Effects of human‐induced prey depletion on large carnivores in protected areas: Lessons from modeling tiger populations in stylized spatial scenarios

Prey depletion is a major threat to the conservation of large carnivore species globally. However, at the policy‐relevant scale of protected areas, we know little about how the spatial distribution of prey depletion affects carnivore space use and population persistence. We developed a spatially explicit, agent‐based model to investigate the effects of different human‐induced prey depletion experiments on the globally endangered tiger (Panthera tigris) in isolated protected areas—a situation that prevails throughout the tiger's range. Specifically, we generated 120 experiments that varied the spatial extent and intensity of prey depletion across a stylized (circle) landscape (1,000 km²) and Nepal's Chitwan National Park (~1,239 km²). Experiments that created more spatially homogenous prey distributions (i.e., less prey removed per cell but over larger areas) resulted in larger tiger territories and smaller population sizes over time. Counterintuitively, we found that depleting prey along the edge of Chitwan National Park, while decreasing tiger numbers overall, also decreased female competition for those areas, leading to lower rates of female starvation. Overall our results suggest that subtle differences in the spatial distributions of prey densities created by various human activities, such as natural resource‐use patterns, urban growth and infrastructure development, or conservation spatial zoning might have unintended, detrimental effects on carnivore populations. Our model is a useful planning tool as it incorporates information on animal behavioral ecology, resource spatial distribution, and the drivers of change to those resources, such as human activities.     

Factors affecting breeding habitat selection in a cliff-nesting peregrine Falco peregrinus population

We studied factors affecting breeding habitat selection in a population of cliff-nesting peregrines Falco peregrinus across multiple spatial levels (cliff site, cliff context and land-use of the surrounding landscape), over a 2,100 km² study area in the Alps (Italy and Switzerland). We detected 30 breeding pairs (density: 1.43 territorial pairs/100 km²), whose territories were uniformly distributed over the study area. We compared 15 habitat features characterising occupied cliffs and 30 randomly selected unoccupied cliffs by means of stepwise forward logistic regression and hierarchical partitioning. The logistic regression analysis showed that occupied cliffs were longer (horizontal length), steeper, and had a greater extension of urban areas in the surrounding landscape compared to non-occupied cliffs. The model had a discrimination ability of 0.95. Hierarchical partitioning indicated that the logistic regression model was appropriate. Neither the distance of cliffs to the nearest site occupied by a potential competitor and predator, the eagle owl Bubo bubo, which occurred at a low density (0.67 pairs/100 km²), nor the distance to the nearest site occupied by peregrines had any effect on the cliff suitability model. Therefore, habitat selection in cliff-nesting peregrines was mainly influenced by cliff site features and surrounding landscape characteristics, whereas the proximity to conspecifics and to an intraguild predator had no apparent effects on peregrine settlement in our study population.     

Suburban scenario development based on multiple landscape assessments

Housing suburbanisation led in the past decades to problems caused by deconcentration of population and intensive area-consumption. Major social, economic and ecological functions for a sustainable spatial decision support in the suburban landscape are described and functionalised by indicators and modelled using GIS with the aim to minimise the problems related to the suburbanisation. The indicators chosen include human-ecological functions, accessibility and infrastructure development and the regulation and regeneration of population and biocoenosis. Out of a balanced list of 11 indicators (one is used twice) the regulation of traffic noise immissions, the landscape accessibility to the nearest freeway and the habitat network integration of sites are modelled, assessed and discussed detailed. The indicator modelling operationalises a wide range of methods including the analysis of travel costs, distance functions, visibility analysis and landscape metrics on the basis of public available data (biotope types, digital elevation model and road data). The methods are applied to a suburban agricultural landscape northeast of Leipzig in Saxony/Germany (66 km²). Three scenarios developed for the aggregation of multiple considerations are demonstrated with maps — based on the status quo of the “(mono)-functional landscape”, the “multi functional landscape” and the “sustainable landscape”. The scenarios aggregate an increasing number of indicators to form a comprehensive assessment. The result maps clearly show the suitable areas for private housing that fulfil e.g. silence, recreational functions while simultaneously ensuring nature protection. The paper emphasises the integrative prospects of landscape functions for monitoring, indicator assessment and the integration to land use decision-making in the context of spatial planning.     

