Ecological principles of species distribution models: the habitat matching rule

Most species distribution models (SDMs) assume that habitats are closed, stable and without competition. In that environmental context, it is ecologically correct to assume that members of a species will be distributed in direct relation to the suitability of the habitat, that is, according to the so‐called habitat matching rule. This paper examines whether it is possible to maintain the assumption of the habitat matching rule in the following circumstances: (1) when habitats are connected and organisms can move between them, (2) when there are disturbances and seasonal cycles that generate instability, and (3) when there is inter‐specific and intra‐specific competition. Here I argue that it is possible as long as the following aspects are taken into account. In open habitats at equilibrium, in which habitat selection and competition operate, the habitat matching rule can be applied in some conditions, while competition tends to homogenize the species distribution in other environmental contexts. In the latter case, two methods can be used to incorporate these effects into SDMs: new parameters can be incorporated into the response functions, or the occurrence of proportions of categories of individuals (adult/young, male/female, or dominant/subordinate species in guilds) can be used instead of the occurrence of organisms. The habitat matching rule is not fulfilled in non‐equilibrium environments. The solution to this problem lies in the design of SDMs with two strategies that depend on scale. Locally, the disequilibrium can be encapsulated using average environmental conditions, with sufficiently large cells (in the case of metapopulations) and/or long enough sampling periods (in the case of seasonal cycles). At coarse scales, the use of presence‐only models can in some cases avoid the destabilizing effect of catastrophic historical processes. The matching law is a strong assumption of SDMs because it is based on population ecology theory and the principle of evolution by natural selection.     

Using a species distribution model to guide NSW surveys of the long‐footed potoroo (Potorous longipes)

Knowledge of threatened species’ distributions is essential for effective conservation decision‐making. Species distribution models (SDMs) are widely used to map species’ geographic ranges, identify new areas of suitable habitat and guide field surveys. In New South Wales (NSW), Australia, there are grave doubts about whether populations of the critically endangered long‐footed potoroo (Potorous longipes) remain extant, and identification of occupied sites is a high priority for its conservation. We used an SDM (Maxent) to identify regions in NSW that may have suitable habitat for the potoroo. The SDM was built with seven climate layers and had strong predictive performance (cross‐validated AUC = 0.94). We then combined this information on habitat suitability with vegetation and topography, to identify 58 survey sites across NSW. From April 2016 to May 2017, we undertook six field trips deploying six to eight cameras at each site for 52–63 days, resulting in 25 120 camera trap nights. A total of 215 759 images captured 43 native and feral animal species, but no long‐footed potoroos. Following the survey, newly available, independent presence and absence data were used to validate our model. A Kruskal–Wallis H test indicated that habitat suitability values were significantly higher at presence locations than absence locations (H = 58.66, d.f. = 1, P < 0.001). Finally, we refitted the Maxent model with the new data and identified additional regions that future surveys could explore. We conclude, however, that if the long‐footed potoroo remains extant in NSW, it is extremely rare.     

物种分布模型在海洋潜在生境预测的应用研究进展

海洋生物的栖息分布与环境要素的关联性一直是海洋生态学研究的热点之一.近年来,物种分布模型被广泛应用于预测海洋物种分布、潜在适宜性生境评价等研究,为保护海洋生物多样性、防治外来物种入侵及制定渔业管理措施等提供了一条有效途径.物种分布模型主要包括生境适宜性指数模型、机理模型和统计模型.本文对物种分布模型的理论基础进行了归纳和总结,回顾了物种分布模型在预测海洋物种潜在地理分布研究中的开发与应用,重点介绍了不同类型统计模型在海洋物种潜在分布预测中的研究实例.比较各种选取变量和模型验证方法,认为赤池信息准则对于选取模型变量具有优势,Kappa系数和受试者操作特征曲线下面积在验证模型精度中应用最广泛.阐述了物种分布模型存在的问题及未来发展趋势,随着海洋生物生理机制研究的进一步深入,机理模型将是今后物种分布模型发展的重点.     

