Spatial Distribution and Coexistence Patterns of Caddisfly Larvae (Trichoptera) in a Hungarian Stream

It is well known that stream macroinvertebrates usually show aggregated spatial distributions caused by extrinsic factors and interactions among species and individuals. In the present study, the spatial distribution of caddisfly assemblages and coexistence patterns of larval caddisfly species (Insecta: Trichoptera) were measured in a Hungarian stream reach at three different spatial scales. Caddisfly assemblages showed aggregated, random and regular distributions as measured by the variance‐mean relationship of species richness as sampling area increased from 0.0225 m² to 0.2025 m². The observed coexistence patterns indicated interactions (lower diversity of unique species combinations than expected by chance) among species for aggregated distributions. These interactions among species proved to be positive associations particularly among species belonging to the same functional feeding group. The positive associations and the aggregated distribution of caddisflies supported the hypothesis that microhabitat patches (patchy microhabitat‐macroinvertebrate model) and/or positive biological interactions among species using the same resource (hypothesis of facilitation) have a deterministic effect on the spatial distribution of caddisfly assemblages. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A unified model explains commonness and rarity on coral reefs

Abundance patterns in ecological communities have important implications for biodiversity maintenance and ecosystem functioning. However, ecological theory has been largely unsuccessful at capturing multiple macroecological abundance patterns simultaneously. Here, we propose a parsimonious model that unifies widespread ecological relationships involving local aggregation, species‐abundance distributions, and species associations, and we test this model against the metacommunity structure of reef‐building corals and coral reef fishes across the western and central Pacific. For both corals and fishes, the unified model simultaneously captures extremely well local species‐abundance distributions, interspecific variation in the strength of spatial aggregation, patterns of community similarity, species accumulation, and regional species richness, performing far better than alternative models also examined here and in previous work on coral reefs. Our approach contributes to the development of synthetic theory for large‐scale patterns of community structure in nature, and to addressing ongoing challenges in biodiversity conservation at macroecological scales.     

Metacommunity‐scale biodiversity regulation and the self‐organised emergence of macroecological patterns

There exist a number of key macroecological patterns whose ubiquity suggests that the spatio‐temporal structure of ecological communities is governed by some universal mechanisms. The nature of these mechanisms, however, remains poorly understood. Here, we probe spatio‐temporal patterns in species richness and community composition using a simple metacommunity assembly model. Despite making no a priori assumptions regarding biotic spatial structure or the distribution of biomass across species, model metacommunities self‐organise to reproduce well‐documented patterns including characteristic species abundance distributions, range size distributions and species area relations. Also in agreement with observations, species richness in our model attains an equilibrium despite continuous species turnover. Crucially, it is in the neighbourhood of the equilibrium that we observe the emergence of these key macroecological patterns. Biodiversity equilibria in models occur due to the onset of ecological structural instability, a population‐dynamical mechanism. This strongly suggests a causal link between local community processes and macroecological phenomena.     

The hierarchical continuum concept

Abstract. Two general models have been proposed to explain the structure of the plant community: the community-unit model of Clements and the continuum model of Whittaker and Curtis, the latter based on Gleason's individualistic distribution of species. It is generally assumed that most ecologists now accept the continuum model. Empirical evidence suggests, however, that the continuum in its current form does not fully describe the observed patterns of vegetation along environmental gradients. In this paper, we introduce the hierarchical continuum as a general concept to represent dynamic community structure along regional spatial gradients. The hierarchical continuum is derived from a combination of the individualistic distribution of species, hierarchical assemblage structure, and the core-satellite species hypothesis. The hierarchical continuum concept predicts that the distribution of species across sites in a region will be polymodal, which reflects hierarchical structure, and that the distribution and abundance of species within and between sites will be spatially and temporally dynamic. Regional distribution of plant species in North American tallgrass prairie, southeastern flood-plain hardwood forests, northern upland hardwood forests, and boreal forests were either bimodal or polymodal as predicted by the hierarchical continuum concept. Species in tallgrass prairie were spatially and temporally dynamic with an average turnover of 8–9 species per 50 m² yr¹. In addition, the hierarchical continuum concept predicts the potential for fractal (self-similar) patterns of community structure, and provides a framework for testable hypotheses concerning species distributions along environmental gradients.     

