important drivers of changing insecticide use?

Methods

We use panel models applied to county-level agriculture, land cover, and weather data in the US to understand how landscape composition and configuration, weather, and farm characteristics impact present-day insecticide use. We then leverage forecasted changes in land cover and climate under different future scenarios to predict insecticide use in 2050.

Results

We find different future scenarios—through modifications in both landscape and climate conditions—increase the amount of area treated by ~ 4–20% relative to 2017, with regionally heterogeneous impacts. Of note, we report large farms are more influential than large crop patches and increased winter minimum temperature is more influential than increased summer maximum temperature. However, our results suggest the most important determinants of future insecticide use are crop composition and farm size, variables for which future forecasts are sparse.

Conclusions

Both landscape and climate change are expected to increase future insecticide use. Yet, crop composition and farm size are highly influential, data-poor variables. Better understanding of future crop composition and farm economics is necessary to effectively predict and mitigate increases in pesticide use.

     

Habitat suitability and connectivity modeling reveal priority areas for Indiana bat (Myotis sodalis) conservation in a complex habitat mosaic

Context

Conservation 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.

Objectives

We 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.

Methods

Using 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.

Results

Factors 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.

Conclusions

While 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.

     

Multiple-scale prediction of forest loss risk across Borneo

Context

The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet.

Objectives

Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the training sample, (4) identify the multiple-scale drivers of recent forest loss and (5) predict future forest loss risk across Borneo.

Methods

We compared random forest machine learning and logistic regression in a multi-scale approach to model forest loss risk between 2000 and 2010 as a function of topographical variables and landscape structure, and applied the highest performing model to predict the spatial pattern of forest loss risk between 2010 and 2020. We utilized a naïve model as a null comparison and used the total operating characteristic AUC to assess model performance.

Results

Our analysis produced five main results. We found that: (1) random forest consistently outperformed logistic regression and the naïve model; (2) including landscape structure variables substantially improved predictions; (3) a ratio of occurrence to non-occurrence points in the training dataset that does not match the actual ratio in the landscape biases the predictions of both random forest and logistic regression; (4) forest loss risk differed between the three nations that comprise Borneo, with patterns in Kalimantan highly related to distance from the edge of the previous frontier of forest loss, while Malaysian Borneo showed a more diffuse pattern related to the structure of the landscape; (5) we predicted continuing very high rates of forest loss in the 2010–2020 period, and produced maps of the expected risk of forest loss across the full extent of Borneo.

Conclusions

These results confirm that multiple-scale modelling using landscape metrics as predictors in a random forest modelling framework is a powerful approach to landscape change modelling. There is immense immanent risk to Borneo’s forests, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo.

     

Precipitation-dependent source–sink dynamics in a spatially-structured population of an outbreaking caterpillar

Context

Patch-based population models predominately focus on factors that affect regional processes namely, patch size and connectivity, as the primary drivers explaining patch occupancy. This trend persists despite the recognition that patch quality can strongly influence population demography at the local scale. The quality of patches is often temporally variable and influenced by abiotic conditions. However, few studies have explicitly investigated how climatic variables influence the spatial and temporal dynamics of spatially-structured populations either directly or indirectly through changes in patch quality.

Objectives

Using a 10-year census of a spatially-structured population of an outbreaking caterpillar, we determined the relative importance of patch quality (determined demographically), connectivity, precipitation, and their interactive effects on patch abundance, occupancy, colonization, and extinction.

Methods

We generated a series of statistical models and performed comparisons using Akaike’s information criterion. We subsequently used likelihood ratio tests to determine the influence of each parameter on model fit.

Results

Patch quality and precipitation were the strongest predictors of the observed dynamics. We found that the dynamics of the spatially-structured population of Arctia virginalis were strongly influenced by precipitation: all patches had a higher probability of occupancy, contained higher abundances of caterpillars, and experienced fewer extinctions following wet winters compared to years following droughts.

Conclusion

These findings suggest that precipitation may act to influence the strength of heterogeneity of patch quality. This work demonstrates that patch-based models that do not include local and climatic factors may produce poor predictions under future climatic regimes.