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees

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Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change

Climate change influences species geographical distribution and diversity pattern. The Chinese fire‐bellied newt (Cynops orientalis) is an endemic species distributed in East‐central China, which has been classified as near‐threatened species recently due to habitat destruction and degradation and illegal trade in the domestic and international pet markets. So far, little is known about the spatial distribution of the species. Based on bioclimatic data of the current and future climate projections, we modeled the change in suitable habitat for C. orientalis by ten algorithms, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. In this study, 46 records of C. orientalis from East China and 8 bioclimatic variables were used. Among the ten modeling algorithms, four (GAM, GBM, Maxent, and RF) were selected according to their predictive abilities. The current habitat suitability showed that C. orientalis had a relatively wide but fragmented distribution, and it encompassed 41,862 km². The models suggested that precipitation of warmest quarter (bio18) and mean temperature of wettest quarter (bio6) had the highest contribution to the model. This study revealed that C. orientalis is sensitive to climate change, which will lead to a large range shift. The projected spatial and temporal pattern of range shifts for C. orientalis should provide a useful reference for implementing long‐term conservation and management strategies for amphibians in East China.     

集合种群动态对栖息地毁坏时空异质性的响应

栖息地毁坏既有时间异质性,也有空间异质性,而以往的研究往往只关注其中的一种。将两种不同的异质性共同引入到元胞自动机中,模拟了集合种群动态对栖息地毁坏时空异质性的响应。发现,在随机离散的栖息地毁坏下,由于物种的迁移繁殖力受栖息地毁坏的影响很大,迁移繁殖力弱而竞争力强的物种先灭绝。在连续的栖息地毁坏下,物种的迁移繁殖力受栖息地毁坏的影响较小,物种的灭绝由竞争力和迁移繁殖力共同决定:在有绝对优势种的群落里,种间竞争显著,弱物种先灭绝,而在没有绝对优势种的群落里,种间竞争较小,则以强物种先灭绝。因此,随机毁坏不利于强物种续存,而连续毁坏则不利于具有绝对优势种群的群落里的弱物种续存。在实际开发某一栖息地时,根据集合种群结构和被保护的对象采取相应的开发模式。     

Relationship between tropical cyclones and the distribution of sea turtle nesting grounds

Aim This study examines the relationship between the distribution of existing sea turtle nesting sites and historical patterns of tropical cyclone events to investigate whether cyclones influence the current distribution of sea turtle nesting sites. The results, together with information on predicted cyclone activity and other key environmental variables, will help in the identification and prediction of future nesting sites for sea turtles as changes to the coastal environment continue. Location Queensland, Australia. Methods We used data on the nesting distribution of seven populations of four species of sea turtles [green (Chelonia mydas), flatback (Natator depressus), hawksbill (Eretmochelys imbricata) and loggerhead (Caretta caretta)] from the eastern Queensland coast, and tropical cyclone track data from 1969 to 2007 to explore the relationship between (1) sea turtle nesting phenology and cyclone season, and (2) sea turtle nesting sites and cyclone distribution. Furthermore, using two green turtle populations as a case study, we investigated the relationship between cyclone disturbance and sea turtle reproductive output, nesting site and season. Bootstrapping was used to explore if current sea turtle nesting sites are located in areas with lower or higher cyclone frequency than areas where turtles are currently not nesting. Results All populations of sea turtles studied here were disturbed by cyclone activity during the study period. The exposure (frequency) of tropical cyclones that crossed each nesting site varied greatly among and within the various sea turtle populations. This was mainly a result of the spatial distribution of each population’s nesting sites. Bootstrapping indicated that nesting sites generally have experienced lower cyclone activity than other areas that are available for nesting. Main conclusions Tropical cyclones might have been sufficiently detrimental to sea turtle hatching success on the eastern Queensland coast that through a natural selection process turtles in this region are now nesting in areas with lower cyclone activity. Therefore, it is important that future studies that predict climate or range shifts for sea turtle nesting distributions consider future cyclone activity as one of the variables in their model.     