Spatially explicit conservation issues for threatened bird species in Mediterranean farmland landscapes

Coupling habitat models based on GIS and on ground variables could help identify suitable areas (by means of landscape models obtained by GIS variables) to concentrate management actions for species’ conservation. In this study, the habitat requirements of Lesser Greys (LGS) and Woodchat Shrikes (WS), two threatened farmland bird species declining in Europe, were assessed in Apulia (south-eastern Italy) by means of binary logistic regression at two different levels: landscape (using GIS-measured variables); and, territory (using ground-measured variables) scales. The LGS occurrence at landscape scale was correlated to steppe-like areas and cereal crops. At the territory level, significant effects were detected for deciduous forests and the presence of isolated trees and shrubs. The WS occurrence at landscape scale was promoted by steppe-like areas and cereal crops, whereas, at the territory level significant effects were detected for steppe-like areas positively and suburban areas negatively. The landscape model was extrapolated to the entire region. Within highly suitable areas (occurrence probability higher than 0.66 according to the landscape model), we measured average habitat features and compared them with the optimal mosaic depicted by the territory level models. This allowed us to give spatially explicit and site-specific management recommendations for these two threatened species. LGS will mostly benefit from an increase in isolated shrubs and trees; whereas for WS, the most widespread recommendations are to increase steppe-like habitat and to prevent further urbanisation.Coupling “coarse” landscape models with the species ecology provided by fine-scaled models can integrate relevant information on species potential distribution and territory level requirements, making planning fine-tuned habitat management (within potentially suitable landscapes) in a spatially explicit way possible.     

Introducing a new method for assessing spatially explicit processes of landscape fragmentation

Landscape fragmentation is commonly defined as having five distinct phases (perforation, dissection, subdivision, shrinkage, and attrition). Previous studies focus on using landscape pattern metrics to interpret the phase of the landscape. A critical but underinvestigated aspect is that these five phases are also spatially explicit processes. This study proposes a new method to map and measure the different spatially explicit processes of landscape fragmentation. Unlike previous studies that are based on landscape pattern metrics, this current study measures landscape change directly. The new method is applied to Bao’an District in Shenzhen, China, to investigate forest land fragmentation under rapid urbanization. Landsat data were used to map the land use distributions from 1978 to 2009. Results show that different spatial processes occur simultaneously throughout the study area as well as in different study periods of forest fragmentation. Shrinkage was the dominant spatial process in the early period. In the later period, subdivision played a more important role, followed by attrition. Interestingly, urban land was not the leading land use that directly encroached on forest land, as many other studies have shown. Instead, forest land was first converted to orchard land, and orchard land was converted to urban land. The study contributes to Forman's general model of spatially explicit processes of landscape fragmentation and holds implications for urban planning policy and practice. The study concludes that the new method is effective in understanding and assessing forest land fragmentation, especially in the context of rapid urbanization.     

Rapid assessment of metapopulation viability under climate and land-use change

In order to predict species response to climate and land-use change, numerically fast and easily applicable assessment tools for species survival are required. We present a set of formulae to calculate the mean lifetime of a metapopulation in a spatially heterogeneous and dynamic landscape subject to habitat patch diminution, loss and/or spatial shift of the habitat network. The formulae require as inputs (i) information about the number, location and size of the habitat patches for several time steps to quantify landscape dynamics in terms of patch destruction, diminution or shifting rates and (ii) data on species traits such as their vulnerability to environmental variation and their dispersal ability to quantify local colonisation and extinction rates. We validate the formulae with a spatially explicit simulation. The analysis is complemented by a protocol for the easy use of the approach and practical application examples. A software implementation is available on request from the authors.     

Can we measure ecological sustainability? Landscape pattern as an indicator for naturalness and land use intensity at regional,national and European level

