Functional beetle diversity in managed grasslands: effects of region,landscape context and land use intensity

Current biodiversity conservation policies have so far had limited success because they are mainly targeted to the scale of individual fields with little concern on different responses of organism groups at larger spatial scales. We investigated the relative impacts of multi-scale factors, including local land use intensity, landscape context and region, on functional groups of beetles (Coleoptera). In 2008, beetles were suction-sampled from 95 managed grasslands in three regions, ranging from Southern to Northern Germany. The results showed that region was the most important factor affecting the abundance of herbivores and the abundance and species composition of predators and decomposers. Herbivores were not affected by landscape context and land use intensity. The species composition of the predator communities changed with land use intensity, but only in interaction with landscape context. Interestingly, decomposer abundance was negatively related to land use intensity in low-diversity landscapes, whereas in high-diversity landscapes the relation was positive, possibly due to enhanced spillover effects in complex landscapes. We conclude that (i) management at multiple scales, from local sites to landscapes and regions, is essential for managing biodiversity, (ii) beetle predators and decomposers are more affected than herbivores, supporting the hypothesis that higher trophic levels are more sensitive to environmental change, and (iii) sustaining biological control and decomposition services in managed grassland needs a diverse landscape, while effects of local land use intensity may depend on landscape context.     

Landscapes Toolkit: an integrated modelling framework to assist stakeholders in exploring options for sustainable landscape development

At present, stakeholders wishing to develop land use and management change scenarios at the landscape scale and to assess their corresponding impacts on water quality, biodiversity and economic performance, must examine the output of a suite of separate models. The process is not simple and presents a considerable deterrent to making such comparisons and impedes the development of more sustainable, multifunctional landscapes. To remedy this problem, we developed the Landscapes Toolkit, an integrated modelling framework that assists natural resource managers, policy-makers, planners and local communities explore options for sustainable landscape development. The Landscapes Toolkit links spatially-explicit disciplinary models, to enable integrated assessment of the water quality, biodiversity and economic outcomes of stakeholder-defined land use and management change scenarios. We use the Tully–Murray catchment in the Great Barrier Reef region of Australia as a case study to illustrate the development and application of the Landscapes Toolkit. Results show that the Landscapes Toolkit strikes a satisfactory balance between the inclusion of component models that sufficiently capture the richness of some key aspects of social-ecological system processes and the need for stakeholders to understand and compare the results of the different models. The latter is a prerequisite to making more informed decisions about sustainable landscape development. The flexibility of being able to add additional models and to update existing models is a particular strength of the Landscapes Toolkit design. Hence, the Landscapes Toolkit offers a promising modelling framework for supporting social learning and adaptive management through participatory scenario development and evaluation as well as being a tool to guide planning and policy discussions at the landscape scale.     

Multifunctionality at what scale? A landscape multifunctionality assessment for the European Union under conditions of land use change

Context

The provision of multiple ecosystem services (ES) within a landscape is commonly referred to as landscape multifunctionality. Modifying landscapes to increase multifunctionality and reduce trade-offs with concurrent services bears the potential to enhance sustainability in human-dominated landscapes. Assessing landscape multifunctionality is thus crucial for land management and planning, but lack of a clear definition and operationalization of multifunctionality impedes comparisons of different study results.

Objectives

We want to address how elements of the study design affect results of multifunctionality assessments. Furthermore, we want to quantify future multifunctionality in the European Union (EU) and indicate the role of land use change and land use diversity on multifunctionality.

Methods

We analyzed diverging scenarios depicting land use change in the EU between 2000 and 2040 for their effects on landscape multifunctionality. We tested different multifunctionality indicators at various spatial scales based on the modelling of 12 ES and biodiversity indicators.

Results

Particularly the analysis scale determines the interpretation of landscape multifunctionality. Coldspots identified by different indicators are in higher agreement than hotspots. We could not confirm links between land use diversity and landscape multifunctionality. While, at EU scale, multifunctionality slightly increases in future scenarios, agricultural intensification and (peri-)urban growth pose large threats to multifunctional landscapes.

