Altitudinal zonation of Andean cryptogam communities

To test whether cryptogamic plant communities in tropical Andean rain forests are distributed in floristically discrete communities corresponding to altitudinal belts, I subjected the elevational distribution of pteridophytes along two elevational gradients in Bolivia, and of bryophytes and lichens along two transects in Peru and Colombia (data from Gradstein & Frahm, 1987 ; Wolf, 1993 ) to an analysis of deviance. All well‐defined elevational boundaries in floristic composition were related to marked ecological changes: the transition from the steep mountains to the hilly lowland zone coupled with a change in geological substrate at 400 m along the Bolivian Carrasco transect, a strong humidity gradient at 1000 m at the Bolivian Masicurí transect and at 1250–1980 m along the Colombian transect, and the transition from mixed cloud forests to forests dominated by Polylepis or Podocarpus at 3400–3600 m in Carrasco, at 1650–1800 m in Masicurí, and at 3670 m in Colombia. Consequently, floristic elevational belts appear to be well‐defined at strong environmental boundaries and in fairly species‐poor forest communities where the presence or absence of one or a few tree species influences the whole ecosystem while they are ill‐defined in species‐rich communities such as tropical forests at low to mid‐elevations.     

Elevational zonation of afrotropical forest bird communities along a homogeneous forest gradient

Aim This study analyses the distribution and abundance of birds from a forested tropical gradient in order to determine whether elevationally distinct communities are detectable in this habitat. Location An avifaunal census was carried out on a single transect within the tropical forest of the Udzungwa Mountains in the Eastern Arc, Tanzania, covering a range in elevation from 300 to 1850 m. Methods Two complementary data sets on forest birds were analysed, encompassing (1) data derived from standardized 20‐ha spot‐mapping censuses performed at nine elevations over 175‐m intervals from 400 to 1800 m a.s.l., and (2) all observations of birds binned into 32 data points at 50‐m intervals, from 300 to 1850 m a.s.l. The degree of zonation in the avian community along the elevational gradient was examined using the chronological clustering method, an agglomerative hierarchical clustering method that can be carried out with a range of similarity indices. Results The chronological clustering analysis of the data set based on standardized spot‐mapping revealed a clearly defined boundary at c. 1200 m a.s.l., separating lowland from montane communities. Most bird species could be categorized as belonging to one of these two communities. The data set based on all observations revealed a number of potential secondary boundaries, although these boundaries delimited the entire elevational ranges of individual species in only relatively few cases. Main conclusions In contrast to previously published studies, we find evidence of an elevational zonation of distinct communities within a seemingly homogeneous habitat. Although similar boundaries have been assumed to arise as a result of vegetational ecotones, or because of interspecific competition, these mechanisms are poorly corroborated. We suggest that the causes of patterns of zonation are not well understood, and that the interplay among species distributions, species richness, and environmental factors needs more consideration. The chronological clustering method is proposed as an appropriate tool for studying these specific patterns.     

Detecting spatial regimes in ecosystems

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory‐based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.     

Vegetation controls vary across space and spatial scale in a historic grassland‐forest biome boundary

Ecological boundaries are critical landscape regions of transition between adjacent ecological systems. While environmental controls of boundaries may operate in a scale‐dependent manner, multiple‐scale comparisons of vegetation–environment relationships have been characterized for few boundary systems. We used approximately 250 000 point records on the occurrence of woody versus grassland vegetation in conjunction with climatic, topographical, and soils data to evaluate scale effects and spatial heterogeneity in a 650‐km section of the historic prairie–forest biome boundary of Minnesota, USA. We chose this as a model system because of the availability of historical vegetation data, a considerable spatial extent, a sharp ecological transition, and the ability to avoid confounding from more recent anthropogenic land use change. We developed modeling techniques using hierarchical variance partitioning in a spatially‐structured format that allowed us to simultaneously evaluate vegetation–environment relationships across two‐dimensional space (i.e. the prairie‐forest boundary) and across spatial scales (i.e. varying extents). Soils variables displayed the least spatial autocorrelation at shortest lag distances and tended to be the least important predictors of woody vegetation at all spatial extents. Topographical variables displayed greater spatial heterogeneity in regions dominated by forest compared with prairie and were more important at fine‐intermediate spatial scales, highlighting their likely control on fire regimes. An integrated climatic variable (precipitation minus potential evapotranspiration) displayed a trend of increasing spatial variance across the study region and was unambiguously the strongest biome boundary control, although its joint influence with fire was difficult to characterize. Spatially heterogeneous vegetation–environment relationships were observed at all scales, especially at finer scales. Our results suggest that the importance of environmental controls changes smoothly rather than discretely across scales and demonstrate the need to account for spatial non‐stationarity and scale to predict and understand vegetation distribution across ecological boundaries.     

