Individual dispersal,landscape connectivity and ecological networks

Connectivity is classically considered an emergent property of landscapes encapsulating individuals' flows across space. However, its operational use requires a precise understanding of why and how organisms disperse. Such movements, and hence landscape connectivity, will obviously vary according to both organism properties and landscape features. We review whether landscape connectivity estimates could gain in both precision and generality by incorporating three fundamental outcomes of dispersal theory. Firstly, dispersal is a multi‐causal process; its restriction to an ‘escape reaction’ to environmental unsuitability is an oversimplification, as dispersing individuals can leave excellent quality habitat patches or stay in poor‐quality habitats according to the relative costs and benefits of dispersal and philopatry. Secondly, species, populations and individuals do not always react similarly to those cues that trigger dispersal, which sometimes results in contrasting dispersal strategies. Finally, dispersal is a major component of fitness and is thus under strong selective pressures, which could generate rapid adaptations of dispersal strategies. Such evolutionary responses will entail spatiotemporal variation in landscape connectivity. We thus strongly recommend the use of genetic tools to: (i) assess gene flow intensity and direction among populations in a given landscape; and (ii) accurately estimate landscape features impacting gene flow, and hence landscape connectivity. Such approaches will provide the basic data for planning corridors or stepping stones aiming at (re)connecting local populations of a given species in a given landscape. This strategy is clearly species‐ and landscape‐specific. But we suggest that the ecological network in a given landscape could be designed by stacking up such linkages designed for several species living in different ecosystems. This procedure relies on the use of umbrella species that are representative of other species living in the same ecosystem.     

Inferring connectivity of genetic regulatory networks using information-theoretic criteria

Recently, the concept of mutual information has been proposed for inferring the structure of genetic regulatory networks from gene expression profiling. After analyzing the limitations of mutual information in inferring the gene-to-gene interactions, this paper introduces the concept of conditional mutual information and based on it proposes two novel algorithms to infer the connectivity structure of genetic regulatory networks. One of the proposed algorithms exhibits a better accuracy while the other algorithm excels in simplicity and flexibility. By exploiting the mutual information and conditional mutual information, a practical metric is also proposed to assess the likeliness of direct connectivity between genes. This novel metric resolves a common limitation associated with the current inference algorithms, namely the situations where the gene connectivity is established in terms of the dichotomy of being either connected or disconnected. Based on the data sets generated by synthetic networks, the performance of the proposed algorithms is compared favorably relative to existing state-of-the-art schemes. The proposed algorithms are also applied on realistic biological measurements, such as the cutaneous melanoma data set, and biological meaningful results are inferred.     

Node‐based measures of connectivity in genetic networks

At‐site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at‐site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at‐site processes, where network nodes are used to model site‐level effects. We used simulated genetic networks to compare and contrast the performance of 7 node‐based (as opposed to edge‐based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at‐site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node‐based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at‐site habitat conditions on the immigration and settlement phases of dispersal.     

Minimum mean square error estimation of connectivity in biological neural networks

A minimum mean square error (MMSE) estimation scheme is employed to identify the synaptic connectivity in neural networks. This new approach can substantially reduce the amount of data and the computational cost involved in the conventional correlation methods, and is suitable for both nonstationary and stationary neuronal firings. Two algorithms are proposed to estimate the synaptic connectivities recursively, one for nonlinear filtering, the other for linear filtering. In addition, the lower and upper bounds for the MMSE estimator are determined. It is shown that the estimators are consistent in quadratic mean. We also demonstrate that the conventional cross-interval histogram is an asymptotic linear MMSE estimator with an inappropriate initial value. Finally, simulations of both nonlinear and linear (Kalman filter) estimates demonstrate that the true connectivity values are approached asymptotically.     

基于景观格局和连接度评价的生态网络方法优化与应用

景观生态学中常凭借最小累积阻力模型构建目标种生态网络,以提升破碎栖息地间的景观连接度,缓解生境破碎化负面影响.但传统最小累积阻力生态网络方法缺乏对生态网络的效用验证,对研究地的景观结构变化与生态过程的影响认识不足.本研究运用景观格局指数与连接度概率指数,定量评价生态网络构建前后的研究地景观结构与连接度特征,并以崇左白头叶猴栖息地生态网络为例,详尽叙述此生态网络方法的优化与应用过程.通过对白头叶猴栖息地斑块进行辨认、踏脚石斑块识别,对研究地用地类型进行划分并进行阻力赋值,运用最小累积阻力模型生成了20条白头叶猴栖息地生态网络廊道;然后利用景观结构指数与连接度概率指数结合的方法,对生成的生态网络结构和功能连接度进行评价.结果表明: 凭借最小累积阻力模型构建的目标种生态网络,能有效提升栖息地生境的完整性和连续性,降低总体破碎化水平,并改善生境质量.同时,该生态网络构建能提升生境景观的结构连接度与功能连接度,且两方面的连接度变化在结果上具有极显著的一致性(R²=98.3%,P<0.01).生态网络带来的景观结构方面变化与功能连接度的关联性不强,两种指数间的相互关系不如结构与功能的内在关系显著.     