Conclusions

The choice of indicator and analysis scale strongly determine possible interpretations of the results. Rather than focusing on the impacts of land use change on multifunctionality, it is recommended to base land use policy on the impacts of location-specific change on ES supply and demands.

     

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.

     

A spatial analysis of land cover patterns and its implications for urban avifauna persistence under climate change

Context

Although biodiversity in cities is essential to ensure the healthy functioning of ecosystems and biosecurity over time, biodiversity loss resulting from human interventions in land cover patterns is widespread in urban landscapes. In the Southern Hemisphere, climate change is likely to accelerate the process of landscape upheavals, and consequently biodiversity loss.

Objectives & Methods

The aim of this research is to test the potentials of landscape pattern composition and configuration in safeguarding indigenous avifauna against the local impacts of climate change in urban landscapes, with reference to New Zealand. To build up a platform for landscape pattern interpretation, the literature was reviewed and semi-structured interviews with six subject-matter experts were conducted to provide information about the most important avifauna in the study area, key information on their ecological traits and niches, possible impacts of climate change on their primary habitats, and spatial requirements for ongoing species survival as the climate continues to change. A spatial analysis of land cover patterns was undertaken in Wellington, New Zealand using GIS and FRAGSTATS.

Results

Although there are still opportunities for biodiversity conservation in the study area, the current land cover patterns are unlikely to safeguard the selected species against climate change impacts.

Conclusions

Eight implications for avifauna persistence under climate change are discussed for the first time in relation to a New Zealand context. These implications can give rise to a higher level of informed decision-making on a wide range of practices for biodiversity conservation related to uncertainties associated with climate change.

     

Predicting land use change: comparison of models based on landowner surveys and historical land cover trends

To make informed planning decisions, community leaders, elected officials, scientists, and natural resource managers must be able to evaluate potential effects of policies on land use change. Many land use change models use remotely-sensed images to make predictions based on historical trends. One alternative is a survey-based approach in which landowners’ stated intentions are modeled. The objectives of our research were to: (1) develop a survey-based landowner decision model (SBM) to simulate future land use changes, (2) compare projections from the SBM with those from a trend-based model (TBM), and (3) demonstrate how two alternative policy scenarios can be incorporated into the SBM and compared. We modeled relationships between land management decisions, collected from a mail survey of private landowners, and the landscape, using remotely-sensed imagery and ownership parcel data. We found that SBM projections were within the range of TBM projections and that the SBM was less affected by errors in image classification. Our analysis of alternative policies demonstrates the importance of understanding potential effects of targeted land use policies. While policies oriented toward increasing enrollment in the Conservation Reserve Program (CRP) resulted in a large (11–13%) increase in CRP lands, policies targeting increased forest thinning on private non-industrial lands increased low-density forest projections by only 1%. The SBM approach is particularly appropriate for landscapes including many landowners, because it reflects the decision-making of the landowners whose individual actions will result in collective landscape change.     

Predicting land cover change and avian community responses in rapidly urbanizing environments

We used an integrated modeling approach to simulate future land cover and predict the effects of future urban development and land cover on avian diversity in the Central Puget Sound region of Washington State, USA. We parameterized and applied a land cover change model (LCCM) that used output from a microsimulation model of urban development, UrbanSim, and biophysical site and landscape characteristics to simulate land cover 28 years into the future. We used 1991, 1995, and 1999 Landsat TM-derived land cover data and three different spatial partitions of our study area to develop six different estimations of the LCCM. We validated model simulations with 2002 land cover. We combined UrbanSim land use outputs and LCCM simulations to predict changes in avian species richness. Results indicate that landscape composition and configuration were important in explaining land cover change as well as avian species response to landscape change. Over the next 28 years, urban land cover was predicted to increase at the expense of agriculture and deciduous and mixed lowland forests. Land cover changes were predicted to reduce the total number of avian species, with losses primarily in native forest specialists and gains in common synanthropic species such as the American Crow (Corvus brachyrhynchos). The integrated modeling framework we present has potential applications in urban and natural resource planning and management and in assessing of the effects of policies on land development, land cover, and avian biodiversity.     