Bio‐energetics underpins the spatial response of North Sea plaice (Pleuronectes platessa L.) and sole (Solea solea L.) to climate change

Climate change is currently one of the main driving forces behind changes in species distributions, and understanding the mechanisms that underpin macroecological patterns is necessary for a more predictive science. Warming sea water temperatures are expected to drive changes in ectothermic marine species ranges due to their thermal tolerance levels. Here, we develop a mechanistic tool to predict size‐ and season‐specific distributions based on the physiology of the species and the temperature and food conditions in the sea. The effects of climate conditions on physiological‐based habitat utilization was then examined for different size‐classes of two commercially important fish species in the North Sea, plaice, Pleuronectes platessa, and sole, Solea solea. The two species provide an attractive comparison as they differ in their physiology (e.g. preferred temperature range). Combining dynamic energy budget (DEB) models with the temperature and food conditions estimated by an ecosystem model (ERSEM), allowed spatial differences in potential growth (as a proxy for habitat quality) to be estimated for 2 years with contrasting temperature and food conditions. The resulting habitat quality maps were in broad agreement with observed ontogenetic and seasonal changes in distribution as well as with the recent changes in distribution which could be attributed to an increase in coastal temperatures. Our physiological‐based model provides a powerful tool to explore the effect of climate change on the spatio‐temporal fish dynamics, predict effects of local or broad‐scale environmental changes and provide a physiological basis for observed changes in species distributions.     

SESAM – a new framework integrating macroecological and species distribution models for predicting spatio‐temporal patterns of species assemblages

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S‐SDM) starts with constituent species to approximate the properties of assemblages. Here, we propose to unify the two approaches in a single ‘spatially explicit species assemblage modelling’ (SESAM) framework. This framework uses relevant designations of initial species source pools for modelling, macroecological variables, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio‐temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.     

A spatially explicit model for tropical tree diversity patterns

A simple two-parameter model resembling the classical voter model is introduced to describe macroecological properties of tropical tree communities. The parameters of the model characterize the speciation- and global-dispersion rates. Monte Carlo type computer simulations are performed on the model, investigating species abundances and the spatial distribution of individuals and species. Simulation results are critically compared with the experimental data obtained from a tree census on a 50 hectare area of the Barro Colorado Island (BCI), Panama. Fitting to only two observable quantities from the BCI data (total species number and the slope of the log-log species-area curve at the maximal area), it is possible to reproduce the full species-area curve, the relative species abundance distribution, and a more realistic spatial distribution of species.     

The influence of spatial resolution on macroecological patterns of range size variation: a case study using parrots (Aves: Psittaciformes) of the world

Aim To assess the extent to which the resolution at which geographical range sizes are measured influences macroecological patterns in this variable. Location Global. Methods Data on the geographical ranges of parrot species were digitized, and a Geographic Information System used to produce nine range size estimates for each species using different degrees of spatial resolution. The inter‐correlation of these estimates was then compared, together with their patterns of covariation with population size, body mass and migratory behaviour (across species and controlling for phylogeny), their pattern of phylogenetic correlation, and the frequency distributions of the different measures. Results Strong correlations exist among all nine range size measures across species, albeit that measures of similar spatial resolution are more strongly correlated. All measures show similar patterns of covariation with population size, body mass and migratory behaviour, and similar patterns of phylogenetic correlation. The skewness of frequency distributions increases towards zero as the resolution of the range size measure declines. Main conclusions The results of macroecological analyses are little affected by the resolution with which geographical range sizes are calculated, at least for the parrots of the world. Previously published studies based on crude measures of range size would be unlikely to have produced markedly different conclusions had they used more refined range size metrics.     

基于零模型的宁夏荒漠草原优势种群点格局分析

植物种群空间分布格局是多种生态过程综合作用的结果。明确植物优势种群个体的空间分布格局与形成机制有助于认识种群生态适应对策与群落多样性维持机制。以宁夏荒漠草原优势种群蒙古冰草、短花针茅、牛枝子和牛心朴子为研究对象,采用完全空间随机零模型分析其种群空间分布格局特征,并通过异质泊松零模型与泊松聚块零模型探讨生境异质性、扩散限制等因子在其空间分布格局形成过程中的作用。结果显示:(1)完全空间随机零模型下,4个物种在<4 m尺度范围内表现为聚集分布,随尺度增大,逐渐过渡到随机分布和均匀分布。(2)在排除生境异质性的异质泊松零模型下,蒙古冰草种群在整个研究尺度上表现为随机分布;牛枝子、短花针茅和牛心朴子种群仅分别在0—0.2、0.1—0.4 m与0—0.2 m尺度范围内发生偏离,表现为均匀分布与聚集分布,其他尺度均为随机分布。(3)在排除扩散限制的泊松聚块零模型下,所研究种群均表现为随机分布。综上,荒漠草原优势种群在小尺度范围内主要表现为聚集分布;生境异质性与扩散限制均是驱动其空间分布格局形成的重要因子,相对而言,小尺度空间范围内扩散限制的作用更为显著。     