European landscapes have been shaped over the centuries by processes related to human land use, which are reflected in regionally distinct landscape patterns. Since landscape pattern has been linked to biodiversity and other ecological values of the landscapes, this paper explores landscape pattern as a tool for ecological sustainability assessments at the regional (Austrian Cultural Landscapes), national (Austria) and European (European Union + Norway, Switzerland) level with focus on agricultural landscapes. A set of landscape metrics served as a basis to assess naturalness and geometrisation of Austrian and European landscapes as a proxy for their sustainability. To achieve an accurate spatially explicit assessment, we applied a spatial reference framework consisting in units that are homogeneous in biophysical and socio-economic contexts, adapted the regional approach for its application at European level, and developed relative sustainability thresholds for the landscape metrics. The analyses revealed that several landscape metrics, particularly the “Number of Shape Characterising Points” showed a high correlation with the degree of naturalness. The sustainability map of Austria based on an ordinal regression model revealed well-known problem regions of ecological sustainability. At the European level, the relative deviation from the average pattern showed clearly the simplification processes in the landscapes. However, a better spatial resolution of land cover data would add to the refinement of pattern analysis in regions and therefore the assessment of sustainability. We recommend the combination of information of different scales for the formulation and implementation of sustainability policies.     

Identifying priority areas for reducing species vulnerability to climate change

Aim The dimensions of species vulnerability to climate change are complex, and this impedes efforts to provide clear advice for conservation planning. In this study, we used a formal framework to assess species vulnerability to climate change quantifying exposure, sensitivity and adaptive capacity and then used this information to target areas for reducing vulnerability at a regional scale. Location The 6500‐km² Mount Lofty Ranges region in South Australia. Methods We quantified the vulnerability of 171 plant species in a fragmented yet biologically important agro‐ecological landscape, typical of many temperate zones globally. We specified exposure, using three climate change scenarios; sensitivity, as the adverse impact of climate change on species’ spatial distribution; and adaptive capacity, as the ability of species to migrate calculated using dispersal kernels. Priority areas for reducing vulnerability were then identified by incorporating these various components into a single priority index. Results Climate change had a variable impact on species distributions. Those species whose range decreased or shifted geographically were attributed higher sensitivity than those species that increased geographic range or remained unchanged. The ability to adapt to range changes in response to shifting climates varies both spatially and between species. Areas of highest priority for reducing vulnerability were found at higher altitudes and lower latitudes with increasing severity of climate change. Main conclusions Our study demonstrates the use of a single spatially explicit index that identifies areas in the landscape for targeting specific conservation and restoration actions to reduce species vulnerability to climate change. Our index can be transferred to other regions around the world in which climate change poses an increasing threat to native species.     

Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales

Predictive models on breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus; Aves: Accipitridae) have been performed at four different spatial scales in Castellón province, East of Iberian Peninsula. The scales considered were: (1) nest site scale (1×1 km² Universal Transverse Mercator (UTM) square containing the nest); (2) near nest environment (3×3 km² UTM square); (3) home range scale (5×5 km² UTM square); and (4) landscape level scale (9×9 km² UTM square containing the above mentioned ones). Topographic, disturbance, climatic and land use factors were measured on a geographic information system (GIS) at occupied and unoccupied UTM squares. Logistic regression was performed by means of a stepwise addition procedure. We tested whether inclusion of new subset of variables improved the models by increasing the area under the receiver operator characteristic plot. At nest site scale, only topographic factors were considered as the most parsimonious predictors. Probability of species occurrence increases with slope in craggy areas at lower altitudes. At the 3×3 km² scale, climate and disturbance variables were included. At home range and landscape level scales, models included climate, disturbance, topographic and land use factors. Higher temperatures in January, template ones in July, higher rainfall in June, lower altitudes and higher slope in the sample unit increase probability of occurrence of Bonelli’s eagle at broadest scales. The species seems to prefer disperse forests, scrubland and agricultural areas. From our results, we consider that there is a hierarchical framework on habitat selection procedure. We suggest that it is necessary to analyse what key factors are affecting Bonelli’s eagle nest-site selection at every study area to take steps to ensure appropriate conservation measures. The combination of regression modelling and GIS will become a powerful tool for biodiversity and conservation studies, taking into account that application depends on sampling design and the model assumptions of the statistical methods employed. Finally, predictive models obtained could be used for the efficient monitoring of this scarce species, to predict range expansions or identify suitable locations for reintroductions, and also to design protected areas and to help on wildlife management.     

