洲际入侵植物生态位稳定性研究进展

人类活动引起的大规模洲际物种交换与生物入侵, 改变了当地生态系统结构与功能, 使生物多样性受到日益严重的威胁。本文通过综合分析主要国家和地区入侵植物的地理起源, 发现洲际入侵主要包括东亚—北美、东亚—南美、欧洲—南非、欧洲—北美、欧洲—东亚、北美—大洋洲等, 这些洲际入侵造成的后果往往比陆内入侵更为严重。利用物种分布模型(SDMs)预测入侵物种潜在分布范围是有效管理和提早预防生物入侵的重要依据, 但这些模型的一个关键假定是: 入侵物种的生态位在空间和时间上是保守的、稳定的。然而, 对于远离原产地种群并能快速适应新生境的洲际入侵植物来说, 生态位可能发生显著的变化。入侵种能否在入侵地保持原有的生态位, 取决于制约其生态分布的限制因素和生态过程在不同地区间是否发生变化。本文中作者总结了洲际入侵与陆内入侵的生态与进化过程的异同点, 认为这些限制物种原产地分布的因素如扩散限制、种间互作、适应性进化、生态可塑性和种群遗传特性等均可能导致入侵物种生态位的改变。建议下一步的研究应该重视: (1)对生态位属性进行多尺度的研究, 包括时间、空间、环境或系统发育等几个方面; (2)对比生态位稳定与发生偏移的物种特性, 确定什么样的入侵物种更容易改变原有的生态位; (3)进行生态位时间动态格局研究, 探讨生态位变化的倾向、历史速率和偏移程度, 以便判定生态位变化趋势。这些研究结果将会进一步提高物种分布模型的预测能力, 有助于更为准确地揭示气候变化和物种入侵对生物多样性的影响。     

A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area

To investigate the comparative abilities of six different bioclimatic models in an independent area, utilizing the distribution of eight different species available at a global scale and in Australia. Global scale and Australia. We tested a variety of bioclimatic models for eight different plant species employing five discriminatory correlative species distribution models (SDMs) including Generalized Linear Model (GLM), MaxEnt, Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, together with CLIMEX (CL) as a mechanistic niche model. These models were fitted using a training dataset of available global data, but with the exclusion of Australian locations. The capabilities of these techniques in projecting suitable climate, based on independent records for these species in Australia, were compared. Thus, Australia is not used to calibrate the models and therefore it is as an independent area regarding geographic locations. To assess and compare performance, we utilized the area under the receiver operating characteristic (ROC) curves (AUC), true skill statistic (TSS), and fractional predicted areas for all SDMs. In addition, we assessed satisfactory agreements between the outputs of the six different bioclimatic models, for all eight species in Australia. The modeling method impacted on potential distribution predictions under current climate. However, the utilization of sensitivity and the fractional predicted areas showed that GLM, MaxEnt, Bioclim, and CL had the highest sensitivity for Australian climate conditions. Bioclim calculated the highest fractional predicted area of an independent area, while RF and BRT were poor. For many applications, it is difficult to decide which bioclimatic model to use. This research shows that variable results are obtained using different SDMs in an independent area. This research also shows that the SDMs produce different results for different species; for example, Bioclim may not be good for one species but works better for other species. Also, when projecting a “large” number of species into novel environments or in an independent area, the selection of the “best” model/technique is often less reliable than an ensemble modeling approach. In addition, it is vital to understand the accuracy of SDMs' predictions. Further, while TSS, together with fractional predicted areas, are appropriate tools for the measurement of accuracy between model results, particularly when undertaking projections on an independent area, AUC has been proved not to be. Our study highlights that each one of these models (CL, Bioclim, GLM, MaxEnt, BRT, and RF) provides slightly different results on projections and that it may be safer to use an ensemble of models.     

Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges

Species distribution models (SDMs) use spatial environmental data to make inferences on species' range limits and habitat suitability. Conceptually, these models aim to determine and map components of a species' ecological niche through space and time, and they have become important tools in pure and applied ecology and evolutionary biology. Most approaches are correlative in that they statistically link spatial data to species distribution records. An alternative strategy is to explicitly incorporate the mechanistic links between the functional traits of organisms and their environments into SDMs. Here, we review how the principles of biophysical ecology can be used to link spatial data to the physiological responses and constraints of organisms. This provides a mechanistic view of the fundamental niche which can then be mapped to the landscape to infer range constraints. We show how physiologically based SDMs can be developed for different organisms in different environmental contexts. Mechanistic SDMs have different strengths and weaknesses to correlative approaches, and there are many exciting and unexplored prospects for integrating the two approaches. As physiological knowledge becomes better integrated into SDMs, we will make more robust predictions of range shifts in novel or non-equilibrium contexts such as invasions, translocations, climate change and evolutionary shifts.     

