空间直观景观模型的验证方法

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

Field theory for biogeography: a spatially explicit model for predicting patterns of biodiversity

Predicting the variation of biodiversity across the surface of the Earth is a fundamental issue in ecology, and in this article we focus on one of the most widely studied spatial biodiversity patterns: the species–area relationship (SAR). The SAR is a central tool in conservation, being used to predict species loss following global climate change, and is striking in its universality throughout different geographical regions and across the tree of life. In this article we draw upon the methods of quantum field theory and the foundation of neutral community ecology to derive the first spatially explicit neutral prediction for the SAR. We find that the SAR has three phases, with a power law increase at intermediate scales, consistent with decades of documented empirical patterns. Our model also provides a building block for incorporating non-neutral biological variation, with the potential to bridge the gap between neutral and niche-based approaches to community assembly.
Ecology Letters (2010) 13: 87–95     

像元尺度上不确定性对空间景观直观模型模拟的影响

LANDIS模型是模拟自然和人为干扰下森林景观变化的空间直观景观模型。模型把景观概念化为由相同大小的像元或样地组成的格网。在每一个像元上,模型要求输入物种和年龄组信息。但是,由于研究区一般由成千上百万个像元构成,不可能通过实际调查获取每一个像元上的物种和年龄组信息。因此,采用了一种基于小班的随机赋值法从森林调查数据中获取每一个像元的物种和年龄组信息。该方法是一种基于概率的方法,会在LANDIS模型模拟的物种和年龄组信息的输入中引入不确定性。为了评价由基于小班的随机赋值法所引入像元尺度上的不确定性对模型模拟结果的影响,用蒙特卡罗模拟法进行不确定性分析。对LANDIS模型模拟的每一个物种,用众数年龄组发生频率来定量化单个像元上年龄组信息的不确定性,用所有像元上的众数年龄组平均发生频率来定量化年龄组信息在像元尺度上总的不确定性。平均发生频率越高,不确定性越低。为了评价基于小班的随机赋值法对景观尺度上模型模拟结果的影响,计算了每一个物种在整个研究区内的面积百分比和聚集度指数。变异系数越大,不确定性越高。对所有物种,年龄组信息不确定性在模型模拟的初期是比较低的(平均发生频率大于10)。种子传播、建群、死亡和火干扰使模型结果的不确定性随模拟时间增加而增加。最后,不确定性达到稳定状态,达到平衡状态的时间与物种寿命接近。此时,初始的物种和年龄组信息不再对模型结果有影响。在景观尺度上,物种分布面积百分比和由聚集度指数所定量化的空间格局并未受像元尺度上不确定性增加的影响。因为LANDIS模型模拟研究的目的在于预测总的景观格局变化,而不是单一的事件,所以,基于小班的随机赋值法可用于LANDIS模型的参数化。     

The effects of archipelago spatial structure on island diversity and endemism: predictions from a spatially‐structured neutral model

Islands are particularly suited to testing hypotheses about the ecological and evolutionary mechanisms underpinning community assembly. Yet the complex spatial arrangements of real island systems have received little attention from both empirical studies and theoretical models. Here, we investigate the extent to which the spatial structure of archipelagos affects species diversity and endemism. We start by proposing a new spatially structured neutral model that explicitly considers archipelago structure, and then investigate its predictions under a diversity of scenarios. Our results suggest that considering the spatial structure of archipelagos is crucial to understanding their diversity and endemism, with structured island systems acting both as “museums” and “cradles” of biodiversity. These dynamics of diversification may change the traditionally expected pattern of decrease in species richness with distance from the mainland, even potentially leading to increasing patterns for taxa with high speciation rates in archipelagos off species‐poor continental areas. Our results also predict that, within spatially structured archipelagos, metapopulation dynamics and evolutionary processes can generate higher diversity on islands more centrally placed than at the periphery. We derive from our results a set of theoretical predictions, potentially testable with empirical data.     

A spatially explicit model of patchy stomatal responses to humidity

Stomata of leaves can exhibit either temporally stable, spatially homogeneous behaviour or complex spatial and temporal dynamics, depending on environmental and physiological conditions. To test the ability of accepted physiological mechanisms to describe these patterns, we developed a simple, spatially explicit model of stomatal responses to humidity that incorporated hydraulic interactions among stomata. Model results showed qualitative agreement with experimental evidence for a number of phenomena: (1) at high humidities, whole-leaf steady-state conductance is a monotonic function of humidity; (2) the initial stomatal response following a perturbation in humidity is in the direction opposite to the final response, and (3) spatial dynamics include patch formation and self-organization similar to that observed in actual leaves. These comparisons do not eliminate other explanations, but do suggest that novel mechanisms need not be invoked to explain the diversity of spatial and temporal patterns of stomatal behaviour in leaves.     