干旱区绿洲城镇景观生态风险时空变化分析——以张掖绿洲乡镇为例

科学评估与分析干旱区绿洲乡镇景观生态风险,对优化绿洲土地资源管控和维护干旱区绿洲生态系统稳定性具有重要现实意义。以张掖市绿洲乡镇为对象,基于土地利用数据和景观格局指数,结合ArcGIS空间分析功能,研究其景观生态风险时空特征及影响因素。结果表明：1987—2018年,耕地和建设用地变化明显,分别增加429.03 km~2和236.26 km~2;整体景观生态风险呈下降趋势,并呈“南北高、中间低”格局特征;各乡镇风险水平在空间上正向聚集,位于绿洲边缘地区的乡镇风险变化明显;人为活动干扰是近年风险水平变化的主要因素。研究成果可为西北干旱区绿洲生态保护与治理提供决策参考。     

Spatial distribution, connectivity, and the influence of scale: habitat availability for the endangered Mona Island rock iguana

The Caribbean region is one of the five leading biodiversity hotspots in the world. Analysis of the spatial structure of critical habitats and how it affects endemic species in this region is essential baseline information for biodiversity monitoring and management. We quantified and evaluated the spatial structure and connectivity of depression forests on Mona Island and their potential impact on Mona Island rock iguana habitat, as a framework to assess spatial distribution, connectivity, and the issue of scale in small and widely dispersed habitats. Using IKONOS imagery, we mapped and delineated depression forests at four different scales (minimum mapping units: <100, 100, 500, and 1,000 m), and calculated landscape metrics describing their spatial structure, and connectivity, for each map resolution. Our approach resulted in a more detailed map than previously described maps, providing better information on habitat connectivity for iguanas. The comparison of the island landscape mapped at different scales provided evidence on how changing scales affect the output of spatial metrics and may have a significant impact when planning decisions and assigning conservation priorities. It also highlighted the importance of adequate ecological scales when addressing landscape management and conservation priorities. The analysis of landscapes at multiple scales provided a mechanism to evaluate the role of patch detection and its effect on the interpretation of connectivity and spatial structure of suitable areas for species with small and widely dispersed habitats. These methodologies can be applied other species, in different environments, with similar limitations related to connectivity and habitat availability.     

Cultural ecosystem services of mountain regions: Modelling the aesthetic value

Mountain regions meet an increasing demand for pleasant landscapes, offering many cultural ecosystem services to both their residents and tourists. As a result of global change, land managers and policy makers are faced with changes to this landscape and need efficient evaluation techniques to assess cultural ecosystem services. This study provides a spatially explicit modelling approach to estimating aesthetic landscape values by relating spatial landscape patterns to human perceptions via a photo-based survey. The respondents attributed higher aesthetic values to the Alpine landscape in respect to areas with settlements, infrastructure or intensive agricultural use. The aesthetic value of two study areas in the Central Alps (Stubai Valley, Austria and Vinschgau, Italy) was modelled for 10,215 viewpoints along hiking trails according to current land cover and a scenario considering the spontaneous reforestation of abandoned land. Viewpoints with high aesthetic values were mainly located at high altitude, allowing long vistas, and included views of lakes or glaciers, and the lowest values were for viewpoints close to streets and in narrow valleys with little view. The aesthetic values of the reforestation scenario decreased mainly at higher altitudes, but the whole area was affected, reducing aesthetic value by almost 10% in Stubai Valley and 15% in Vinschgau. Our proposed modelling approach allows the estimation of aesthetic values in spatial and qualitative terms for most viewpoints in the European Alps. The resulting maps can be used as information and the basis for discussion by stakeholders, to support the decision-making process and landscape planning. This paper also discusses the role of mountain farming in preserving an attractive landscape and related cultural values.     

厦门湾中华白海豚潜在生态廊道识别及人类活动干扰评估

生态廊道具有维持或恢复生态连通性的功能,对于连接生物栖息地、保护物种多样性具有重要意义。现有的生态廊道研究主要集中于陆地,而海洋生态系统具有水体广泛连通、缺乏直观的景观斑块等特点,导致海洋生态廊道的研究成为长期以来的科学难题。以栖息地位于厦门湾的国家一级保护动物中华白海豚(Sousa chinensis)为对象,尝试基于物种分布模型和最小成本路径分析法建立海洋生态廊道的识别方法。研究采用物种分布模型识别厦门湾内中华白海豚的适宜生境分布区和节点,并利用模型产出的生境适宜性结果生成海洋中的阻力表面,模拟计算节点与节点间在阻力表面上的最小成本路径,从而生成物种扩散网络。研究结果显示,厦门湾中华白海豚的分布主要受到航道距离、到岸线距离和叶绿素浓度三项因素的影响,主要适宜生境位于西海域至九龙江口和大嶝海域。潜在的核心生态廊道面积93.19km²,次级生态廊道面积170.41km²,九龙江口-鼓浪屿南侧-黄厝-大小嶝岛沿线可能是厦门湾中华白海豚的主要迁移路线。在此基础上,从用海空间重叠和桥梁影响两方面开展了人类活动对廊道的干扰评估。评估结果显示旅游活动和...     