Stochastic determinants of assemblage patterns in coral reef fishes: a quantification by means of two models

Synopsis One perspective emphasizing the importance of stochastic processes in determining coral reef fish assemblages implies that there is little organization in species richness, abundance structure, and spatial distribution. We examine the degree to which this perspective is correct by analyzing distribution of fishes on a collection of patch reefs (Discovery Bay, Jamaica). We ask the question whether these patches accumulate species and individuals in a manner consistent with stochastic expectations. To address this question we use two conceptual models, each permitting a different insight. One assumes that fish are distributed stochastically on patches while the other assumes presence of restrictions on fish distribution due to habitat structure. For each conceptual model we use two types of benchmark: we compare observed patterns to those predicted by theoretical models, and we also compare observed patterns to those obtained from a random reallocation of fish individuals to patches. We found that the conceptual model assuming stochastic processes appeared to provide weaker explanation of patterns than the conceptual model that includes restrictions due to habitat structure. Further, and more importantly, we found that (i) the community is shaped by a mixture of stochastic and non-stochastic mechanisms, and (ii) the stochastic assembly processes decrease in importance for species restricted to fewer microhabitat types and sites. Our study therefore indicates that patches do accumulate individuals and species in a manner consistent with stochastic expectations, however, this applies primarily to the habitat generalists (unrestricted species). By the same token, increased habitat specialization by some species imposes constraints on the stochastic model such that it eventually fails.     

The relationship between global and regional distribution diminishes among phylogenetically basal species

Phylogenetic legacy and phylogenetic trends affect the ecology of species-except, apparently, for the width of their distribution. As a result, "macroecological" patterns of species distributions emerge constantly in phylogenetically very distinct species assemblages. The width of the global distribution of species, for instance, constantly correlates positively to the width of their regional distribution. However, such patterns primarily reflect the phylogenetically derived species that dominate most assemblages. Basal species, in contrast, might show different macroecological patterns. We tested the hypothesis that the correlation between global and regional distributions of species diminishes among the phylogenetically basal species. We considered central European higher plants and defined global distribution as the occupancy of global floristic zones, regional distribution as the grid occupancy in Eastern Germany, and phylogenetic position as the rank distance to tree base. We also took into account a number of confounding variables. We found that, across all lineages, the global/regional correlation diminished among basal species. We then reanalyzed 19 lineages separately and always found the same pattern. The pattern reflected both increases in global distributions and decreases in regional distributions among basal species. The results indicate that many basal species face a risk of global or at least regional extinction, but have escaped the downward spiral of mutually reinforcing extinction risks at multiple scales. We suggest that many basal species had much time to expand their global ranges but are presently displaced locally by more derived species. Overall, the study shows that macroecological patterns may not be static and universal, but may undergo macroevolutionary trends. Analyses of macroecological patterns across a phylogeny may thus provide insights into macroevolutionary processes.     

Accounting for spatial autocorrelation in null models of tree species association

A commonly used null model for species association among forest trees is a well‐mixed community (WMC). A WMC represents a non‐spatial, or spatially implicit, model, in which species form nearest‐neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the species’ spatial distributions. Yet, stochastic dispersal processes often lead to spatial autocorrelation (SAC) in tree species densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially‐explicit models, its impact on non‐spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non‐spatial models, we developed a spatially‐heterogeneous (SH) modelling approach that incorporates measured levels of SAC. Using the mapped locations of individuals in a tropical tree community, we tested the hypothesis that the identity of nearest‐neighbors represents a random draw from neighborhood species pools. Correlograms of Moran's I confirmed that, for 50 of 51 dominant species, stem density was significantly autocorrelated over distances ranging from 50 to 200 m. The observed patterns of SAC were consistent with dispersal limitation, with most species occurring in distinct patches. For nearly all of the 106 species in the community, the frequency of pairwise association was statistically indistinguishable from that projected by the null models. However, model comparisons revealed that non‐spatial models more strongly underestimated observed species‐pair frequencies, particularly for conspecific pairs. Overall, the CSR models projected more significant facilitative interactions than did SH models, yielding a more liberal test of niche differences. Our results underscore the importance of accounting for stochastic spatial processes in tests of association, regardless of whether spatial or non‐spatial models are employed.     

