Modelling the influence of landscape connectivity on animal distribution: a functional grain approach

Landscape change may reduce the connectivity of landscapes and impact the movement of animals. If movement processes have been influenced by landscape connectivity, we hypothesize that animals may distribute themselves in larger connected regions of the landscape in order to minimize the movement costs associated with obtaining required resources and avoiding predators. We adopt the term functional grain to describe a set of functionally connected regions. In this spatial pattern, each region describes a contiguous area of the landscape within which an animal may move freely below a threshold amount of movement cost. We used telemetry data from woodland caribou Rangifer tarandus caribou to test hypothetical functional grains where connectivity was determined by the spatial configuration of resource patches (patch only), by the resistance to movement presented by landscape features (resistance only), and by a combination of the two (patch + resistance). To identify these functional grains, we used a grains of connectivity approach, and introduced a novel lattice‐based variant of this method to build the resistance only model. We developed a measure of fit that describes caribou distribution with respect to larger functionally connected regions in the grain, and used this to ask: 1) are seasonal caribou locations consistent with a random functional grain, implying that landscape connectivity has not shaped their distribution? 2) Given a functional grain model, are seasonal caribou locations distributed in larger functionally connected regions than random points, implying a response to the shape, size, and location of the connected regions. We found support for landscape connectivity influencing animal distribution using grains based on a landscape resistance model, and that support varied between behaviourally defined seasons. We also discuss how our novel lattice approach may be valuable for highly mobile mammals and other species where the identification of resource patches is a limitation.     

The effect of cost surface parameterization on landscape resistance estimates

A cost or resistance surface is a representation of a landscape's permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization.     

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

Climate change can affect the habitat resources available to species by changing habitat quantity, suitability and spatial configuration, which largely determine population persistence in the landscape. In this context, dispersal is a central process for species to track their niche. Assessments of the amount of reachable habitat (ARH) using static snap-shots do not account, however, for the temporal overlap of habitat patches that may enhance stepping-stone effects. Here, we quantified the impacts of climate change on the ARH using a spatio–temporal connectivity model. We first explored the importance of spatio–temporal connectivity relative to purely spatial connectivity in a changing climate by generating virtual species distributions and analyzed the relative effects of changes in habitat quantity, suitability and configuration. Then, we studied the importance of spatio–temporal connectivity in three vertebrate species with divergent responses to climate change in North America (grey wolf, Canadian lynx and white-tailed deer). We found that the spatio–temporal connectivity could enhance the stepping-stone effect for species predicted to experience range contractions, and the relative importance of the spatio–temporal connectivity increased with the reduction in habitat quantity and suitability. Conversely, for species that are likely to expand their ranges, spatio–temporal connectivity had no additional contribution to improve the ARH. We also found that changes in habitat amount (quantity and suitability) were more influential than changes in habitat configuration in determining the relative importance of spatio–temporal connectivity. We conclude that spatio–temporal connectivity may provide less biased and more realistic estimates of habitat connectivity than purely spatial connectivity.     

Gene flow and functional connectivity in the natterjack toad

Functional connectivity is a key factor for the persistence of many specialist species in fragmented landscapes. However, connectivity estimates have rarely been validated by the observation of dispersal movements. In this study, we estimated functional connectivity of a real landscape by modelling dispersal for the endangered natterjack toad (Bufo calamita) using cost distance. Cost distance allows the evaluation of 'effective distances', which are distances corrected for the costs involved in moving between habitat patches in spatially explicit landscapes. We parameterized cost-distance models using the results of our previous experimental investigation of natterjack's movement behaviour. These model predictions (connectivity estimates from the GIS study) were then confronted to genetic-based dispersal rates between natterjack populations in the same landscape using Mantel tests. Dispersal rates between the populations were inferred from variation at six microsatellite loci. Based on these results, we conclude that matrix structure has a strong effect on dispersal rates. Moreover, we found that cost distances generated by habitat preferences explained dispersal rates better than did the Euclidian distances, or the connectivity estimate based on patch-specific resistances (patch viscosity). This study is a clear example of how landscape genetics can validate operational functional connectivity estimates.     