空间直观景观模型LANDIS在大兴安岭呼中林区的应用

应用空间直观景观模型(LANDIS),研究有采伐和无采伐预案下大兴安岭呼中林区的森林景观的长期变化。用APACK计算每一个物种及各年龄级的分布面积。为了研究物种分布格局的变化,计算了物种分布的聚集度指数。研究结果如下：(1)在无采伐预案下。火干扰模式为低频率大面积高强度火烧;在有采伐预下,火干扰模式为高频率小面积低强度火烧;(2)在无采伐预案下,火会造成各种群分布面积的强烈波动,但是对种群的年龄结构没有很大影响;在有采伐预案下,火对种群分布面积和年龄结构都没有很大的影响;(3)采伐能完全改变各种群的年龄结构。降低种群分布的聚集度,但是对各种群的分布面积并没有很大影响;(4)在有采伐预案下,各种群为增长型种群,增长量通过采伐取走,群落处于演替的干扰顶极状态;在无采伐预案下,各种群为稳定型种群(樟子松和偃松除外),大面积高强度火烧使群落产生较大的波动。结果表明,在呼中林业局,在没有人为干扰情况下,火干扰是森林景观变化的主导因素。自从有了人为干扰,采伐开始逐渐取代火干扰成为影响森林景观变化的主导因素。空间直观景观模型的一个挑战是模型的验证。由于缺乏详细的空间数据及模型模拟中的随机性,很难通过模型模拟结果与实地调查或遥感数据的比较进行验证。通过对火模拟、物种分布和物种组成的生态或生物学实现对模型进行验证。     

空间直观景观模型在呼中林区土壤侵蚀预测研究中的初步应用

土壤通用流失方程(USLE)已被广泛应用于大尺度的土壤侵蚀预测．在以往的土壤侵蚀研究中,由于只能获得静态的植被图,土壤通用流失方程只能用于土壤侵蚀的静态估算．空间直观景观模型能在大尺度上模拟植被动态,为土壤通用流失方程提供动态的植被因子,从而使土壤侵蚀的动态模拟成为可能．本研究结合空间直观景观模型LANDIS和土壤通用流失修正方程,以大兴安岭呼中林区为研究区。动态地模拟未来650年内有采伐和无采伐预案下的土壤侵蚀量;同时以无火无采伐预案下的土壤侵蚀为对比值．结果表明,土壤侵蚀量随时间变化呈周期性的波动,其波动程度在无火无采伐预案下最小,而在有火无采伐预案下最大;采伐对土壤侵蚀的影响没有火对土壤侵蚀的影响在空间上表现得明显,但是其累积效果则比火的影响强;降低采伐所产生的裸露土能有效降低年平均土壤侵蚀量,但是对土壤侵蚀动态变化的影响不明显;虽然采伐增加使平均土壤侵蚀量增加,但是也同时使土壤侵蚀的年际变化更趋于平稳．     

Moving beyond abundance distributions: neutral theory and spatial patterns in a tropical forest

Assessing the relative importance of different processes that determine the spatial distribution of species and the dynamics in highly diverse plant communities remains a challenging question in ecology. Previous modelling approaches often focused on single aggregated forest diversity patterns that convey limited information on the underlying dynamic processes. Here, we use recent advances in inference for stochastic simulation models to evaluate the ability of a spatially explicit and spatially continuous neutral model to quantitatively predict six spatial and non-spatial patterns observed at the 50 ha tropical forest plot on Barro Colorado Island, Panama. The patterns capture different aspects of forest dynamics and biodiversity structure, such as annual mortality rate, species richness, species abundance distribution, beta-diversity and the species–area relationship (SAR). The model correctly predicted each pattern independently and up to five patterns simultaneously. However, the model was unable to match the SAR and beta-diversity simultaneously. Our study moves previous theory towards a dynamic spatial theory of biodiversity and demonstrates the value of spatial data to identify ecological processes. This opens up new avenues to evaluate the consequences of additional process for community assembly and dynamics.     