Using multilevel models to identify drivers of landscape‐genetic structure among management areas

Landscape genetics offers a powerful approach to understanding species' dispersal patterns. However, a central obstacle is to account for ecological processes operating at multiple spatial scales, while keeping research outcomes applicable to conservation management. We address this challenge by applying a novel multilevel regression approach to model landscape drivers of genetic structure at both the resolution of individuals and at a spatial resolution relevant to management (i.e. local government management areas: LGAs) for the koala (Phascolartos cinereus) in Australia. Our approach allows for the simultaneous incorporation of drivers of landscape‐genetic relationships operating at multiple spatial resolutions. Using microsatellite data for 1106 koalas, we show that, at the individual resolution, foliage projective cover (FPC) facilitates high gene flow (i.e. low resistance) until it falls below approximately 30%. Out of six additional land‐cover variables, only highways and freeways further explained genetic distance after accounting for the effect of FPC. At the LGA resolution, there was significant variation in isolation‐by‐resistance (IBR) relationships in terms of their slopes and intercepts. This was predominantly explained by the average resistance distance among LGAs, with a weaker effect of historical forest cover. Rates of recent landscape change did not further explain variation in IBR relationships among LGAs. By using a novel multilevel model, we disentangle the effect of landscape resistance on gene flow at the fine resolution (i.e. among individuals) from effects occurring at coarser resolutions (i.e. among LGAs). This has important implications for our ability to identify appropriate scale‐dependent management actions.     

Hedgerow presence does not enhance indicators of nest‐site habitat quality or nesting rates of ground‐nesting bees

A major challenge in habitat restoration is targeting the key aspects of a species' niche for enhancement, particularly for species that use a diverse set of habitat features. However, restoration that focuses on limited aspects of a species' niche may neglect other resources that are critical to population persistence. We evaluated the ability of native plant hedgerows, planted to increase pollen and nectar resources for wild bees in agricultural landscapes, to provide suitable nesting habitat and enhance nesting rates of ground‐nesting bees. We found that, when compared to unmanaged field edges (controls), hedgerows did not augment most indicators of nest habitat quality (bare ground, soil surface irregularity, and soil hardness), although coarser soils were associated with higher incidence and richness of nesting bees. Hedgerows did not augment nesting rates when compared to control edges. Although all the bee species we detected nesting were also found foraging on floral resources, the foraging versus nesting assemblages found within a site were highly dissimilar. These results may reflect sampling error; or, species found foraging but not nesting in hedgerows could be utilizing hedgerows as “partial habitats,” nesting outside hedgerow plantings but foraging on the floral resources they provide. We conclude that although hedgerows are known to provide critical floral resources to wild bees especially in resource‐poor intensive agricultural landscapes, simply increasing vegetative diversity and structure may not be simultaneously enhancing nesting habitat for ground‐nesting bees.     

Integrating species distribution models and interacting particle systems to predict the spread of an invasive alien plant

Aim We demonstrate how to integrate two widely used tools for modelling the spread of invasive plants, and compare the performance of the combined model with that of its individual components using the recent range dynamics of the invasive annual weed Ambrosia artemisiifolia L. Location Austria. Methods Species distribution models, which deliver habitat‐based information on potential distributions, and interacting particle systems, which simulate spatio‐temporal range dynamics as dependent on neighbourhood configurations, were combined into a common framework. We then used the combined model to simulate the invasion of A. artemisiifolia in Austria between 1990 and 2005. For comparison, simulations were also performed with models that accounted only for habitat suitability or neighbourhood configurations. The fit of the three models to the data was assessed by likelihood ratio tests, and simulated invasion patterns were evaluated against observed ones in terms of predictive discrimination ability (area under the receiver operating characteristic curve, AUC) and spatial autocorrelation (Moran’s I). Results The combined model fitted the data significantly better than the single‐component alternatives. Simulations relying solely on parameterized spread kernels performed worst in terms of both AUC and spatial pattern formation. Simulations based only on habitat information correctly predicted infestation of susceptible areas but reproduced the autocorrelated patterns of A. artemisiifolia expansion less adequately than did the integrated model. Main conclusions Our integrated modelling approach offers a flexible tool for forecasts of spatio‐temporal invasion patterns from landscape to regional scales. As a further advantage, scenarios of environmental change can be incorporated consistently by appropriately updating habitat suitability layers. Given the susceptibility of many alien plants, including A. artemisiifolia, to both land use and climate changes, taking such scenarios into account will increasingly become relevant for the design of proactive management strategies.     