Comparative Landscape Genetics of Three Closely Related Sympatric Hesperid Butterflies with Diverging Ecological Traits

To understand how landscape characteristics affect gene flow in species with diverging ecological traits, it is important to analyze taxonomically related sympatric species in the same landscape using identical methods. Here, we present such a comparative landscape genetic study involving three closely related Hesperid butterflies of the genus Thymelicus that represent a gradient of diverging ecological traits. We analyzed landscape effects on their gene flow by deriving inter-population connectivity estimates based on different species distribution models (SDMs), which were calculated from multiple landscape parameters. We then used SDM output maps to calculate circuit-theoretic connectivity estimates and statistically compared these estimates to actual genetic differentiation in each species. We based our inferences on two different analytical methods and two metrics of genetic differentiation. Results indicate that land use patterns influence population connectivity in the least mobile specialist T. acteon. In contrast, populations of the highly mobile generalist T. lineola were panmictic, lacking any landscape related effect on genetic differentiation. In the species with ecological traits in between those of the congeners, T. sylvestris, climate has a strong impact on inter-population connectivity. However, the relative importance of different landscape factors for connectivity varies when using different metrics of genetic differentiation in this species. Our results show that closely related species representing a gradient of ecological traits also show genetic structures and landscape genetic relationships that gradually change from a geographical macro- to micro-scale. Thus, the type and magnitude of landscape effects on gene flow can differ strongly even among closely related species inhabiting the same landscape, and depend on their relative degree of specialization. In addition, the use of different genetic differentiation metrics makes it possible to detect recent changes in the relative importance of landscape factors affecting gene flow, which likely change as a result of contemporary habitat alterations.     

LORACS: JAVA software for modeling landscape connectivity and matrix permeability

GIS tools and remote sensing products have opened the possibility to model the impacts of matrix permeability on a broad range of ecological phenomena. LORACS (Landscape ORganization and Connectivity Survey) is JAVA software containing a GUI interface and an API for easy extensibility. The user inputs maps with the relative costs to move within each pixel and the location of source and target patches. The software outputs Multiple Shortest Paths and Conditional Minimum Transit Cost maps. One key feature is the derivation of uncertainty estimates around path length, cost, and spatial distribution. We use data from the Brazilian Atlantic Forest to illustrate how LORACS can be used to translate assumptions about habitat quality into landscape connectivity patterns.     

基于MSPA与最小路径方法的巴中西部新城生态网络构建

目前快速城市化导致了生境斑块的日益破碎化,景观之间的连通性不断降低。构建生态网络可以连接破碎的生境斑块,增加绿地景观的连通性,对生物多样性保护具有重要意义。以高度景观破碎化的四川省巴中西部新城为研究区,采用形态学空间格局分析(MSPA)方法,提取出对研究区生态网络构建具有重要生态意义的核心区和桥接区两类景观要素,并选用整体连通性(IIC)、可能连通性(PC)和斑块重要性(d I)等景观指数,分别对核心区和桥接区进行景观连接度评价,遴选出对维持景观连通性贡献最大的10个核心区生境斑块作为生态网络的源地,并根据斑块对维持景观连通的重要性程度将其他核心区和桥接区进行类型划分,以此作为景观阻力的赋值依据,融入消费面模型中,最后采用最小路径方法构建了研究区潜在的生态网络,并基于重力模型对重要生态廊道进行了识别与提取,在此基础上有针对性地提出了生态网络优化的对策。研究结果表明,MSPA方法能够科学的辨识出研究区内对生态保护具有重要意义的结构性要素,例如作为物种栖息地的核心区和物种迁移通道的桥接区,这些要素是生态网络的重要组成部分;景观连通性的计算,明确了研究区景观要素的保护重点,为最小路径方法中的景观阻力赋值提供了重要的参考信息;基于MSPA与最小路径方法的生态网络分析框架综合了现有景观结构性要素识别、连通性分析以及物种潜在迁移路径分析等方法,将景观中潜在的生态源地和结构性廊道的连通性作为构建生态网络的重要基础和主要依据,从而使得生态网络的构建更科学。研究结果可为高度破碎化地区生态网络的构建提供重要的参考与依据,对其他地区生态网络的构建也具有一定的借鉴意义。     