Characterising extinction debt following habitat fragmentation using neutral theory

Habitat loss leads to species extinctions, both immediately and over the long term as ‘extinction debt’ is repaid. The same quantity of habitat can be lost in different spatial patterns with varying habitat fragmentation. How this translates to species loss remains an open problem requiring an understanding of the interplay between community dynamics and habitat structure across temporal and spatial scales. Here we develop formulas that characterise extinction debt in a spatial neutral model after habitat loss and fragmentation. Central to our formulas are two new metrics, which depend on properties of the taxa and landscape: ‘effective area’, measuring the remaining number of individuals and ‘effective connectivity’, measuring individuals’ ability to disperse through fragmented habitat. This formalises the conventional wisdom that habitat area and habitat connectivity are the two critical requirements for long‐term preservation of biodiversity. Our approach suggests that mechanistic fragmentation metrics help resolve debates about fragmentation and species loss.     

Linking species-area and species-energy relationships in Drosophila microcosms

Resource availability is an important constraint on community structure. Some authors have suggested it conceptually links two of the most basic patterns in ecology, the species–area relationship and the latitudinal gradient in species richness. I present the first experimental test of this conjecture, by manipulating both the area and resource concentration of artificial larval drosophilid fly habitats and then allowing colonization from a natural species pool. Both the abundance and species richness of these habitats depended upon the total quantity of resources available, regardless of whether those resources were contained within smaller high-quality habitats or larger poor-quality habitats. While the intercepts of species–area relationships varied with resource concentration, they all collapsed onto the same species–energy curve. These results support the view that energetic constraints are of fundamental importance in structuring ecological communities, and that such constraints may even help explain ecological patterns such as the species–area relationship that do not explicitly address resource availability.     

Time-dependent solutions of the spatially implicit neutral model of biodiversity

Previous research into the neutral theory of biodiversity has focused mainly on equilibrium solutions rather than time-dependent solutions. Understanding the time-dependent solutions is essential for applying neutral theory to ecosystems in which time-dependent processes, such as succession and invasion, are driving the dynamics. Time-dependent solutions also facilitate tests against data that are stronger than those based on static equilibrium patterns. Here I investigate the time-dependent solutions of the classic spatially implicit neutral model, in which a small local community is coupled to a much larger metacommunity through immigration. I present explicit general formulas for the eigenvalues, left eigenvectors and right eigenvectors of the models’s transition matrix. The time-dependent solutions can then be expressed in terms of these eigenvalues and eigenvectors. Some of these results are translated directly from existing results for the classic Moran model of population genetics (the Moran model is equivalent to the spatially implicit neutral model after a reparameterization); others of the results are new. I demonstrate that the asymptotic time-dependent solution corresponding to just these first two eigenvectors can be a good approximation to the full time-dependent solution. I also demonstrate the feasibility of a partial eigendecomposition of the transition matrix, which facilitates direct application of the results to a biologically relevant example in which a newly invading species is initially present in the metacommunity but absent from the local community.     

Two-phase species–time relationships in North American land birds

The species–time relationship (STR) is a macroecological pattern describing the increase in the observed species richness with the length of time censused. Understanding STRs is important for understanding the ecological processes underlying temporal turnover and species richness. However, accurate characterization of the STR has been hampered by the influence of sampling. I analysed STRs for 521 breeding bird survey communities. I used a model of sampling effects to demonstrate that the increase in richness was not due exclusively to sampling. I estimated the time scale at which ecological processes became dominant over sampling effects using a two‐phase model combining a sampling phase and either a power function or logarithmic ecological phase. These two‐phase models performed significantly better than sampling alone and better than simple power and logarithmic functions. Most community dynamics were dominated by ecological processes over scales <5 years. This technique provides an example of a rigorous, quantitative approach to separating sampling from ecological processes.     

基于个体的空间显性模型和遥感技术模拟入侵植物扩张机制

基于个体的空间显性模型和遥感技术,以互花米草为例,模拟了自1997到2010年的种群扩张动态,揭示了土地利用变化与潮间带高程的影响;并通过全局敏感性分析揭示了种子扩散、成体存活率、有性和无性繁殖等种群统计学特征对互花米草种群扩张的相对重要性。研究结果发现:1)有性繁殖与无性繁殖共同决定互花米草种群快速扩张;2)潮间带高程和土地利用变化显著影响模型预测的精度,对互花米草种群扩张有非常重要的影响;3)成体存活率与种子长距离扩散是影响互花米草种群扩张速度最重要的因素;无性繁殖比有性繁殖对种群扩张的影响更大;种子长距离扩散比本地扩散更为重要,同时,小概率的种子长距离扩散事件对种群扩张有非常重要的影响。为了经济有效地控制外来入侵植物的扩张,应该抑制种子的长距离扩散和移除种子长距离扩散形成的位于入侵前沿的小斑块。     

The quest for a null model for macroecological patterns: geometry of species distributions at multiple spatial scales