物种保护的理论基础——从岛屿生物地理学理论到集合种群理论

全球面临着生境破碎化的危机,物种保护已成为人类面临的重大课题,并不是所有的人对岛屿生物地理学理论的产生及其关注的海洋岛屿都很熟悉,但是越来越多生物赖以生存的自然栖息地的丧失和破碎化都是有目共睹的,岛屿生物地理学和集合种群理论是目前物种保护的两个基本理论,物种迁入率和绝灭率的动态变化决策岛屿上的物种丰富度是岛屿生物地理学理论的核心内容,而集合种群理论关注的是局部种群之间个体迁移的动态以及物种的续存条件,在概述两个理论形成、发展及其核心内容的基础上,着重比较它们的异同点以及在生态学理论和实践中的应用,并论述物种保护理论范式从岛屿生物地理学向集合种群理论转变的基本背景和原因。     

生境破坏的模式对集合种群动态和续存的影响

构建了空间关联的集合种群模型,该模型不但包含了种群的空间结构信息,而且引入了破坏生境的全局密度和局部密度两个指标,它们描述了破坏生境的模式.模型揭示了破坏生境的空间分布格局复杂地影响了集合种群的动态和续存,破坏和未破坏生境斑块的均匀混合不利于集合种群的增长和续存,而生境类型聚集分布可以促进集合种群的快速增长和长期续存;对于两种斑块类型相对均匀混合的生境来说,均匀场假设可能会高估集合种群的续存,对于相对斑块类型高度聚集的生境,均匀场假设可能会低估集合种群的续存;物种的迁移范围也会影响集合种群的续存,迁移范围越大的物种越容易抵御生境的破坏而免遭灭绝.这意味着在生物保护中不能仅仅考虑生境的恢复和斑块质量的改善,生境结构的构建也是很重要的,加强生境斑块之间的连通性也有利于物种的长期续存.     

Effects of species and habitat positional errors on the performance and interpretation of species distribution models

Aim A key assumption in species distribution modelling is that both species and environmental data layers contain no positional errors, yet this will rarely be true. This study assesses the effect of introduced positional errors on the performance and interpretation of species distribution models. Location Baixo Alentejo region of Portugal. Methods Data on steppe bird occurrence were collected using a random stratified sampling design on a 1‐km² pixel grid. Environmental data were sourced from satellite imagery and digital maps. Error was deliberately introduced into the species data as shifts in a random direction of 0–1, 2–3, 4–5 and 0–5 pixels. Whole habitat layers were shifted by 1 pixel to cause mis‐registration, and the cumulative effect of one to three shifted layers investigated. Distribution models were built for three species using three algorithms with three replicates. Test models were compared with controls without errors. Results Positional errors in the species data led to a drop in model performance (larger errors having larger effects – typically up to 10% drop in area under the curve on average), although not enough for models to be rejected. Model interpretation was more severely affected with inconsistencies in the contributing variables. Errors in the habitat layers had similar although lesser effects. Main conclusions Models with species positional errors are hard to detect, often statistically good, ecologically plausible and useful for prediction, but interpreting them is dangerous. Mis‐registered habitat layers produce smaller effects probably because shifting entire layers does not break down the correlation structure to the same extent as random shifts in individual species observations. Spatial autocorrelation in the habitat layers may protect against species positional errors to some extent but the relationship is complex and requires further work. The key recommendation must be that positional errors should be minimised through careful field design and data processing.     