An integrative framework of coexistence mechanisms in competitive metacommunities

Species distribution in a metacommunity varies according to their traits, the distribution of environmental conditions and connectivity among localities. These ingredients contribute to coexistence across spatial scales via species sorting, patch dynamics, mass effects and neutral dynamics. These mechanisms however seldom act in isolation and the impact of landscape configuration on their relative importance remains poorly understood. We present a new model of metacommunity dynamics that simultaneously considers these four possible mechanisms over spatially explicit landscapes and propose a statistical approach to partition their contribution to species distribution. We find that landscape configuration can induce dispersal limitations that have negative consequences for local species richness. This result was more pronounced with neutral dynamics and mass effect than with species sorting or patch dynamics. We also find that the relative importance of the four mechanisms varies not only among landscape configurations, but also among species, with some species being mostly constrained by dispersal and/or drift and others by sorting. Changes in landscape properties might lead to a shift in coexistence mechanisms and, by extension, to a change in community composition. This confirms the importance of considering landscape properties for conservation and management. Our results illustrate the idea that ecological communities are the results of multiple mechanisms acting at the same time and complete our understanding of spatial processes in competitive metacommunities.     

Interactions between landcover pattern and geospatial processing methods: Effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric “number of patches” than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty.     

Generalizing matrix structure affects the identification of least-cost paths and patch connectivity

Understanding and assessing landscape connectivity is often a primary goal when studying patchy or spatially structured populations. It is commonly accepted that the matrix plays a role in determining connectivity; however, it is not clear how the process of assessing connectivity is impacted by different ways in which the matrix may be represented, particularly if matrix structure is generalized to expedite analysis. We conducted a controlled experiment using computer simulations to evaluate the impact of increasing levels of matrix generalization on connectivity assessment using a constant arrangement of habitat patches. We varied matrix generalization for six simulated landscape patterns by adjusting the number of classes and level of pattern grain in 16 ways to yield sets of landscapes for which the matrix ranged from not generalized (i.e., heterogeneous) to completely generalized (i.e., homogeneous) while habitat placement was held constant. Least-cost paths were calculated for each landscape, and a spatial interaction model (SIM) was implemented to model the counts of patch inflows (immigration) and pairwise exchange. Applying a SIM allowed us to generate absolute outputs and explicitly compare the effect of changes to matrix generalization on connectivity. We found that both assessment of connections (i.e., measured distance and spatial delineation of least-cost paths) and patch inflows/pairwise exchange were highly sensitive to matrix generalization and that effects were inconsistent and unpredictable across the range of matrix representations, especially when estimating connectivity for individual patches. We conclude that matrix pattern may have an underappreciated effect on connectivity and that least-cost path delineation and connectivity assessment may be very sensitive to generalizations of the matrix. We suggest that sensitivity analysis of the matrix representation should be performed when conducting connectivity analyses.     

Connectivity and propagule sources composition drive ditch plant metacommunity structure

The fragmentation of agricultural landscapes has a major impact on biodiversity. In addition to habitat loss, dispersal limitation increasingly appears as a significant driver of biodiversity decline. Landscape linear elements, like ditches, may reduce the negative impacts of fragmentation by enhancing connectivity for many organisms, in addition to providing refuge habitats. To characterize these effects, we investigated the respective roles of propagule source composition and connectivity at the landscape scale on hydrochorous and non-hydrochorous ditch bank plant metacommunities. Twenty-seven square sites (0.5 km² each) were selected in an agricultural lowland of northern France. At each site, plant communities were sampled on nine ditch banks (totaling 243 ditches). Variables characterizing propagule sources composition and connectivity were calculated for landscape mosaic and ditch network models. The landscape mosaic influenced only non-hydrochorous species, while the ditch network impacted both hydrochorous and non-hydrochorous species. Non-hydrochorous metacommunities were dependent on a large set of land-use elements, either within the landscape mosaic or adjacent to the ditch network, whereas hydrochorous plant metacommunities were only impacted by the presence of ditches adjacent to crops and roads. Ditch network connectivity also influenced both hydrochorous and non-hydrochorous ditch bank plant metacommunity structure, suggesting that beyond favoring hydrochory, ditches may also enhance plant dispersal by acting on other dispersal vectors. Increasing propagule sources heterogeneity and connectivity appeared to decrease within-metacommunity similarity within landscapes. Altogether, our results suggest that the ditch network's composition and configuration impacts plant metacommunity structure by affecting propagule dispersal possibilities, with contrasted consequences depending on species' dispersal vectors.     