There have been several attempts to build a unified framework for macroecological patterns. However, these have mostly been based either on questionable assumptions or have had to be parameterized to obtain realistic predictions. Here, we propose a new model explicitly considering patterns of aggregated species distributions on multiple spatial scales, the property which lies behind all spatial macroecological patterns, using the idea we term 'generalized fractals'. Species' spatial distributions were modelled by a random hierarchical process in which the original 'habitat' patches were randomly replaced by sets of smaller patches nested within them, and the statistical properties of modelled species assemblages were compared with macroecological patterns in observed bird data. Without parameterization based on observed patterns, this simple model predicts realistic patterns of species abundance, distribution and diversity, including fractal-like spatial distributions, the frequency distribution of species occupancies/abundances and the species–area relationship. Although observed macroecological patterns may differ in some quantitative properties, our concept of random hierarchical aggregation can be considered as an appropriate null model of fundamental macroecological patterns which can potentially be modified to accommodate ecologically important variables.     

A complex speciation-richness relationship in a simple neutral model

Speciation is the "elephant in the room" of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities. We focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. We use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations.     

Temperature and prey quality effects on growth of juvenile walleye pollock Theragra chalcogramma (Pallas): a spatially explicit bioenergetics approach

A bioenergetics model for juvenile age‐0 year walleye pollock Theragra chalcogramma was applied to a spatially distinct grid of samples in the western Gulf of Alaska to investigate the influence of temperature and prey quality on size‐specific growth. Daily growth estimates for 50, 70 and 90 mm standard length (L_S) walleye pollock during September 2000 were generated using the bioenergetics model with a fixed ration size. Similarities in independent estimates of prey consumption generated from the bioenergetics model and a gastric evacuation model corroborated the performance of the bioenergetics model, concordance correlation (r_c) = 0·945, lower 95% CL (transformed) (L₁) = 0·834, upper 95% CL (transformed) (L₂) = 0·982, P < 0·001. A mean squared error analysis (M_SE) was also used to partition the sources of error between both model estimates of consumption into a mean component (M_C), slope component (S_C), and random component (R_C). Differences between estimates of daily consumption were largely due to differences in the means of estimates (M_C= 0·45) and random sources (R_C= 0·49) of error, and not differences in slopes (S_C= 0·06). Similarly, daily growth estimates of 0·031–0·167 g day^?1 generated from the bioenergetics model was within the range of growth estimates of 0·026–0·190 g day^?1 obtained from otolith analysis of juvenile walleye pollock. Temperature and prey quality alone accounted for 66% of the observed variation between bioenergetics and otolith growth estimates across all sizes of juvenile walleye pollock. These results suggest that the bioenergetics model for juvenile walleye pollock is a useful tool for evaluating the influence of spatially variable habitat conditions on the growth potential of juvenile walleye pollock.     

Biodiversity scales from plots to biomes with a universal species–area curve

Classic theory predicts species richness scales as the quarter-power of area, yet species–area relationships (SAR) vary widely depending on habitat, taxa, and scale range. Because power-law SAR are used to predict species loss under habitat loss, and to scale species richness from plots to biomes, insight into the wide variety of observed SAR and the conditions under which power-law behavior should be observed is needed. Here we derive from the maximum entropy principle, a new procedure for upscaling species richness data from small census plots to larger areas, and test empirically, using multiple data sets, the prediction that up to an overall scale displacement, nested SAR lie along a universal curve, with average abundance per species at each scale determining the local slope of the curve. Power-law behaviour only arises in the limit of increasing average abundance, and in that limit, the slope approaches zero, not ¼. An extrapolation of tree species richness in the Western Ghats to biome scale (60 000 km²) using only census data at plot scale (¼ ha) is presented to illustrate the potential for applications of our theory.     

Global diversity of island floras from a macroecological perspective

Islands harbour a significant portion of all plant species worldwide. Their biota are often characterized by narrow distributions and are particularly susceptible to biological invasions and climate change. To date, the global richness pattern of islands is only poorly documented and factors causing differences in species numbers remain controversial. Here, we present the first global analysis of 488 island and 970 mainland floras. We test the relationship between island characteristics (area, isolation, topography, climate and geology) and species richness using traditional and spatial models. Area is the strongest determinant of island species numbers ( R ² = 0.66) but a weaker predictor for mainlands ( R ² = 0.25). Multivariate analyses reveal that all investigated variables significantly contribute to insular species richness with area being the strongest followed by isolation, temperature and precipitation with about equally strong effects. Elevation and island geology show relatively weak yet significant effects. Together these variables account for 85% of the global variation in species richness.