Searching for a Needle in a Haystack: Evaluating Survey Methods for Non-indigenous Plant Species

The control and management of non-indigenous plant species (NIS) can be conceptually divided into three phases: inventory/survey, monitoring and management. Here we focus on phase one, determining which species are present and where they are located within the environment. Sampling for NIS is inherently time-consuming and thus costly. Many management areas are large and therefore can only be surveyed (partial observation of the total area by sampling) and not inventoried (total observation of area). Survey data should reflect the spatial distribution of the target species populations over the landscape. Such data can then be used in combination with environmental data, to create probability maps of target species occurrence for the entire area of interest. We used a GIS model to evaluate seven different survey methods for consistency and reliability of intersecting NIS species’ patches and producing samples which reflect the spatial distribution of the population, and which can be performed in a cost and time-efficient manner. The GIS model was developed to create NIS populations which were then sampled using the different survey methods, and the results recorded. To improve the applicability of the model, four patch sizes and levels of occurrence were used, along with random and weighted distribution patterns in relation to patch proximity to roads and trails. Grid and random points, and targeted (stratified continuous) transects (starting on a road or trail (rights of way (RoW)) and finishing 2 km from any RoW) methods provided the most consistent samples of the population. Logistically, point methods required an unrealistic distance and time commitment in comparison with transect methods. The importance of collecting information on the size of NIS patches was demonstrated as more small patches were intersected than larger ones when the area infested was held constant. Thus, if frequency of patches is used to explain the results of a survey then comparisons between species and methods are difficult to interpret thus leading to erroneous conclusions. However, use of percentage of area infested estimates provides for easier comparison between species and sample methods. The targeted transect method provided the most reliable, efficient and consistent sample with the expected spatial distribution.     

Prior knowledge about spatial pattern affects patch assessment rather than movement between patches in tactile-feeding mallard

1. Heterogeneity in food abundance allows a forager to concentrate foraging effort in patches that are rich in food. This might be problematic when food is cryptic, as the content of patches is unknown prior to foraging. In such case knowledge about the spatial pattern in the distribution of food might be beneficial as this enables a forager to estimate the content of surrounding patches. A forager can benefit from this pre-harvest information about the food distribution by regulating time in patches and/or movement between patches. 2. We conducted an experiment with mallard Anas platyrhynchos foraging in environments with random, regular, and clumped spatial configurations of full and empty patches. An assessment model was used to predict the time in patches for different spatial distributions, in which a mallard is predicted to remain in a patch until its potential intake rate drops to the average intake rate that can be achieved in the environment. A movement model was used to predict lengths of interpatch movements for different spatial distributions, in which a mallard is predicted to travel to the patch where it expects the highest intake rate. 3. Consistent with predictions, in the clumped distribution mallard spent less time in an empty patch when the previously visited neighbouring patch had been empty than when it had been full. This effect was not observed for the random distribution. This shows that mallard use pre-harvest information on spatial pattern to improve patch assessment. Patch assessment could not be evaluated for the regular distribution. 4. Movements that started in an empty patch were longer than movements that started in a full patch. Contrary to model predictions this effect was observed for all spatial distributions, rather than for the clumped distribution only. In this experiment mallard did not regulate movement in relation to pattern. 5. An explanation for the result that pre-harvest information on spatial pattern affected patch assessment rather than movement is that mallard move to the nearest patch where the expected intake rate is higher than the critical value, rather than to the patch where the highest intake rate is expected.     