Effects of exposure uncertainties in the TSCE model and application to the Colorado miners data

The simulations in this paper show that exposure measurement error affects the parameter estimates of the biologically motivated two-stage clonal expansion (TSCE) model. For both Berkson and classical error models, we show that likelihood-based techniques of correction work reliably. For classical errors, the distribution of true exposures needs to be known or estimated in addition to the distribution of recorded exposures conditional on true exposures. Usually the exposure uncertainty biases the model parameters toward the null and underestimates the precision. But when several parameters are allowed to be dependent on exposure, e.g. initiation and promotion, then their relative importance is also influenced, and more complicated effects of exposure uncertainty can occur. The application part of this paper shows for two different types of Berkson errors that a recent analysis of the data for the Colorado plateau miners with the TSCE model is not changed substantially when correcting for such errors. Specifically, the conjectured promoting action of radon remains as the dominant radiation effect for explaining these data. The estimated promoting action of radon increases by a factor of up to 1.2 for the largest assumed exposure uncertainties.     

Effects of grain size and niche breadth on species distribution modeling

Scale is a vital component to consider in ecological research, and spatial resolution or grain size is one of its key facets. Species distribution models (SDMs) are prime examples of ecological research in which grain size is an important component. Despite this, SDMs rarely explicitly examine the effects of varying the grain size of the predictors for species with different niche breadths. To investigate the effect of grain size and niche breadth on SDMs, we simulated four virtual species with different grain sizes/niche breadths using three environmental predictors (elevation, aspect, and percent forest) across two real landscapes of differing heterogeneity in predictor values. We aggregated these predictors to seven different grain sizes and modeled the distribution of each of our simulated species using MaxEnt and GLM techniques at each grain size. We examined model accuracy using the AUC statistic, Pearson's correlations of predicted suitability with the true suitability, and the binary area of presence determined from suitability above the maximum true skill statistic (TSS) threshold. Habitat specialists were more accurately modeled than generalist species, and the models constructed at the grain size from which a species was derived generally performed the best. The accuracy of models in the homogenous landscape deteriorated with increasing grain size to a greater degree than models in the heterogenous landscape. Variable effects on the model varied with grain size, with elevation increasing in importance as grain size increased while aspect lost importance. The area of predicted presence was drastically affected by grain size, with larger grain sizes over predicting this value by up to a factor of 14. Our results have implications for species distribution modeling and conservation planning, and we suggest more studies include analysis of grain size as part of their protocol.     

评估不同尺度下农牧地对滇金丝猴景观连接度的影响

基于图论法原理,综合最小费用距离和猴群的最小家域,建立了滇金丝猴栖息地的潜在扩散廊道及廊道缓冲区。在此区域内,根据遗传距离与栖息地连接最小费用距离的相关性,确定了5个不同管理单元间猴群可能扩散的阈值,并根据此阈值计算获得可能连通性指数(PC)去评估不同尺度下农牧地对滇金丝猴栖息地景观连接度的影响。结果表明:在距离为2.15km的廊道缓冲区范围内,5个不同管理单元间猴群可能扩散的最小费用距离阈值为1600,在两个斑块之间的费用距离小于或等于1600时,两个斑块能够连接,猴群可能在这两个斑块进行扩散,超过费用距离1600时,两个斑块不再连接,即猴群在这两个斑块间不会扩散。景观尺度下,PC指数逐渐增加,意味着未来4种不同的农牧地改善情景(C1,C2,C3,C4)都将促进景观连接度的增加;在斑块尺度下,通过确定出的最佳距离阈值,将整个研究区域分成不同的组分,小于或等于阈值的相邻斑块被划分在同一个组分中,大于阈值则不在一个组分中,研究区域中的5个不同管理单元间的猴群被划分在3个不同的组分中,情景C1,C2中组分数量没有变化,意味着连接度没有发生改变,但在情景C3,C4中,组分数量减少,并与相邻的组分融为一个组分,意味着连接度发生改变,滇金丝猴的活动范围扩大,更有利于猴群的基因交流。研究结果将为滇金丝猴栖息地的保护、未来廊道的恢复建设提供科学依据,同时也能为类似的研究提供方法上的参考。     