Predicting forest grouse distribution taking account of spatial autocorrelation

Spatially explicit, multi-scale models for predictions of species potential distribution can be useful tools for integrating biodiversity considerations in planning and strategic environmental assessment. In such models, the occurrences of focal species are related to habitat and landscape variables, which in urbanising areas should also include effects of urban disturbances. Moreover, the accuracy of the spatial predictive models may be affected by spatial autocorrelation, which means that a part of the variance is explained by neighbouring values. The aim of this study was to explore the effects of habitat and disturbance patterns on the distribution of two forest grouse species, Tetrao urogallus and Bonasa bonasia, and to detect and model the effects of spatial autocorrelation. The distribution of the two species could be explained in terms of reduction of a main predator, habitat quality, quantity and connectivity, including urban disturbances. The residuals of the initial regressions showed positive spatial autocorrelation that could be quantified by using a spatial probit model. The application of the spatial probit model revealed strongly significant spatial dependencies for both species. Furthermore, the model fit could be increased for T. urogallus by applying this model. The results implied that both species distributions might be affected by both reactions to the underlying land-use pattern, but also by interaction with neighbours. The use of the spatial probit model is a way to incorporate spatial interactions that otherwise cannot be captured by the independent variables.     

Using satellite imagery to assess breeding habitat availability of the endangered loggerhead shrike in Québec

The loggerhead shrike (Lanius ludovicianus) is a grassland bird species whose preferred nesting habitat in eastern Canada is pastureland. This species has been extirpated from much of its historical range in this region, and breeding habitat loss is suspected to be an important cause of this decline. We evaluated the availability of suitable breeding habitats in Québec using satellite imagery. Because this species no longer breeds in Québec, we established habitat selection criteria from known nesting sites in the adjacent province of Ontario, from analysis of a Landsat-TM satellite image, and applied these criteria to Landsat-TM images covering southern Québec. We developed regional landscape criteria in 100 km² plots and patch indices criteria at the pasture level. Spatial analyses were conducted to characterize plots and pastures on the basis of pasture availability and spatial distribution. Pastures suitable for nesting loggerhead shrikes were those fulfilling patch criteria at the pasture level and located in plots fulfilling regional landscape criteria. Overall, 310 out of 1700 plots located in the historical breeding range of the loggerhead shrike in Québec fulfilled landscape criteria, supporting 3988 pastures that fulfilled patch criteria. More than 500 of these pastures were visited to validate their current status. The Outaouais region would be the most suitable region for nesting loggerhead shrikes in southern Québec, where suitable breeding habitat still remains because more than two-thirds of visited sites were still pastureland, hawthorns were well-distributed in the region, and pastureland fragmentation was lowest. We conclude that the availability of breeding habitat does not limit the establishment of a breeding population of loggerhead shrike in southern Québec, as we estimated that thousands of hectares of suitable habitat still remain in that province.     

空间直观景观模型的验证方法

空间直观景观模型已是当前景观生态学研究的一大热点。空间景观模型模拟空间格局变化。其模拟结果包含非空间数据和空间数据。空间直观景观模型的验证除进行非空间数据的验证外,还需要进行空间数据的验证。本文回顾了空间直观模型发展历程,总结现有的空间直观模型验证方法。包括主观评价、图形比较、偏差分析、回归分析、假设检验、多尺度拟合度分析和景观指数分析,同时提出今后空间直观景观模型验证方法研究的重点方向。     