Comparative landscape genetics reveals the evolution of viviparity reduces genetic connectivity in fire salamanders

Evolutionary changes in reproductive mode may affect co‐evolving traits, such as dispersal, although this subject remains largely underexplored. The shift from aquatic oviparous or larviparous reproduction to terrestrial viviparous reproduction in some amphibians entails skipping the aquatic larval stage and, thus, greater independence from water. Accordingly, amphibians exhibiting terrestrial viviparous reproduction may potentially disperse across a wider variety of suboptimal habitats and increase population connectivity in fragmented landscapes compared to aquatic‐breeding species. We investigated this hypothesis in the fire salamander (Salamandra salamandra), which exhibits both aquatic‐ (larviparity) and terrestrial‐breeding (viviparity) strategies. We genotyped 426 larviparous and 360 viviparous adult salamanders for 13 microsatellite loci and sequenced a mitochondrial marker for 133 larviparous and 119 viviparous individuals to compare population connectivity and landscape resistance to gene flow within a landscape genetics framework. Contrary to our predictions, viviparous populations exhibited greater differentiation and reduced genetic connectivity compared to larviparous populations. Landscape genetic analyses indicate viviparity may be partially responsible for this pattern, as water courses comprised a significant barrier only in viviparous salamanders, probably due to their fully terrestrial life cycle. Agricultural areas and, to a lesser extent, topography also decreased genetic connectivity in both larviparous and viviparous populations. This study is one of very few to explicitly demonstrate the evolution of a derived reproductive mode affects patterns of genetic connectivity. Our findings open avenues for future research to better understand the eco‐evolutionary implications underlying the emergence of terrestrial reproduction in amphibians.     

基于最小费用模型的景观连接度评价

作为物种扩散的重要影响因子,景观连接度反映了景观促进或阻碍生物体在资源斑块间运动的程度,它也是区域土地可持续利用和生物保护领域的主要指标.最小费用模型起源于图论,其结合了景观中的详细地理信息和生物体的行为特征,通过费用距离分析可直观形象地描绘出物种在异质景观中的连接度,且可在GIS程序包中实现简便运算和适度的数据需求量,使其在大尺度景观连接度评价中受到广泛关注.本文结合当前的景观连接度研究,详细阐述了最小费用模型评价景观连接度的意义、原理及运算过程,并探讨了该模型应用中存在的问题,以期为进一步开展相关研究及生物多样性保护提供依据.     

A scalar analysis of landscape connectivity

Landscape connectivity is critical to the maintenance of spatially-structured populations and consists of both a structural component, which describes the shape, size and location of landscape features; and a biological component, which consists of both the response of individuals to landscape features, and the patterns of gene flow that result from those individual responses. Traditional studies of landscape connectivity have attempted to discern individual behavioral responses to landscape features, but this methodology is intractable for many species. This paper is an attempt to relate the components of landscape connectivity through the explicit treatment of their spatial and temporal scales. Traditional measures of structural and biological components of connectivity are reviewed and more recently developed methods for the analysis of scale for each are introduced. I then present a framework for the comparison of scalar phenomena based on Watt's unit pattern, describe the potential outcomes of the comparison and discuss the implications of each. Several testable hypotheses emerge from the analysis that may serve as a useful framework for the investigation of landscape connectivity in the future .     

Directed dispersal by rotational shepherding supports landscape genetic connectivity in a calcareous grassland plant

Directed dispersal by animal vectors has been found to have large effects on the structure and dynamics of plant populations adapted to frugivory. Yet, empirical data are lacking on the potential of directed dispersal by rotational grazing of domestic animals to mediate gene flow across the landscape. Here, we investigated the potential effect of large‐flock shepherding on landscape‐scale genetic structure in the calcareous grassland plant Dianthus carthusianorum, whose seeds lack morphological adaptations to dispersal to animals or wind. We found a significant pattern of genetic structure differentiating population within grazed patches of three nonoverlapping shepherding systems and populations of ungrazed patches. Among ungrazed patches, we found a strong and significant effect of isolation by distance (r = 0.56). In contrast, genetic distance between grazed patches within the same herding system was unrelated to geographical distance but significantly related to distance along shepherding routes (r = 0.44). This latter effect of connectivity along shepherding routes suggests that gene flow is spatially restricted occurring mostly between adjacent populations. While this study used nuclear markers that integrate gene flow by pollen and seed, the significant difference in the genetic structure between ungrazed patches and patches connected by large‐flock shepherding indicates the potential of directed seed dispersal by sheep across the landscape.     