     

Contrasting time-scale effects of land-use legacy on species richness,diversity and composition in Mediterranean scrubland communities

Context

It is known that land-use and land-cover (LULC) changes affect plant community assembly for decades. However, both the short- and the long-term effects of contrasting LULC change pathways on this assembly are seldom explored.

Objectives

To assess how LULC change pathways affect woody plant community parameters (i.e. species richness, diversity and evenness) and species’ presence and abundance, compared with environmental factors and neutral processes.

Methods

The study was performed in Mediterranean limestone scrublands in NE Spain. Cover of each woody species was recorded in 150 scrubland plots belonging to five LULC change pathways along the past century, identified using land-cover maps and fieldwork. For each plot, total woody and herbaceous vegetation cover, local environmental variables and geographical position were recorded. Effects of these pathways and factors on plant community parameters and on species presence and abundance were assessed, considering spatial effects potentially associated to neutral processes.

Results

Species richness and diversity were associated with LULC change pathways and elevation, while evenness was only associated with this last. Pathways and environmental variables explained similar variance in both species’ presence and cover. In general, while community parameters were affected by recent-past (1956) use, species presence and abundance were associated with far-past (pre-1900) cropping. No relevant spatial effect was detected for any studied factor.

Conclusions

Historical LULC changes and current environmental factors drive local-scale community assembly in Mediterranean scrublands to an equal extent, while contrasting time-scale effects are found at community and species level. Neutral, dispersal-based processes are found to be non-relevant.

     

Perceived ecosystem services synergies,trade-offs,and bundles in European high nature value farming landscapes

Context

Around 30% of European agricultural landscapes are classified as high nature value (HNV) farmlands. Current policies emphasize the multifunctionality of these landscapes, but little is known about the positive and negative associations of multiple ecosystem services within HNV farmland.

Objectives

This study aims to identify perceived ecosystem services synergies, trade-offs, and bundles in agricultural landscapes of HNV from a socio-cultural perspective.

Methods

We performed a participatory mapping survey of 10 ecosystem services categories among 2301 rural residents in 13 European sites. We analyzed bivariate synergies and trade-offs between perceived ecosystem services through nonparametric correlation analyses. Spatial bundles of perceived ecosystem services were identified through hierarchical cluster analysis. Multinomial logit models were used to assess the influence of land cover on generating associations of ecosystem services.

Results

We find two strong and 16 moderate synergies of perceived ecosystem services (out of 46 possible ecosystem services pairs), mainly among different cultural ecosystem services. We do not reveal moderate or strong trade-offs. We identify five spatial bundles of ecosystem services, termed “Ecosystem services coldspots”, “Wild harvesting ranges”, “Nature areas”, “Recreational spaces”, and “Ecosystem services hotspots”. Of all land-cover co-variates, natural areas, urban areas, and roads have the strongest explanatory power.

Conclusions

Our study complements prevailing biophysical and economic analyses of ecosystem services synergies, trade-offs and bundles by a spatially explicit, socio-cultural perspective. We conclude that socio-cultural mapping of ecosystem services is useful for understanding the perceived multifunctionality of a landscape.

     

Saproxylic species are linked to the amount and isolation of dead wood across spatial scales in a beech forest

Context

Dead wood is a key habitat for saproxylic species, which are often used as indicators of habitat quality in forests. Understanding how the amount and spatial distribution of dead wood in the landscape affects saproxylic communities is therefore important for maintaining high forest biodiversity.

Objectives

We investigated effects of the amount and isolation of dead wood on the alpha and beta diversity of four saproxylic species groups, with a focus on how the spatial scale influences results.

Methods

We inventoried saproxylic beetles, wood-inhabiting fungi, and epixylic bryophytes and lichens on 62 plots in the Sihlwald forest reserve in Switzerland. We used GLMs to relate plot-level species richness to dead wood amount and isolation on spatial scales of 20–200 m radius. Further, we used GDMs to determine how dead wood amount and isolation affected beta diversity.