虚拟物种的基本原理及其在物种分布模型评估中的应用

物种分布模型是建立在物种出现或缺失数据的基础上,但可获得的真实分布数据存在着各种各样的缺点(如:物种识别错误、坐标错误、抽样偏差、数据缺失等),影响着物种分布模型的预测性能、稳定性及应用,因此使用物种真实分布数据评估物种分布模型将带来很大的不确定性。为避免这种不确定性,越来越多的研究使用虚拟物种来评价物种分布模型的性能,评估新方法的优劣。虚拟物种是一种建立在真实(或虚拟)地理信息系统下人工生命,是简化和抽象的物种,它通过模拟物种对环境变量的响应关系,评估物种在不同环境变量下的出现概率,人为地给出虚拟的物种分布数据。虚拟物种具有数据容易获得、数据质量可控、避免过度模拟等优势,目前它被广泛用于评估物种特性、抽样偏差、地理信息、出现/缺失标准等对物种分布模型性能的影响。虚拟物种是大尺度研究中不可或缺的重要工具,有利于解决真实数据未能解决的科学问题。常用的构成算法有求和法、求积法和综合法,但这些方法可能存在补偿效应,扩大了物种的分布范围。考虑到虚拟物种的不足,提出了未来虚拟物种可能的发展方向(避免过度脱离真实,完善虚拟物种的构成算法,构建虚拟的模式生物、群落及生态系统等)。为帮助研究者快速构建虚拟物种,基于R环境开发了一个虚拟物种构成软件包(SDMvspecies)。虚拟物种可以与真实物种相结合,通过改进模型的构成方法,有利于解决一些真实数据未能解决的问题;虚拟物种的应用也将导致一些新理论的产生,有利于更好地理解生态学原理。     

Temporal transferability of wildlife habitat models: implications for habitat monitoring

Aim Temporal transferability is an important issue when habitat models are used beyond the time frame corresponding to model development, but has not received enough attention, particularly in the context of habitat monitoring. While the combination of remote sensing technology and habitat modelling provides a useful tool for habitat monitoring, the effect of incorporating remotely sensed data on model transferability is unclear. Therefore, our objectives were to assess how different satellite‐derived variables affect temporal transferability of habitat models and their usefulness for habitat monitoring. Location Wolong Nature Reserve, Sichuan Province, China. Methods We modelled giant panda habitat with the maximum entropy algorithm using panda presence data collected in two time periods and four different sets of predictor variables representing land surface phenology. Each predictor variable set contained either a time series of smoothed wide dynamic range vegetation index (WDRVI) or 11 phenology metrics, both derived from single‐year or multi‐year (i.e. 3‐year) remotely sensed imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). We evaluated the ability of models obtained with these four variable sets to predict giant panda habitat within and across time periods by using threshold‐independent and threshold‐dependent evaluation methods and five indices of temporal transferability. Results Our results showed that models developed with the four variable sets were all useful for characterizing and monitoring giant panda habitat. However, the models developed using multi‐year data exhibited significantly higher temporal transferability than those developed using single‐year data. In addition, models developed with phenology metrics, especially when using multi‐year data, exhibited significantly higher temporal transferability than those developed with the time series. Main conclusions The integration of land surface phenology, captured by high temporal resolution remotely sensed imagery, with habitat modelling constitutes a suitable tool for characterizing wildlife habitat and monitoring its temporal dynamics. Using multi‐year phenology metrics reduces model complexity, multicollinearity among predictor variables and variability caused by inter‐annual climatic fluctuations, thereby increasing the temporal transferability of models. This study provides useful guidance for habitat monitoring through the integration of remote sensing technology and habitat modelling, which may be useful for the conservation of the giant panda and many other species.     

Predicting species distribution: offering more than simple habitat models

In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.