Evaluating the role of biotic interactions in structuring communities using a gradient analysis of multiple interacting guilds

The extent to which ecological communities are coherent entities as opposed to mere intersections of individual species distributions has long been one of the fundamental questions of ecology. Gradient analysis is one commonly used tool for addressing this question; however, all such studies have used organisms from a single taxon or guild. This risks missing important connections due to non‐competitive interactions, which should be more likely to occur between members of different guilds. Such organisms are unlikely to compete for resources and can have complementary niches that promote non‐competitive interactions. We examined the abundances of taxa in four interacting guilds along an elevation gradient in a forest in the southern Appalachian mountains. A causal discovery algorithm was used to investigate the relative frequencies of interguild and intraguild interactions. These were approximately equally common once taxonomic richness was taken into account. We used elements of metacommunity structure analysis to study the extent to which species distributions are non‐independent and tested the hypothesis that combinations of two or more interacting guilds exhibit more coherence than single guilds. In this analysis, all guilds other than collembola were classified as Clementsian or quasi‐Clementsian. (Collembola were classified as random.) When sets of multiple guilds were examined, Clementsian and quasi‐Clementsian structures predominated. We also compared boundary conjunction, measured as Morisita’s index (MI) for these sets of guilds to the weighted average of the guilds’ MI values. Only sets of directly interacting guilds had higher‐than‐baseline boundary conjunction values, and such boundary conjunction values are found in all but one set of directly interacting guilds. Our results highlight the importance of inter‐guild interactions in structuring patterns of cooccurrence. Trophic interactions and plant–fungus symbioses (mutualistic and/or pathogen–host) appear particularly important.     

Towards a density measure for assessments of arid plant populations – examples from the southern Namib Desert

Plant species in arid environments are often widely spaced making population assessments difficult. In order to minimise observer bias we tested two repeatable simple methods during red data assessments in the southern Namib Desert. Both the transect‐based and the quadrat‐based method resulted in over‐estimates of the true population size. However, because of case of application, the transect method warrants further development.     

Analyzing geolocator data for birds that roost in cavities year‐round

The use of light‐level geolocators for monitoring migration has been limited to non‐cavity roosting species because light transitions for cavity‐roosting species are obscured. Using Northern Flickers (Colaptes auratus), nocturnal cavity‐roosting woodpeckers, as a model, I describe a method for analyzing geolocator data that initially adjusts light transitions to account for differences between the time of minimum light threshold and when a bird enters or exits a cavity. Using known locations from the breeding grounds, I assessed the precision of this adjustment method for estimating location by examining the associated error, the repeatability of the length of time individuals roosted in cavities, and by conducting a sensitivity analysis to assess uncertainty. Mean location error decreased from 1417 ± 277 km (SD) to 129 ± 194 km when sunrise and sunset times were adjusted and locations from >25 d were averaged. Sensitivity analysis showed that if an adjusted sunrise or sunset time was “incorrect” by 10 min, the error was 121–137 km from the actual location. This adjustment method significantly improved location estimates at known sites, suggesting that adjusting light transitions based off a calibration is a good initial step for determining location. However, to account for behavioral changes in entrance and emergence times, applying state‐space Kalman filter models can further improve the accuracy of location estimates. The combination of adjusting transitions and applying a state‐space Kalman filter thus allows location estimates to be obtained from cavity‐roosting species using geolocator data.     