Results

A larger amount of dead wood increased beetle richness on all spatial scales, while isolation had no effect. For fungi, bryophytes and lichens this was only true on small spatial scales. On larger scales of our study, dead wood amount had no effect, while greater isolation decreased species richness. Further, we found no strong consistent patterns explaining beta diversity.

Conclusions

Our multi-taxon study shows that habitat amount and isolation can strongly differ in the spatial scale on which they influence local species richness. To generally support the species richness of different saproxylic groups, dead wood must primarily be available in large amounts but should also be evenly distributed because negative effects of isolation already showed at scales under 100 m.

     

The importance of land-use legacies for modeling present-day species distributions

Context

Land-use legacies play an important role in shaping contemporary species distributions. However, land-use legacies are rarely considered in species distribution models (SDMs) that aim to model present-day species distributions across the landscape, even though they can lead to a species absence in suitable areas. SDMs that do not account for land-use legacies will likely result in biased predictions of species distributions.

Objective

We examine the importance of land-use legacies for modeling present-day distributions of tree species at a regional scale, assessing how the addition of land-use legacy variables improves predictive power of SDMs.

Methods

We generated land-use legacy variables using raster layers of reconstructed historical agricultural land use and 3310 inventory plots. SDMs were developed for six forest tree species based on climatic, edaphic, and topographic variables, and with (SDM_LU) and without (SDM_Base) land-use legacy variables. We compared the predictive power between SDM_LU and SDM_Base models and then quantified the local importance of land-use legacy variables relative to other abiotic variables.

Results

Our results show that the importance of land-use legacy variables for present-day species distributions and the improvement on the predictive power of SDMs is species-specific. The inclusion of land-use legacy variables improved SDMs primarily by lowering errors of commission and increasing the overall accuracy of prediction.

Conclusion

The influence of land-use legacies on SDMs suggests that, for some tree species, incorporating land-use legacies can accurately identify suitable areas that are not occupied by the species due to land-use legacies, and advance our understanding of their present-day distributions.

     

Multi-temporal trajectories of landscape change explain forest biodiversity in urbanizing ecosystems

Context

Forest loss and fragmentation negatively affect biodiversity. However, disturbances in forest canopy resulting from repeated deforestation and reforestation are also likely important drivers of biodiversity, but are overlooked when forest cover change is assessed using a single time interval.

Objectives

We investigated two questions at the nexus of plant diversity and forest cover change dynamics: (1) Do multitemporal forest cover change trajectories explain patterns of plant diversity better than a simple measure of overall forest change? (2) Are specific types of forest cover change trajectories associated with significantly higher or lower levels of diversity?

Methods

We sampled plant biodiversity in forests spanning the Charlotte, NC, region. We derived forest cover change trajectories occurring within nested spatial extents per sample site using a time series of aerial photos from 1938 to 2009, then classified trajectories by spatio-temporal patterns of change. While accounting for landscape and environmental covariates, we assessed the effects of the trajectory classes as compared to net forest cover change on native plant diversity.

Results

Our results indicated that forest stand diversity is best explained by forest change trajectories, while the herb layer is better explained by net forest cover change. Three distinct forest change trajectory classes were found to influence the forest stand and herb layer.

Conclusions

The influence of forest dynamics on biodiversity can be overlooked in analyses that use only net forest cover change. Our results illustrate the utility of assessing how specific trajectories of past land cover change influence biodiversity patterns in the present.

     

Statistical models of landscape pattern metrics,with applications to regional scale dynamic forest simulations