Independent effects of habitat loss,habitat fragmentation and structural connectivity on forest‐dependent birds

Aim Habitat loss and fragmentation are amongst the greatest threats to biodiversity world‐wide. However, there is still little evidence on the relative influence of these two distinct processes on biodiversity, and no study, to date, has investigated the independent contribution of structural connectivity in addition to habitat loss and fragmentation. The aim of this study is to evaluate the independent effects of habitat loss (the decrease in total amount of habitat), habitat fragmentation per se (habitat subdivision) and structural connectivity (in the form of hedgerow networks) on the distribution of seven resident forest‐dependent birds in central Italy. Location Central Italy. Methods We strategically selected 30 landscapes (each of 16 km² in size) with decreasing total amount of forest cover and with contrasting configuration of patches and contrasting lengths of hedgerow networks. Presence/absence of birds in each landscape unit was studied through point counts. Results The amount of forest cover in the landscape had the strongest relative influence on birds’ occupancy, whilst habitat subdivision played a negligible role. Structural connectivity and the geographic position of the landscape unit played a relatively important role for four species. Main conclusions Our study shows the importance of disentangling the contribution of different landscape properties in determining distribution patterns. Our results are consistent with the fact that halting habitat loss and carrying out habitat restoration should be conservation priorities, since habitat loss is the main factor affecting the distribution of the target species; implementation of structural connectivity through hedgerows, instead, should be evaluated with caution since its contribution is secondary to the predominant role of habitat loss.     

整合电路理论的生态廊道及其重要性识别

景观连接度被认为是影响诸多生态过程的一个重要因素.基于最小累积阻力模型的最小成本路径识别方法可以有效识别异质性景观中的功能连接,已被广泛应用到景观的功能连接评价与生态廊道模拟的研究中.基于电路理论的连接度模型用电阻代替了图论中的边、用电阻距离代替成本距离,来衡量异质性景观的功能连接.本文以SIMMAP 2.0软件生成的模拟景观为对象,借助于Linkage Mapper工具和Circuitscape软件,探讨如何将最小累积阻力模型与基于电路理论的连接度模型相结合来识别生态廊道及其景观要素的相对重要性.结果表明: 两种模型在应用中各有优势,互为补充.最小成本路径方法可以有效识别栖息地之间的最小成本廊道,基于电路理论的连接度模型通过电流密度的计算可以有效识别对景观连接性有重要影响的景观要素和“夹点”地区,并且“夹点”的位置不受廊道宽度的影响,在廊道重要性识别研究中具有明显优势.该方法可为区域生态保护规划和生态廊道设计提供科学依据.     

面向连通性提升的旱区城市生态网络优化情景——以巴彦淖尔市及其周边地区为例

巴彦淖尔市作为典型的干旱区城市,经济发展与生态保护之间的矛盾突出,生态空间的破碎化日益严重。生态网络是景观连通性视角下耦合景观结构、生态过程和功能的有效途径。基于生态系统服务重要性、景观核心区与桥接区、自然保护区、重要湖泊湿地4个层面指标选取生态源地,使用最小耗费距离方法识别巴彦淖尔市及其周边区域的潜在生态网络,并设置了3种网络优化情景进行网络优化,包括情景一增加生态"踏脚石"、情景二清除生态障碍点、情景三保护生态夹点,结合"网络构建成本"及"生境连通效果"选取最佳优化方案。结果表明,研究区当前的生态网络由24处生态源地,44条生态廊道、39个生态障碍点和41个生态夹点组成。3种情景中生态夹点的保护对生态网络连通度的改善最明显,且相对保护成本较低。研究结果对干旱区城市生态网络构建提供了方法支撑。     