乌兰巴托-锡林浩特样带草地植被特征与水热因子的关系

2012年夏季,研究人员对蒙古高原长约1100km的乌兰巴托—锡林浩特草地样带开展考察,获取了46个样地的物种数量、地上生物量等数据;基于全球GHCN(全球历史气象网络)数据集,提取了样带夏季(6—8月)月均温度和降水总量;继而根据自然地理和行政区边界,将草地样带大致分成北部(蒙古国乌兰巴托—蒙古国艾日格)、中部(蒙古国艾日格—中国苏尼特左旗)和南部(中国苏尼特左旗—中国锡林浩特),开展了分析。研究表明:(1)样带夏季平均温度的空间分布形态呈现明显的倒"U"型分布,南北两端温度较低,中部温度较高;夏季降水量在空间上的分布形态则与之相反,呈现南北两端降水量较高,中部降水量较低的正"U"型分布;(2)样带上植物物种数量、地上生物量的空间分布形态均呈现正"U"型分布,即在生态景观类型为典型温性草原的样带南部和北部地区,其生物多样性、地上生物量明显好于呈现为温性荒漠草原、温性荒漠景观的样带中部地区。(3)相关分析体现了大尺度(高原样带尺度)上植被特征与水热环境因子间的关系:植物物种数量、地上生物量与夏季月均温度均呈现负相关,而与夏季降水总量则呈现正相关关系。(4)偏相关分析反映了局地小尺度上植被特征与水热环境因子间的关系:温度和降水要素对于植物物种数量、地上生物量均呈现正相关。     

An application of a mixed-effects location scale model for analysis of Ecological Momentary Assessment (EMA) data

Summary .   For longitudinal data, mixed models include random subject effects to indicate how subjects influence their responses over repeated assessments. The error variance and the variance of the random effects are usually considered to be homogeneous. These variance terms characterize the within-subjects (i.e., error variance) and between-subjects (i.e., random-effects variance) variation in the data. In studies using ecological momentary assessment (EMA), up to 30 or 40 observations are often obtained for each subject, and interest frequently centers around changes in the variances, both within and between subjects. In this article, we focus on an adolescent smoking study using EMA where interest is on characterizing changes in mood variation. We describe how covariates can influence the mood variances, and also extend the standard mixed model by adding a subject-level random effect to the within-subject variance specification. This permits subjects to have influence on the mean, or location, and variability, or (square of the) scale, of their mood responses. Additionally, we allow the location and scale random effects to be correlated. These mixed-effects location scale models have useful applications in many research areas where interest centers on the joint modeling of the mean and variance structure.     

Using geometric and non‐geometric internal evaluators to compare eight vegetation classification methods

Questions: How similar are solutions of eight commonly used vegetation classification methods? Which classification methods are most effective according to classification validity evaluators? How do evaluators with different optimality criteria differ in their assessments of classification efficacy? In particular, do evaluators which use geometric criteria (e.g. cluster compactness) and non‐geometric evaluators (which rely on diagnostic species) offer similar classification evaluations? Methods: We analysed classifications of two vegetation data‐sets produced by eight classification methods. Classification solutions were assessed with five geometric and four non‐geometric internal evaluators. We formally introduce three new evaluators: PARTANA, an intuitive variation on evaluators which use the ratio of within/between cluster dissimilarity as the optimality criterion, an adaptation of Morisita's index of niche overlap, and ISAMIC, an algorithm which measures the degree to which species are either always present or always absent within clusters. Results and Conclusions: 1. With the exception of single linkage hierarchical clustering, classifications resulting from the eight methods were often similar. 2. Although evaluators varied in their assessment of best overall classification method, they generally favored three hierarchical agglomerative clustering strategies: flexible beta (β=– 0.25), average linkage, and Ward's linkage. 3. Among introduced evaluators PARTANA appears to be an effective geometric strategy which provides assessments similar to C‐index and Gamma evaluators. Non‐geometric evaluators ISAMIC and Morisita's index demonstrate a strong bias for single linkage solutions. 4. Because non‐geometric criteria are of interest to phytosociologists there is a strong need for their continued development for use with vegetation classifications.     