Road Density and Landscape Pattern in Relation to Housing Density,and Ownership,Land Cover,and Soils

Roads are conspicuous components of landscapes and play a substantial role in defining landscape pattern. Previous studies have demonstrated the link between roads and their effects on ecological processes and landscape patterns. Less understood is the placement of roads, and hence the patterns imposed by roads on the landscape in relation to factors describing land use, land cover, and environmental heterogeneity. Our hypothesis was that variation in road density and landscape patterns created by roads can be explained in relation to variables describing land use, land cover, and environmental factors. We examined both road density and landscape patterns created by roads in relation to suitability of soil substrate as road subgrade, land cover, lake area and perimeter, land ownership, and housing density across 19 predominantly forested counties in northern Wisconsin, USA. Generalized least squares regression models showed that housing density and soils with excellent suitability for road subgrade were positively related to road density while wetland area was negatively related. These relationships were consistent across models for different road types. Landscape indices showed greater fragmentation by roads in areas with higher housing density, and agriculture, grassland, and coniferous forest area, but less fragmentation with higher deciduous forest, mixed forest, wetland, and lake area. These relationships provide insight into the complex relationships among social, institutional, and environmental factors that influence where roads occur on the landscape. Our results are important for understanding the impacts of roads on ecosystems and planning for their protection in the face of continued development.     

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

Natural reforestation of European mountain landscapes raises major environmental and societal issues. With local stakeholders in the Pyrenees National Park area (France), we studied agricultural landscape colonisation by ash (Fraxinus excelsior) to enlighten its impacts on biodiversity and other landscape functions of importance for the valley socio-economics. The study comprised an integrated assessment of land-use and land-cover change (LUCC) since the 1950s, and a scenario analysis of alternative future policy. We combined knowledge and methods from landscape ecology, land change and agricultural sciences, and a set of coordinated field studies to capture interactions and feedback in the local landscape/land-use system. Our results elicited the hierarchically-nested relationships between social and ecological processes. Agricultural change played a preeminent role in the spatial and temporal patterns of LUCC. Landscape colonisation by ash at the parcel level of organisation was merely controlled by grassland management, and in fact depended on the farmer’s land management at the whole-farm level. LUCC patterns at the landscape level depended to a great extent on interactions between farm household behaviours and the spatial arrangement of landholdings within the landscape mosaic. Our results stressed the need to represent the local SES function at a fine scale to adequately capture scenarios of change in landscape functions. These findings orientated our modelling choices in the building an agent-based model for LUCC simulation (SMASH–Spatialized Multi-Agent System of landscape colonization by ASH). We discuss our method and results with reference to topical issues in interdisciplinary research into the sustainability of multifunctional landscapes.     

Historic landscape change and habitat loss: the case of black grouse in Lower Saxony,Germany

The declines of many specialist bird species in the agricultural landscapes of Central Europe have resulted in small and isolated populations. In the case of the black grouse, a ground-nesting bird species with large spatial requirements, empiric evidence about underlying landscape changes is scarce. In this study, we examined land cover and land cover changes in a farmland-forest mosaic in eastern Lower Saxony, Germany and how they affect occurrence and persistence of black grouse. Spatial information came from historic topographic maps from 1958 to 1975. The results show profound conversions of habitat to forest and farmland but also an increase in settlement area. Habitat conversions and suburbanization were negative correlates of black grouse persistence. Habitat models from before and after a decline period differed in some of the predictors and suggest black grouse habitat to be more diverse before the land cover changes. Our study confirms that land use factors at a landscape scale extent contribute to explain black grouse occurrence and thus can complement important small scale factors like the quality and size of individual habitat patches. Results also show that landscape factors affect black grouse distribution predominantly from an area much greater than an individual black grouse home range. Our models may be further evaluated on present-day landscapes and might be used to evaluate large-scale habitat availability for black grouse.     