Forest managers in Canada need to model landscape pattern or spatial configurationoverlarge (100,000 km²) regions. This presents a scalingproblem, as landscape configuration is measured at a high spatial resolution,but a low spatial resolution is indicated for regional simulation. We present astatistical solution to this scaling problem by showing how a wide range oflandscape pattern metrics can be modelled from low resolution data. Our studyarea comprises about 75,000 km² of boreal mixedwoodforest in northeast Alberta, Canada. Within this area we gridded a sample of 84digital forest cover maps, each about 9500 ha in size, to aresolution of 1 ha and used FRAGSTATS to compute a suite oflandscape pattern metrics for each map. We then used multivariate dimensionreduction techniques and canonical correlation analysis to model therelationship between landscape pattern metrics and simpler stand table metricsthat are easily obtained from non-spatial forest inventories. These analyseswere performed on four habitat types common in boreal mixedwood forests: youngdeciduous, old deciduous, white spruce, and mixedwood types. Using only threelandscape variables obtained directly from stand attribute tables (totalhabitatarea, and the mean and standard deviation of habitat patch size), ourstatistical models explained more than 73% of the joint variation in fivelandscape pattern metrics (representing patch shape, forest interior habitat,and patch isolation). By PCA, these five indices captured much of the totalvariability in the rich set of landscape pattern metrics that FRAGSTATS cangenerate. The predictor variables and strengths of association were highlyconsistent across habitat classes. We illustrate the potential use of suchstatistical relationships by simulating the regional, cumulative effects ofwildfire and forest management on the spatial arrangement of forest patches,using non-spatial stand attribute tables.This revised version was published online in May 2005 with corrections to the Cover Date.     

Multiscale effects of habitat and surrounding matrices on waterbird diversity in the Yangtze River Floodplain

Context

With the expansion in urbanization, understanding how biodiversity responds to the altered landscape becomes a major concern. Most studies focus on habitat effects on biodiversity, yet much less attention has been paid to surrounding landscape matrices and their joint effects.

Objective

We investigated how habitat and landscape matrices affect waterbird diversity across scales in the Yangtze River Floodplain, a typical area with high biodiversity and severe human-wildlife conflict.

Methods

The compositional and structural features of the landscape were calculated at fine and coarse scales. The ordinary least squares regression model was adopted, following a test showing no significant spatial autocorrelation in the spatial lag and spatial error models, to estimate the relationship between landscape metrics and waterbird diversity.

Results

Well-connected grassland and shrub surrounded by isolated and regular-shaped developed area maintained higher waterbird diversity at fine scales. Regular-shaped developed area and cropland, irregular-shaped forest, and aggregated distribution of wetland and shrub positively affected waterbird diversity at coarse scales.

Conclusions

Habitat and landscape matrices jointly affected waterbird diversity. Regular-shaped developed area facilitated higher waterbird diversity and showed the most pronounced effect at coarse scales. The conservation efforts should not only focus on habitat quality and capacity, but also habitat connectivity and complexity when formulating development plans. We suggest planners minimize the expansion of the developed area into critical habitats and leave buffers to maintain habitat connectivity and shape complexity to reduce the disturbance to birds. Our findings provide important insights and practical measures to protect biodiversity in human-dominated landscapes.

     

Forest recovery in a tropical landscape: what is the relative importance of biophysical,socioeconomic, and landscape variables?

Socioeconomic changes in many areas in the tropics have led to increasing urbanization, abandonment of agriculture, and forest re-growth. Although these patterns are well documented, few studies have examined the drivers leading to landscape-level forest recovery and the resulting spatial structure of secondary forests. Land cover transitions from agricultural lands to secondary forest in the island of Puerto Rico have been ongoing since the 1940s. This study is a glimpse into this landscape level trend from 1991 to 2000. First, we relied on Landsat images to characterize changes in the landscape structure for forest, urban, and agricultural land classes. We found that although forest cover has increased in this period, forest has become increasingly fragmented while the area of urban cover has spread faster and become more clustered. Second, we used logistic regression to assess the relationship between the transition to forest and 21 biophysical, socioeconomic, and landscape variables. We found that the percentage of forest cover within a 100 m radius of a point, distance to primary roads and nature reserves, slope, and aspect are the most important predictors of forest recovery. The resulting model predicts the spatial pattern of forest recovery with accuracy (AUC-ROC = 0.798). Together, our results suggest that forest recovery in Puerto Rico has slowed down and that increasing pressure from urbanization may be critical in determining future landscape level forest recovery. These results are relevant to other areas in the tropics that are undergoing rapid economic development.