On the prevalence and dynamics of inverted trophic pyramids and otherwise top‐heavy communities

Classically, biomass partitioning across trophic levels was thought to add up to a pyramidal distribution. Numerous exceptions have, however, been noted including complete pyramidal inversions. Elevated levels of biomass top‐heaviness (i.e. high consumer/resource biomass ratios) have been reported from Arctic tundra communities to Brazilian phytotelmata, and in species assemblages as diverse as those dominated by sharks and ants. We highlight two major pathways for creating top‐heaviness, via: (1) endogenous channels that enhance energy transfer across trophic boundaries within a community and (2) exogenous pathways that transfer energy into communities from across spatial and temporal boundaries. Consumer–resource models and allometric trophic network models combined with niche models reveal the nature of core mechanisms for promoting top‐heaviness. Outputs from these models suggest that top‐heavy communities can be stable, but they also reveal sources of instability. Humans are both increasing and decreasing top‐heaviness in nature with ecological consequences. Current and future research on the drivers of top‐heaviness can help elucidate fundamental mechanisms that shape the architecture of ecological communities and govern energy flux within and between communities. Questions emerging from the study of top‐heaviness also usefully draw attention to the incompleteness and inconsistency by which ecologists often establish definitional boundaries for communities.     

A remarkable case of mosaic parapatry in millipedes

The parapatric boundary between Tasmaniosoma compitale Mesibov, 2010 and Tasmaniosoma hickmanorum Mesibov, 2010 (Polydesmida: Dalodesmidae) in northwest Tasmania was mapped in preparation for field studies of parapatry and speciation. Both millipede species can be collected as adults throughout the year, are often abundant in eucalypt forest and tolerate major habitat disturbance. The parapatric boundary between the two species is ca 100 m wide in well-sampled sections and ca 230 km long. It runs from sea level to 600-700 m elevation, crosses most of the river catchments in northwest Tasmania and several major geological boundaries, and one portion of the boundary runs along a steep rainfall gradient. The location of the boundary is estimated here from scattered sample points using a method based on Delaunay triangulation.     

Complexity is costly: a meta‐analysis of parametric and non‐parametric methods for short‐term population forecasting

Short‐term forecasts based on time series of counts or survey data are widely used in population biology to provide advice concerning the management, harvest and conservation of natural populations. A common approach to produce these forecasts uses time‐series models, of different types, fit to time series of counts. Similar time‐series models are used in many other disciplines, however relative to the data available in these other disciplines, population data are often unusually short and noisy and models that perform well for data from other disciplines may not be appropriate for population data. In order to study the performance of time‐series forecasting models for natural animal population data, we assembled 2379 time series of vertebrate population indices from actual surveys. Our data were comprised of three vastly different types: highly variable (marine fish productivity), strongly cyclic (adult salmon counts), and small variance but long‐memory (bird and mammal counts). We tested the predictive performance of 49 different forecasting models grouped into three broad classes: autoregressive time‐series models, non‐linear regression‐type models and non‐parametric time‐series models. Low‐dimensional parametric autoregressive models gave the most accurate forecasts across a wide range of taxa; the most accurate model was one that simply treated the most recent observation as the forecast. More complex parametric and non‐parametric models performed worse, except when applied to highly cyclic species. Across taxa, certain life history characteristics were correlated with lower forecast error; specifically, we found that better forecasts were correlated with attributes of slow growing species: large maximum age and size for fishes and high trophic level for birds. Synthesis Evaluating the data support for multiple plausible models has been an integral focus of many ecological analyses. However, the most commonly used tools to quantify support have weighted models’ hindcasting and forecasting abilities. For many applications, predicting the past may be of little interest. Concentrating only on the future predictive performance of time series models, we performed a forecasting competition among many different kinds of statistical models, applying each to many different kinds of vertebrate time series of population abundance. Low‐dimensional (simple) models performed well overall, but more complex models did slightly better when applied to time series of cyclic species (e.g. salmon).     