Road impacts a tipping point for wildlife populations in threatened landscapes

The conservation of wildlife populations living adjacent to roads is gaining international recognition as a worldwide concern. Populations living in road-impacted environments are influenced by spatial parameters including the amount and arrangement of suitable habitat. Similarly, heterogeneity in threatening processes can act at a variety of spatial scales and be crucial in affecting population persistence. Common wombats (Vombatus ursinus) are considered both widespread and abundant throughout their eastern Australian continental distribution. They nevertheless face many threats, primarily human induced. As well as impacts from disease and predation by introduced species, high roadside fatality rates on many rural roads are frequently reported. We parameterized a model for common wombat population viability analysis within a 750-km² area of the northwestern corner of Kosciuszko National Park in New South Wales, Australia, and tested its sensitivity to changes in the values of basic parameters. We then assessed the relative efficiency of various mitigation measures by examining the combined impact from roads, disease and predation on wombat subpopulation persistence in the area. We constructed a stage-structured and spatially explicit model incorporating estimates of survival and fecundity parameters for each of the identified subpopulations using RAMAS GIS. Estimates of current threatening processes suggest mitigating road-kill is the most effective management solution. Results highlight the importance of recognizing the interplay between various threats and how their combination has the capacity to drive local depletion events.     

Determinants of the distribution of nitrogen-cycling microbial communities at the landscape scale

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. However, a landscape perspective is needed to understand the relative importance of local and regional factors and land management for the microbial communities and the ecosystem services they provide. In the most comprehensive analysis of spatial patterns of microbial communities to date, we investigated the distribution of functional microbial communities involved in N-cycling and of the total bacterial and crenarchaeal communities over 107 sites in Burgundy, a 31 500 km² region of France, using a 16 × 16 km² sampling grid. At each sampling site, the abundance of total bacteria, crenarchaea, nitrate reducers, denitrifiers- and ammonia oxidizers were estimated by quantitative PCR and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time, and soil physico-chemical properties to the spatial distribution of the different communities were analyzed by canonical variation partitioning. Our results indicate that 43–85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of microbial communities at the landscape scale. The present study highlights the potential of a spatially explicit approach for microbial ecology to identify the overarching factors driving the spatial heterogeneity of microbial communities even at the landscape scale.     

Gypsy moth response to landscape structure differs from neutral model predictions: implications for invasion monitoring

Simulations of dispersal across computer-generated neutral landscapes have generated testable predictions about the relationship between dispersal success and landscape structure. Models predict a threshold response in dispersal success with increasing habitat fragmentation. A threshold is defined as an abrupt, disproportionate decline in dispersal success at a certain proportion of habitat in the landscape. To identify potential empirical threshold responses in invasion success to landscape structure, we quantified the relationship between progression of the gypsy moth (Lymantria dispar) invasion wavefront across Michigan (1985–1996) and the structure of the Michigan landscape using two indices of invasion success and six landscape metrics. We also examined the effect of scale of analysis and choice of land cover characterization on our results by repeating our analysis at three scales using two different land cover maps. Contrary to simulation model predictions, thresholds in invasion success did not correspond closely with thresholds in landscape structure metrics. Increased variation in invasion success indices at smaller scales of analysis also suggested that invasion success should be studied at larger spatial extents (≥75 km²) than would be appropriate for characterizing individual dispersal events. The predictions of individual dispersal models across neutral landscapes may have limited applications for the monitoring and management of vagile species with excellent dispersal capabilities such as the gypsy moth.     

Competing populations on fragmented landscapes with spatially structured heterogeneities: improved landscape generation and mixed dispersal strategies

Interactions between two species competing for space were studied using stochastic spatially explicit lattice-based simulations as well as pair approximations. The two species differed only in their dispersal strategies, which were characterized by the proportion of reproductive effort allocated to long-distance (far) dispersal versus short-distance (near) dispersal to adjacent sites. All population dynamics took place on landscapes with spatially clustered distributions of suitable habitat, described by two parameters specifying the amount and the local spatial autocorrelation of suitable habitat. Whereas previous results indicated that coexistence between pure near and far dispersers was very rare, taking place over only a very small region of the landscape parameter space, when mixed strategies are allowed, multiple strategies can coexist over a much wider variety of landscapes. On such spatially structured landscapes, the populations can partition the habitat according to local conditions, with one species using pure near dispersal to exploit large contiguous patches of suitable habitat, and another species using mixed dispersal to colonize isolated smaller patches (via far dispersal) and then rapidly exploit those patches (via near dispersal). An improved mean-field approximation which incorporates the spatially clustered habitat distribution is developed for modeling a single species on these landscapes, along with an improved Monte Carlo algorithm for generating spatially clustered habitat distributions.