Modeling species distributions by breaking the assumption of self-similarity

Species distributions are commonly measured as the number of sites, or geographic grid cells occupied. These data may then be used to model species distributions and to examine patterns in both intraspecific and interspecific distributions. Harte et al. (1999) used a model based on a bisection rule and assuming self-similarity in species distributions to do so. However, this approach has also been criticized for several reasons. Here we show that the self-similarity in species distributions breaks down according to a power relationship with spatial scales, and we therefore adopt a power-scaling assumption for modeling species occupancy distributions. The outcomes of models based on these two assumptions (self-similar and power-scaling) have not previously been compared. Based on Harte's bisection method and an occupancy probability transition model under these two assumptions (self-similar and power-scaling), we compared the scaling pattern of occupancy (also known as the area-of-occupancy) and the spatial distribution of species. The two assumptions of species distribution lead to a relatively similar interspecific occupancy frequency distribution pattern, although the spatial distribution of individual species and the scaling pattern of occupancy differ significantly. The bimodality in occupancy frequency distributions that is common in species communities, is confirmed to a result for certain mathematical and statistical properties of the probability distribution of occupancy. The results thus demonstrate that the use of the bisection method in combination with a power-scaling assumption is more appropriate for modeling species distributions than the use of a self-similarity assumption, particularly at fine scales.     

Mosses and liverworts show contrasting elevational distribution patterns in an oceanic island (Terceira,Azores): the influence of climate and space

Due to ongoing global changes, it is essential to establish a baseline record from which to determine future shifts in species distributions and community assembly patterns. In this context, we used digitised historical bryophyte distribution data along a 1021?m elevational gradient in Terceira Island (Azores) to determine how bryophyte species distribution varies with elevation and which spatial and climatic drivers contribute to this variation. We used ordinary least squares analysis to test for climatic and spatial data as explanatory variables for bryophyte richness and Mid-Domain Null simulations to assess the influence of spatial constraints on species distributions. Bryophyte richness follows a hump-shaped pattern, with mosses predominating in the first half of the gradient and liverworts in the second half. While moss richness did not correlate to any climatic variables and responded weakly to the presence of forest cover, liverwort presence was related to temperature, rainfall, humidity and the occurrence of native forest areas, suggesting that these plants are more sensitive to changes in their environment and can thus be used as better indicator species for climate change. Despite their inherent biases, our study shows that historically compiled data can be a valuable tool for preliminary assessment of macroecological patterns.     

The significance of geographic range size for spatial diversity patterns in Neotropical palms

We examined the effect of range size in commonly applied macroecological analyses using continental distribution data for all 550 Neotropical palm species (Arecaceae) at varying grain sizes from 0.5° to 5°. First, we evaluated the relative contribution of range-restricted and widespread species on the patterns of species richness and endemism. Second, we analysed the impact of range size on the predictive value of commonly used predictor variables. Species sequences were produced arranging species according to their range size in ascending, descending, and random order. Correlations between the cumulative species richness patterns of these sequences and environmental predictors were performed in order to analyse the effect of range size. Despite the high proportion of rare species, patterns of species richness were found to be dominated by a minority of widespread species (∼20%) which contained 80% of the spatial information. Climatic factors related to energy and water availability and productivity accounted for much of the spatial variation of species richness of widespread species. In contrast, species richness of range-restricted species was to a larger extent determined by topographical complexity. However, this effect was much more difficult to detect due to a dominant influence of widespread species. Although the strength of different environmental predictors changed with spatial scale, the general patterns and trends proved to be relatively stabile at the examined grain sizes. Our results highlight the difficulties to approximate causal explanations for the occurrence of a majority of species and to distinguish between contemporary climatic factors and history.     

Predicting the future of species diversity: macroecological theory, climate change, and direct tests of alternative forecasting methods

Accurate predictions of future shifts in species diversity in response to global change are critical if useful conservation strategies are to be developed. The most widely used prediction method is to model individual species niches from point observations and project these models forward using future climate scenarios. The resulting changes in individual ranges are then summed to predict diversity changes; multiple models can be combined to produce ensemble forecasts. Predictions based on environment-richness regressions are rarer. However, richness regression models, based on macroecological diversity theory, have a long track record of making reliable spatial predictions of diversity patterns. If these empirical theories capture true functional relationships between environment and diversity, then they should make consistent predictions through time as well as space and could complement individual species-based predictions. Here, we use climate change throughout the 20th century to directly test the ability of these different approaches to predict shifts of Canadian butterfly diversity. We found that all approaches performed reasonably well, but the most accurate predictions were made using the single best richness-environment regression model, after accounting for the effects of spatial autocorrelation. Spatially trained regression models based on macroecological theory accurately predict diversity shifts for large species assemblages. Global changes provide pseudo-experimental tests of those macroecological theories that can then generate robust predictions of future conditions.