Limited phylogeographic and genetic connectivity in Acacia species of low stature in an arid landscape

Widespread plant species are expected to maintain genetic diversity and gene flow via pollen and seed dispersal. Stature is a key life history trait that affects seed and potentially pollen dispersal, with limited stature associated with limited dispersal and greater genetic differentiation. We sampled Hill’s tabletop wattle (Acacia hilliana) and curry wattle (Acacia spondylophylla), two co‐distributed, widespread, Acacia shrubs of low stature, across the arid Pilbara region of north‐western Australia. Using chloroplast sequence and nuclear microsatellite data we evaluated patterns of population genetic and phylogeographic diversity and structure, demographic signals, ratios of pollen to seed dispersal, evidence for historical refugia, and association between elevation and diversity. Results showed strong phylogeographic (chloroplast, G _ST = 0.831 and 0.898 for A. hilliana and A. spondylophylla, respectively) and contemporary (nuclear, F _ST = 0.260 and 0.349 for A. hilliana and A. spondylophylla, respectively) genetic structure in both species. This indicates limited genetic connectivity via seed and pollen dispersal associated with Acacia species of small stature compared to taller tree and shrub acacias across the Pilbara bioregion. This effect of stature on genetic structure is superimposed on moderate levels of genetic diversity that were expected based on widespread ranges (haplotype diversity h = 25 and 12; nuclear diversity He = 0.60 and 0.47 for A. hilliana and A. spondylophylla, respectively). Contemporary genetic structure was congruent at the greater landscape scale, especially in terms of strong genetic differentiation among geographically disjunct populations in less elevated areas. Measures of diversity and connectivity were associated with traits of greater geographic population proximity, population density, population size, and greater individual longevity, and some evidence for range expansion in A. hilliana. Results illustrate that low stature is associated with limited dispersal and greater patterns of genetic differentiation for congenerics in a common landscape and highlight the complex influence of taxon‐specific life history and ecological traits to seed and pollen dispersal.     

景观生态学中生态连接度研究进展

生态连接度对生物迁移扩散、基因流动、干扰扩散等生态过程具有重要作用,是目前景观生态学研究的热点内容.生态连接度是测度景观对于资源斑块间运动的促进或者阻碍作用程度的指标.它主要基于渗透和图论两大理论,通过实验、模型模拟以及指数等量化方法描述区域景观结构和功能的变化,广泛应用在自然景观和城市景观格局优化中,对生物多样性保护以及城市开放空间规划具有重要作用.介绍生态连接度的理论基础、评价方法,应用以及主要结论,并对景观生态学中生态连接度的未来研究方向进行展望,以促进生态连接度研究的进一步发展.     

Effects of uncertain cost-surface specification on landscape connectivity measures

Estimates of landscape connectivity are routinely used to inform decision-making by conservation biologists. Most estimates of connectivity rely on cost-surfaces: raster representations of landscapes in which cost values represent the difficulty involved with traversing an area. However, there is considerable uncertainty in the generation of cost-surfaces that have not been widely explored. We investigated the effects of four potential sources of uncertainty in the creation of cost-surfaces: 1) number of landscape classes represented; 2) spatial resolution (grain size); 3) misclassification of edges between landscape classes; and 4) cost values selected for each landscape class. Following a factorial design we simulated multiple cost-surface pairs, each comprising one true surface with no errors and one surface with uncertainty comprised of some combination of the four error sources. We evaluated the relative importance of each source of uncertainty in determining the difference between the least-cost paths (LCPs) costs and resistance distances generated for the true and erroneous cost-surfaces, using four model evaluation metrics. Errors in the underlying geospatial layers produced larger inaccuracies in connectivity estimates than those produced by cost-value errors. Incorrect grain size had the largest overall effect on the accuracy of connectivity estimates. Though the removal of an element class was found to have a large effect on the configuration of connectivity estimates, and the addition of an element class had a large effect on estimates configuration. Our results highlight the importance of minimising and quantifying the uncertainty inherent in the geospatial data used to develop cost-surfaces.     