Using a sub-pixel mapping model to improve the accuracy of landscape pattern indices

The assessment of landscape spatial patterns is a key issue in landscape management. Landscape pattern indices (LPIs) are tools appropriate for analyzing landscape spatial patterns. LPIs are often derived from raster land cover maps that are extracted from remotely sensed data through hard classification. However, pixel-based hard classification methods suffer from the mixed pixel problem (in which pixels contain more than one land cover class), making for inaccurate classification maps and LPIs. In addition, LPIs generated by hard classification methods are characterized by grain sizes (the sampling unit sizes) that limit the derived landscape pattern to a certain scale. Sub-pixel mapping (SPM) models can enable fine-scale estimation of the spatial patterns of land cover classes without requiring additional data; hence, this is an appropriate downscaling method for land cover mapping. The fraction images generated by soft classification estimate the area proportion of each land cover class within each pixel, and using these images as input enables SPM models to alleviate the mixed pixel problem. At the same time, by transforming fraction images into a finer-scaled hard classification map, SPM models can minimize the influence of grain size on LPIs calculation. In this research, simulated landscape thematic patterns that can provide different landscape spatial patterns, eight commonly used LPIs and a SPM model that maximizes the spatial dependence between neighbouring sub-pixels were applied to assess the efficiency of deriving LPIs from sub-pixel model maps. Results showed that the SPM model can more precisely characterize landscape patterns than hard classification methods can. Landscape fragmentation, class abundance, the uncertainty in SPM, and the spatial resolution of the remotely sensed data influenced LPIs derived from sub-pixel maps. The largest patch index, landscape division, and patch cohesion derived from remotely sensed data with different spatial resolutions through the SPM model were suitable for inter-comparison, whereas the patch density, mean patch area, edge density, landscape shape index, and area-weighted mean shape index derived from the sub-pixel maps were sensitive to the spatial resolution of the remotely sensed data.     

Inter‐individual variability in dispersal behaviours impacts connectivity estimates

The importance of landscape connectivity in determining biodiversity outcomes under environmental change has led to indices of connectivity becoming amongst the most widely used measures in conservation. Thus, it is vital that our understanding of connectivity and our use of indices describing it are reliable. Dispersal is the key ecological process involved in determining connectivity, and there is increasing evidence of substantial within‐population variability in dispersal behaviours. Here, we incorporate this inter‐individual variability into two approaches for estimating connectivity, least cost path analysis and stochastic movement simulation. Illustrative results demonstrate that including dispersal variability can yield substantially different estimates of connectivity. While connectivity is typically similar between nearby patches, the frequency of movements between patches further apart is often substantially increased when inter‐individual variability is included. Given the disproportionate role that unusual long‐distance dispersal events play in spatial dynamics, connectivity indices should seek to incorporate variability in dispersal behaviour.     

基于MSPA和MCR模型的秦岭(陕西段)山地生态网络构建

快速的城市化发展破坏了生境斑块的连通性,而在应对此环境变化中,从斑块层构建区域生态网络的研究不足。本研究以秦岭(陕西段)为对象,采用形态学空间格局分析(MSPA)辨别生态源地,利用最小阻力模型(MCR)提取潜在生态廊道,构建秦岭生态网络;基于重力模型对生态网络内部斑块的重要性进行分级,并分析了网络的结构特征及景观构成。结果表明: 秦岭(陕西段)生态网络由10个生态源地、45条潜在生态廊道和38个脚踏石构成,生态源地总面积29686.15 km²;网络闭合度(0.11)、线点率(1.18)、网络连接度(0.42)、成本比(0.99)综合表明,网络结构中潜在生态廊道和生态节点的连通性较好,而源地间的连通程度低,构建网络的成本较高;重要生态廊道主要由林地、草地、耕地等景观类型构成,其中,林地面积最大,为571.00 km²,约占廊道总面积的89.2%,景观结构良好;在生态网络中应加强保护生态源地,优先建立并保护重要生态廊道和生态节点。研究结果可为秦岭生态环境保护与高质量发展提供科学的参考和依据。