Effects of land use legacies and habitat fragmentation on salamander abundance

Context

Landscape modification is an important driver of biodiversity declines, yet we lack insight into how ongoing landscape change and legacies of historical land use together shape biodiversity.

Objectives

We examined how a history of agricultural land use and current forest fragmentation influence the abundance of red-backed salamanders (Plethodon cinereus). We hypothesized that historical agriculture and fragmentation cause changes in habitat quality and landscape structure that limit abundance.

Methods

We measured salamander abundance at 95 forested sites in New York, USA, and we determined whether sites were agricultural fields within the last five decades. We used a structural equation model to estimate relationships between historical agriculture and salamander abundance mediated by changes in forest vegetation, microclimate, and landscape structure.

Results

Historical agriculture affected salamander abundance by altering forest vegetation at a local scale and forest cover at a landscape scale. Abundance was lowest at post-agricultural sites with low woody vegetation, leaf litter depth, and canopy cover. Post-agricultural sites had limited forest cover in the surrounding landscape historically, and salamander abundance was positively related to historical forest cover, suggesting that connectivity to source populations affects colonization of regenerating forests. Abundance was also negatively related to current forest fragmentation.

Conclusions

Historical land use can have legacy effects on animal abundance on par with effects of ongoing landscape change. We showed that associations between animal abundance and historical land use can be driven by altered site conditions and surrounding habitat area, indicating that restoration efforts should consider local site conditions and landscape context.

     

Using animal movement behavior to categorize land cover and predict consequences for connectivity and patch residence times

Context

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types.

Objectives

We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity.

Methods

We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics.

Results

Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times.

Conclusions

Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.

     

An agent-based approach to modeling impacts of agricultural policy on land use, biodiversity and ecosystem services

We present extensions to the agent-based agricultural policy simulator (AgriPoliS) model that make it possible to simulate the consequences of agricultural policy reform on farmers?? land use decisions and concomitant impacts on landscape mosaic, biodiversity and ecosystem services in a real agricultural region. An observed population of farms is modelled as a multi-agent system where individual farm-agent behaviour and their interactions??principally competition for land??are defined through an optimization framework with land use and landscape impacts resulting as emergent properties of the system. The model is calibrated to real data on the farms and the landscape to be studied. We illustrate the utility of the model by evaluating the potential impacts of three alternative frameworks for the European Union Common Agricultural Policy (CAP) on landscape values in two marginal agricultural regions. Mosaic value was found to be sensitive to the choice of policy scheme in one of the landscapes, whereas significant trade-offs were shown to occur in terms of species richness by habitat and species composition at the landscape scale in both regions. The relationship between food production and other ecosystem services was found to be multifaceted. Thus illustrating the difficulty of achieving landscape goals in a particular region with simple or general land management rules (such as the current rules attached to CAPs direct payments). Given the scarcity of funding for conservation, the level and conditions for allocating direct payments are, potentially, of great importance for preserving landscape values in marginal agricultural regions (subject to levels of other support).     

Landscape changes over time: comparison of land uses, boundaries and mosaics

Changes in the landscape from 1946 to 1999 were studied according to changes in the land uses, boundaries and mosaics therein. The abundances of the different categories of these three landscape elements were calculated using land use maps. Their frequency profiles were compared based on their richness, evenness and diversity. Richness of land uses does not noticeably change. However, these slight changes are spatially perceptible in the landscape when changes in the boundaries and mosaics are considered. For the three landscape elements the least diverse landscapes are obtained in the initial year. The highest landscape diversity is reached, however, in the intermediate years when boundaries or mosaics are considered, whereas the highest value based on land uses occurs in the final period studied. Considering that land uses, boundaries and mosaics provide different information on landscape characteristics and qualities, conditional entropy analyses were conducted in order to ascertain which of the types of landscape elements is most related to landscape change. Boundaries are the element most related to landscape change. Mosaics, however, are the element that best describe each of the years because they integrate the information on land uses and boundaries. From an ecological and management point of view, the three elements should be considered as opposed to just land uses. They compliment each other in the information provided by each one in relation to changes occurring and the effects thereof on landscape structure and functioning.     