Improving species distribution models for climate change studies: variable selection and scale

Statistical species distribution models (SDMs) are widely used to predict the potential changes in species distributions under climate change scenarios. We suggest that we need to revisit the conceptual framework and ecological assumptions on which the relationship between species distributions and environment is based. We present a simple conceptual framework to examine the selection of environmental predictors and data resolution scales. These vary widely in recent papers, with light inconsistently included in the models. Focusing on light as a necessary component of plant SDMs, we briefly review its dependence on aspect and slope and existing knowledge of its influence on plant distribution. Differences in light regimes between north‐ and south‐facing aspects in temperate latitudes can produce differences in temperature equivalent to moves 200 km polewards. Local topography may create refugia that are not recognized in many climate change SDMs using coarse‐scale data. We argue that current assumptions about the selection of predictors and data resolution need further testing. Application of these ideas can clarify many issues of scale, extent and choice of predictors, and potentially improve the use of SDMs for climate change modelling of biodiversity.     

Essential elements of discourse for advancing the modelling of species' current and potential distributions

A recent review by Dormann et al. (2012, Journal of Biogeography, 39 , 2119–2131) has proposed that methods for the modelling of species distributions be considered as a continuum. We disagree with this thesis, and contend that attempting to present the diverse range of methods as a continuum is unhelpful and ultimately not convincing. It adds to the confusion about the strengths and weaknesses of the diversity of available modelling methods, what exactly it is that they model, and the most appropriate applications. We highlight variation within and between modelling methods that is obscured by the continuum framework and propose that context of application and clarity of method are critical elements for future discourse on the topic.     

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.     

Using avatar species to model the potential distribution of emerging invaders

Aim Anticipating the potential distributions of emerging invasive species is complicated by the tendency for species distribution models to perform better when both native and invasive range data are available for model development. If invasive range data are lacking, species models are liable to under‐estimate distributions for emerging invaders, particularly for species that are not at equilibrium with their native range environment due to historical factors, dispersal limitation and/or ecological interactions. We demonstrate the potential to use well‐quantified niche shifts from established ‘avatar’ (i.e. the remote or virtual manifestation of an entity) invaders to develop plausible distributions for data‐poor emerging invaders contingent on niche shifts of similar magnitude or character. Location Global. Methods Using the globally invasive crayfishes Pacifastacus leniusculus and Procambarus clarkii as our avatar invaders, we quantify how niche position, size and structure differs between native and total ranges using Mahalanobis distance (a measure of multivariate similarity) and the climate predictors of annual minimum and maximum air temperature. We then generalize patterns of niche shift from these species to the emerging crayfish invader Cherax quadricarinatus. Results Some patterns of niche shifts were similar for Pacifastacus leniusculus and Procambarus clarkii, but niche shifts were of considerably greater magnitude for P. clarkii. When a native range model for C. quadricarinatus was modified with generalized niche shifts similar to Pacifastacus leniusculus and Procambarus clarkii, the potential global distribution for this species increased considerably, including many areas not identified by the native range model. Main conclusions We illustrate the potential to use avatar invaders to provide cautionary, niche shift‐assuming species distribution models for emerging invaders. Many theoretical and applied implications of the avatar species concept require additional investigation, including the development of frameworks to select appropriate avatar species and evaluate the performance of avatar‐derived models for emerging invaders. Despite these research needs, we believe this concept will have considerable utility for predicting vulnerability to invasion by data‐poor species; this is a critical management need because shifting pathways of introduction and climate change will produce many novel, emerging invasive species in the future.     

A niche for biology in species distribution models

Why species are found where they are is a central question in biogeography. The most widely used tool for understanding the controls on distribution is species distribution modelling. Species distribution modelling is now a well‐established method in both the theoretical and applied ecological literature. In this special issue we examine the current state of the art in species distribution modelling and explore avenues for including more biological processes in such models. In particular we focus on physiological, demographic, dispersal, competitive and ecological‐modulation processes. This overview highlights opportunities for new species distribution model concepts and developments, as well as a statistical agenda for implementing such models.     

Ecological niche modeling of coastal dune plants and future potential distribution in response to climate change and sea level rise

Climate change (CC) and sea level rise (SLR) are phenomena that could have severe impacts on the distribution of coastal dune vegetation. To explore this we modeled the climatic niches of six coastal dunes plant species that grow along the shoreline of the Gulf of Mexico and the Yucatan Peninsula, and projected climatic niches to future potential distributions based on two CC scenarios and SLR projections. Our analyses suggest that distribution of coastal plants will be severely limited, and more so in the case of local endemics (Chamaecrista chamaecristoides, Palafoxia lindenii, Cakile edentula). The possibilities of inland migration to the potential ‘new shoreline’ will be limited by human infrastructure and ecosystem alteration that will lead to a ‘coastal squeeze’ of the coastal habitats. Finally, we identified areas as future potential refuges for the six species in central Gulf of Mexico, and northern Yucatán Peninsula especially under CC and SLR scenarios.     

Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae

Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species’ distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent‐rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold‐temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern‐lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over‐predict species prevalence, as they cannot identify absences in climatic conditions within the species’ range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species’ niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change.     

Predicting the global areas for potential distribution of Gastrodia elata based on ecological niche models

Aims Previous studies on the globally suitable areas for growing the medicinal plant Gastrodia elata is lacking. This study aims to predict the global areas for potential distribution of this plant based on multiple ecological niche models. Methods A total of 220 global distribution points of G. elata and 19 ecological variables were compiled and eight environmental variables were selected for the model training. Three ecological niche models, including BIOCLIM, DOMAIN, and MAXENT, were used to predict the global areas for potential distribution of G. elata. The resulting data of different models were analyzed and compared with two statistical criteria: the area under the receiver operating characteristic curve (AUC) and Kappa value. Important findings The predictions of the three models are basically identical, showing that the global areas for potential distribution of G. elata are predominantly in the range of 20° N to 50° N in Asia, mainly in China, South Korea and Japan. A small proportion of the suitable areas occur in India, Nepal and the European countries near Mediterranean. The most suitable areas distribute in provinces close to the Sichuan Basin and the central East China, the mid-eastern parts of South Korea such as Chungcheongbuk-do, Gyeongsangbuk-do and Gyeongsangnam- do, and the Kyushu region and the Shikoku region on Japan’s main island. Therefore, these three countries can be used as the main production areas of G. elata for its commercial development. The AUC average values of the three models are all above 0.9 and the Kappa average values all above 0.65, justifying their applications for predicting the potential areas of G. elata. Among them, the MAXENT model appears to perform the best, followed by DOMAIN and BIOCLIM.     

Neutral theory and the species abundance distribution: recent developments and prospects for unifying niche and neutral perspectives

Published in 2001, The Unified Neutral Theory of Biodiversity and Biogeography (UNTB) emphasizes the importance of stochastic processes in ecological community structure, and has challenged the traditional niche‐based view of ecology. While neutral models have since been applied to a broad range of ecological and macroecological phenomena, the majority of research relating to neutral theory has focused exclusively on the species abundance distribution (SAD). Here, we synthesize the large body of work on neutral theory in the context of the species abundance distribution, with a particular focus on integrating ideas from neutral theory with traditional niche theory. First, we summarize the basic tenets of neutral theory; both in general and in the context of SADs. Second, we explore the issues associated with neutral theory and the SAD, such as complications with fitting and model comparison, the underlying assumptions of neutral models, and the difficultly of linking pattern to process. Third, we highlight the advances in understanding of SADs that have resulted from neutral theory and models. Finally, we focus consideration on recent developments aimed at unifying neutral‐ and niche‐based approaches to ecology, with a particular emphasis on what this means for SAD theory, embracing, for instance, ideas of emergent neutrality and stochastic niche theory. We put forward the argument that the prospect of the unification of niche and neutral perspectives represents one of the most promising future avenues of neutral theory research.     

Pitch the niche – taking responsibility for the concepts we use in ecology and species distribution modelling

In a discussion it is often easier to staunchly reject or offer resolute support for an idea. This third paper on the niche concept aims to develop a balanced argument by exploring general principles for determining an appropriate level for pitching the niche concept that will guide better use and less abuse of niche concepts. To do this we first have to accept that niche concepts are not necessarily essential for ecology. Rather than to improve niche concepts, our aim should then be to pitch the niche in terms of ecology. This aim helps us develop an ‘ultimate goal of the niche’ by which we can evaluate the concepts we use. For species distribution modelling, there has been a focus on the niche as an equilibrium outcome that perhaps has less relevance for disequilibrium situations (e.g. climate change projections). As is the case for much of ecology, more causal explanations of species' distributions use alternative terminologies and less frequently use the word ‘niche’. We suggest that niche concepts that are better aligned with the rest of ecology could arise from taking more responsibility for our own implementations, and by explaining our models with terms other than niche. A general, holistic niche concept promotes this view and promotes practical thinking about what we are modelling and how we interpret those models, which in turn should help inspire and support innovative modelling approaches in species distribution modelling.     

A simple method to estimate the probable distribution of species

Species distribution models (SDMs) are broadly used to predict species distributions from available presence data. However, SDMs results have been criticized for several reasons mainly related to two basic characteristics of most SDMs: 1) general lack of reliable species absence information, 2) the frequent use of an arbitrary geographical extent (GE) or accessible area of the species. These impediments have motivated us to generate a procedure called niche of occurrence (NOO). NOO provides the probable distribution of species (realized niche) relying solely on partial information about presence of species. It operates within a natural geographical extent delimited by available observations and avoids using misleading thresholds to obtain binary presence–absence estimations when the species prevalence is unknown. In this study the main characteristics of NOO are presented, comparing its performance with other recognized and more complex SDMs by using virtual species to avoid the omnipresent error sources of real data sets.