阻力赋值对景观连接模拟的影响

景观连接度是研究景观结构和生态过程互馈关系的重要内容。在最小成本路径模拟中整合图论理论可有效辨识、评价斑块之间的潜在连接,近些年逐步应用于景观连接模拟、生态网络构建等研究中。理论上,模型的重要参数之一,生物体通过不同景观单元的阻力系数应根据观测与实验等实证研究获取,但大多数情况下简化为土地适宜性评价结合专家经验为土地利用/覆盖类型打分,存在一定主观性与不确定性。因此,设计了1个三因素(阻力赋值方式、景观粒度和景观整体破碎度)的析因实验,以SIMMAP2.0景观中性模型产生的8个模拟景观为对象,研究不同的景观格局下,阻力赋值方式对连接模拟的影响;探讨、总结经验赋值带来的不确定性。结果表明,这3个因素均对景观连接模拟产生显著影响,并存在一定交互作用;阻力赋值绝对大小不会对模拟产生影响;而赋值倾向性能够显著改变最小成本路径的空间位置,并且这种影响程度依赖于景观粒度大小,而与景观整体破碎度交互关系不显著。针对阻力赋值方式与景观结构特征交互作用下连接模拟的规律性变化,提出一些建议,以提高连接模拟的准确性。     

Interpreting the effects of landscape connectivity on community diversity

Landscape connectivity is considered a key factor regulating species diversity of natural and managed landscapes, yet the influence of connectivity relative to other factors remains poorly resolved. In this issue of Journal of Vegetation Science, Jakobsson and colleagues illustrate how grassland plant species richness is more strongly affected by the age and management of grassland patches than by connectivity.     

景观生态网络研究进展

作为生态学重要的概念与方法,生态网络是景观生态学研究的热点问题,也是耦合景观结构、生态过程和功能的重要途径。景观生态网络对于保护生物多样性、维持生态平衡、增加景观连接度具有重要意义。从景观生态网络的相关理论、研究进展、研究方法模型等进行分析,并对其应用前景进行展望,主要介绍了传统景观格局分析、网络分析、模型模拟等方法的适用性与特点,并分析了景观生态网络在城市景观格局优化、自然保护区规划、生物多样性保护、土地规划等领域的应用,最后提出了研究的主要问题。     

Population genetics of Anopheles koliensis through Papua New Guinea: New cryptic species and landscape topography effects on genetic connectivity

New Guinea is a topographically and biogeographically complex region that supports unique endemic fauna. Studies describing the population connectivity of species through this region are scarce. We present a population and landscape genetic study on the endemic malaria‐transmitting mosquito, Anopheles koliensis (Owen). Using mitochondrial and nuclear sequence data, as well as microsatellites, we show the evidence of geographically discrete population structure within Papua New Guinea (PNG). We also confirm the existence of three rDNA ITS2 genotypes within this mosquito and assess reproductive isolation between individuals carrying different genotypes. Microsatellites reveal the clearest population structure and show four clear population units. Microsatellite markers also reveal probable reproductive isolation between sympatric populations in northern PNG with different ITS2 genotypes, suggesting that these populations may represent distinct cryptic species. Excluding individuals belonging to the newly identified putative cryptic species (ITS2 genotype 3), we modeled the genetic differences between A. koliensis populations through PNG as a function of terrain and find that dispersal is most likely along routes with low topographic relief. Overall, these results show that A. koliensis is made up of geographically and genetically discrete populations in Papua New Guinea with landscape topography being important in restricting dispersal.     

On the usage and measurement of landscape connectivity

This paper examines the usage and measurement of "landscape connectivity" in 33 recent studies. Connectivity is defined as the degree to which a landscape facilitates or impedes movement of organisms among resource patches. However, connectivity is actually used in a variety of ways in the literature. This has led to confusion and lack of clarity related to (1) function vs structure, (2) patch isolation vs landscape connectivity and, (3) corridors vs connectivity. We suggest the term connectivity should be reserved for its original purpose. We highlight nine studies; these include modeling studies that actually measured connectivity in accordance with the definition, and empirical studies that measured key components of connectivity. We found that measurements of connectivity provide results that can be interpreted as recommending habitat fragmentation to enhance landscape connectivity. We discuss reasons for this misleading conclusion, and suggest a new way of quantifying connectivity, which avoids this problem. We also recommend a method for reducing sampling intensity in landscape-scale empirical studies of connectivity.