Assessing alternative futures for agriculture in Iowa,U.S.A.

The contributions of current agricultural practices to environmental degradation and the social problems facing agricultural regions are well known. However, landscape-scale alternatives to current trends have not been fully explored nor their potential impacts quantified. To address this research need, our interdisciplinary team designed three alternative future scenarios for two watersheds in Iowa, USA, and used spatially-explicit models to evaluate the potential consequences of changes in farmland management. This paper summarizes and integrates the results of this interdisciplinary research project into an assessment of the designed alternatives intended to improve our understanding of landscape ecology in agricultural ecosystems and to inform agricultural policy. Scenario futures were digitized into a Geographic Information System (GIS), visualized with maps and simulated images, and evaluated for multiple endpoints to assess impacts of land use change on water quality, social and economic goals, and native flora and fauna. The Biodiversity scenario, targeting restoration of indigenous biodiversity, ranked higher than the current landscape for all endpoints (biodiversity, water quality, farmer preference, and profitability). The Biodiversity scenario ranked higher than the Production scenario (which focused on profitable agricultural production) in all endpoints but profitability, for which the two scenarios scored similarly, and also ranked higher than the Water Quality scenario in all endpoints except water quality. The Water Quality scenario, which targeted improvement in water quality, ranked highest of all landscapes in potential water quality and higher than the current landscape and the Production scenario in all but profitability. Our results indicate that innovative agricultural practices targeting environmental improvements may be acceptable to farmers and could substantially reduce the environmental impacts of agriculture in this region.This revised version was published online in May 2005 with corrections to the Cover Date.     

Combining process-based models for future biomass assessment at landscape scale

We need an integrated assessment of the bioenergy production at landscape scale for at least three main reasons: (1) it is predictable that we will soon have landscapes dedicated to bioenergy productions; (2) a number of “win–win” solutions combining several dedicated energy crops have been suggested for a better use of local climate, soil mosaic and production systems and (3) “well-to-wheels” analyses for the entire bioenergy production chain urge us to optimize the life cycle of bioenergies at large scales. In this context, we argue that the new generation of landscape models allows in silico experiments to estimate bioenergy distributions (in space and time) that are helpful for this integrated assessment of the bioenergy production. The main objective of this paper was to develop a detailed modeling methodology for this purpose. We aimed at illustrating and discussing the use of mechanistic models and their possible association to simulate future distributions of fuel biomass. We applied two separated landscape models dedicated to human-driven agricultural and climate-driven forested neighboring patches. These models were combined in the same theoretical (i.e. virtual) landscape for present as well as future scenarios by associating realistic agricultural production scenarios and B2-IPCC climate scenarios depending on the bioenergy type (crop or forest) concerned in each landscape patch. We then estimated esthetical impacts of our simulations by using 3D visualizations and a quantitative “depth” index to rank them. Results first showed that the transport cost at landscape scale was not correlated to the total biomass production, mainly due to landscape configuration constraints. Secondly, averaged index values of the four simulations were conditioned by agricultural practices, while temporal trends were conditioned by gradual climate changes. Thirdly, the most realistic simulated landscape combining intensive agricultural practices and climate change with atmospheric CO₂ concentration increase corresponded to the lowest and unwanted bioenergy conversion inefficiency (the biomass production ratio over 100 years divided by the averaged transport cost) and to the most open landscape. Managing land use and land cover changes at landscape scale is probably one of the most powerful ways to mitigate negative (or magnify positive) effects of climate and human decisions on overall biomass productions.     

Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast

Context

Coastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely.

Objectives

To examine the role of land cover diversity and composition in landscape response to SLR across the northeastern United States.

Methods

Using an existing probabilistic framework, we quantify the probability of inundation, a measure of vulnerability, under different SLR scenarios on the coastal landscape. Resistant areas—wherein a dynamic response is anticipated—are defined as unlikely (p < 0.33) to inundate. Results are assessed regionally for different land cover types and at 26 sites representing varying levels of land cover diversity.

Results

Modeling results suggest that by the 2050s, 44% of low-lying, habitable land in the region is unlikely to inundate, further declining to 36% by the 2080s. In addition to a decrease in SLR resistance with time, these results show an increasing uncertainty that the coastal landscape will continue to evolve in response to SLR as it has in the past. We also find that resistance to SLR is correlated with land cover composition, wherein sites containing land cover types adaptable to SLR impacts show greater potential to undergo biogeomorphic state shifts rather than inundating with time.

Conclusions

Our findings support other studies that have highlighted the importance of ecological composition and diversity in stabilizing the physical landscape and suggest that flexible planning strategies, such as adaptive management, are particularly well suited for SLR preparation in diverse coastal settings.

     

Uncertainty analysis as a tool for refining land dynamics modelling on changing landscapes: a case study in a Spanish Natural Park

In this study we developed a methodology aimed at improving the assessment of inter-annual land cover dynamics from hard classified remotely sensed data in heterogeneous and resilient landscapes. The methodology is implemented for the Spanish Natural Park of Sierra de Ancares, where human interference during the last century has resulted in the destruction and fragmentation of the original land cover. We ran supervised classifications, with a maximum likelihood algorithm (Maxlike), on a temporal series of Landsat images (1991–2005), followed by an uncertainty assessment using fuzzy classifications and confusion indices (CIs). This allowed us to show how much (and where) of the resulting maps contained a substantial amount of error, distinguishing data that might be useful to measure land change from data that are not particularly useful when applying a post-classification comparison methodology. In this way, we can detect true changes not skewed by the effects of uncertainty. Even if patterns of change were always coherent amongst years, they were more realistic after reducing uncertainty, in spite of a substantial decrease in the number of available pixels (i.e. unmasked by the method). We then computed land cover dynamics by means of a model specifically designed to determine the frequency of disturbances (mainly fire events) and the vegetation recovery time during the study period. Model outputs showed correlated landscape patterns at a broad scale and provided useful results to explore land cover change from pattern to process.     

Measuring the impacts of climate change on the spatial structure of grasslands in urban landscapes of North America

Although the importance of biodiversity conservation has been acknowledged in urban landscapes of many forest, desert, and coastal biomes, urbanization in grasslands and its negative/positive impacts on biodiversity is understudied. We designed a pilot, spatio-temporal study to envision the impacts of land-use and vegetation change on the composition and configuration of grasslands in urban landscapes of the Upper Missouri River Basin under four climate-change scenarios (A1B, A2, B1, and B2) from 2020 to 2070 with respect to the IPCC’s high-level and mid-level Representative Concentration Pathways (RCP 8.5 w/m² and RCP 4.5 w/m²). We show that under the most climate-change scenarios, the rate of grassland conversion into other land cover classes from 2020 to 2070 was greater in urban landscapes than the whole region but this trend was not correlated with urban expansion. Conversely, habitat proximity was negatively correlated with urban expansion. The capacity of habitat patches to function as wildlife refugia in urban landscapes was substantially greater under the B2 scenario, where social equality and environmental conservation are highly prioritized. On the basis of the results of this study, we demonstrate that measuring the changes in the composition and configuration of habitat patches, combined with an understanding of the rate of grassland conversion can provide more detailed information about opportunities and limitations for biodiversity conservation in this region and beyond. If managed strategically, urban landscapes can play a positive role in conserving biodiversity and preserving ecosystems in regions predominantly used for agricultural lands.