Abrupt shifts in African savanna tree cover along a climatic gradient

Aim To describe patterns of tree cover in savannas over a climatic gradient and a range of spatial scales and test if there are identifiable climate‐related mean structures, if tree cover always increases with water availability and if there is a continuous trend or a stepwise trend in tree cover. Location Central Tropical Africa. Methods We compared a new analysis of satellite tree cover data with botanical, phytogeographical and environmental data. Results Along the climatic transect, six vegetation structures were distinguished according to their average tree cover, which can co‐occur as mosaics. The resulting abrupt shifts in tree cover were not correlated to any shifts in either environmental variables or in tree species distributions. Main conclusions A strong contrast appears between fine‐scale variability in tree cover and coarse‐scale structural states that are stable over several degrees of latitude. While climate parameters and species pools display a continuous evolution along the climatic gradient, these stable structural states have discontinuous transitions, resulting in regions containing mosaics of alternative stable states. Soils appear to have little effect inside the climatic stable state domains but a strong action on the location of the transitions. This indicates that savannas are patch dynamics systems, prone to feedbacks stabilizing their coarse‐scale structure over wide ranges of environmental conditions.     

Current knowledge on non‐native freshwater fish introductions

This review provides a contemporary account of knowledge on aspects of introductions of non‐native fish species and includes issues associated with introduction pathways, ecological and economic impacts, risk assessments, management options and impact of climate change. It offers guidance to reconcile the increasing demands of certain stakeholders to diversify their activities using non‐native fishes with the long‐term sustainability of native aquatic biodiversity. The rate at which non‐native freshwater fishes have been introduced worldwide has doubled in the space of 30 years, with the principal motives being aquaculture (39%) and improvement of wild stocks (17%). Economic activity is the principal driver of human‐mediated non‐native fish introductions, including the globalization of fish culture, whereby the production of the African cichlid tilapia is seven times higher in Asia than in most areas of Africa, and Chile is responsible for c. 30% of the world's farmed salmon, all based on introduced species. Consequently, these economic benefits need balancing against the detrimental environmental, social and economic effects of introduced non‐native fishes. There are several major ecological effects associated with non‐native fish introductions, including predation, habitat degradation, increased competition for resources, hybridization and disease transmission. Consideration of these aspects in isolation, however, is rarely sufficient to adequately characterize the overall ecological effect of an introduced species. Regarding the management of introduced non‐native fish, pre‐introduction screening tools, such as the fish invasiveness scoring kit (FISK), can be used to ensure that species are not introduced, which may develop invasive populations. Following the introduction of non‐native fish that do develop invasive populations, management responses are typified by either a remediation or a mitigation response, although these are often difficult and expensive to implement, and may have limited effectiveness.     

Ecologists should not use statistical significance tests to interpret simulation model results

Simulation models are widely used to represent the dynamics of ecological systems. A common question with such models is how changes to a parameter value or functional form in the model alter the results. Some authors have chosen to answer that question using frequentist statistical hypothesis tests (e.g. ANOVA). This is inappropriate for two reasons. First, p‐values are determined by statistical power (i.e. replication), which can be arbitrarily high in a simulation context, producing minuscule p‐values regardless of the effect size. Second, the null hypothesis of no difference between treatments (e.g. parameter values) is known a priori to be false, invalidating the premise of the test. Use of p‐values is troublesome (rather than simply irrelevant) because small p‐values lend a false sense of importance to observed differences. We argue that modelers should abandon this practice and focus on evaluating the magnitude of differences between simulations. Synthesis Researchers analyzing field or lab data often test ecological hypotheses using frequentist statistics (t‐tests, ANOVA, etc.) that focus on p‐values. Field and lab data usually have limited sample sizes, and p‐values are valuable for quantifying the probability of making incorrect inferences in that situation. However, modern ecologists increasingly rely on simulation models to address complex questions, and those who were trained in frequentist statistics often apply the hypothesis‐testing approach inappropriately to their simulation results. Our paper explains why p‐values are not informative for interpreting simulation models, and suggests better ways to evaluate the ecological significance of model results.     

Predicting the likely response of data‐poor ecosystems to climate change using space‐for‐time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data‐poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data‐poor ecosystems based on a space‐for‐time substitution, using distant, well‐studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate‐ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains – to investigate ecological response to climate change – allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long‐term predictions will be of significant value to natural resource practitioners attempting to manage data‐poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.     

Stocks and dynamics of SOC in relation to soil redistribution by water and tillage erosion

Soil organic carbon (SOC) displaced by soil erosion is the subject of much current research and the fundamental question, whether accelerated soil erosion is a source or sink of atmospheric CO₂, remains unresolved. A toposequence of terraced fields as well as a long slope was selected from hilly areas of the Sichuan Basin, China to determine effects of soil redistribution rates and processes on SOC stocks and dynamics. Soil samples for the determination of caesium‐137 (¹³⁷Cs), SOC, total N and soil particle size fractions were collected at 5 m intervals along a transect down the two toposequences. ¹³⁷Cs data showed that along the long slope transect soil erosion occurred in upper and middle slope positions and soil deposition appeared in the lower part of the slope. Along the terraced transect, soil was lost over the upper parts of the slopes and deposition occurred towards the downslope boundary on each terrace, resulting in very abrupt changes in soil redistribution over short distances either side of terrace boundaries that run parallel with the contour on the steep slopes. These data reflect a difference in erosion process; along the long slope transect, water erosion is the dominant process, while in the terraced landscape soil distribution is mainly the result of tillage erosion. SOC inventories (mass per unit area) show a similar pattern to the ¹³⁷Cs inventory, with relatively low SOC content in the erosional sites and high SOC content in depositional areas. However, in the terraced field landscape C/N ratios were highest in the depositional areas, while along the long slope transect, C/N ratios were highest in the erosional areas. When the samples are subdivided based on ¹³⁷Cs‐derived erosion and deposition data, it is found that the erosional areas have similar C/N ratios for both toposequences, while the C/N ratios in depositional areas are significantly different from each other. These differences are attributed to the difference in soil erosion processes; tillage erosion is mainly responsible for high‐SOC inventories at depositional positions on terraced fields, whereas water erosion plays a primary role in SOC storage at depositional positions on the long slope. These data support the theory that water erosion may cause a loss of SOC due to selective removal of the most labile fraction of SOC, while on the other hand tillage erosion only transports the soil over short distances with less effect on the total SOC stock.     

Tropical metacommunities along elevational gradients: effects of forest type and other environmental factors

Elevational gradients provide a natural experiment for assessing the extent to which the structure of animal metacommunities is molded by biotic and abiotic characteristics that change gradually, or is molded by aspects of plant community composition and physiognomy that change in a more discrete fashion. We used a metacommunity framework to integrate species‐specific responses to environmental gradients as an approach to detect emergent patterns at the mesoscale in the Luquillo Mountains of Puerto Rico. Elements of metacommunity structure (coherence, species turnover and range boundary clumping) formed the basis for distinguishing among random, checkerboard, Gleasonian, Clementsian, evenly spaced and nested patterns. Paired elevational transects (300–1000 m a.s.l.) were sampled at 50 m intervals to decouple underlying environmental mechanisms: a mixed forest transect reflected changes in abiotic and biotic conditions, including forest type (i.e. tabonuco, palo colorado and elfin forests), whereas another transect reflected changes in environmental conditions but not forest type, as its constituent plots were located within palm forest. Based on distributional data (presence versus absence of species), the mixed forest transect exhibited Clementsian structure, whereas the palm forest transect exhibited quasi‐Gleasonian structure. In contrast, the distribution of modes in species abundance was random with respect to the latent environmental gradient in the mixed forest transect and clumped with respect to the latent environmental gradient in the palm forest transect. Such contrasts suggest that the environmental factors affecting abundance differed in form or type from those affecting distributional boundaries. Variation among elevational strata with respect to the first axis of correspondence from reciprocal averaging was highly correlated with elevation along each transect, even though axis scores were not correlated between mixed forest and palm forest transects. This suggests that the identity of the environmental characteristics, or the form of response by the fauna to those characteristics, differed between the two elevational transects. Despite the proximity of the transects, the patchy configuration of palm forest, and the pervasive distribution of the dominant palm species, the relative importance of abiotic variables and habitat in structuring gastropod metacommunities differed between transects, which is remarkable and attests to the sensitivity of metacommunity structure to environmental variation.