Trait hierarchies are stronger than trait dissimilarities in structuring spatial co‐occurrence patterns of common tree species in a subtropical forest

1. The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co‐occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co‐occur either due to environmental filtering or due to competitive exclusion of inferior competitors (hereafter hierarchical competition).
2. We used a fully mapped 50‐ha subtropical forest plot in southern China to explore how pairwise spatial associations between saplings and between adult trees were influenced by trait dissimilarity and hierarchy in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering, and hierarchical competition on species co‐occurrence.
3. We found that trait dissimilarity was generally negatively related to interspecific spatial associations for both saplings and adult trees across spatial scales, meaning that species with similar trait values were more likely to co‐occur and thus supporting environmental filtering or hierarchical competition. We further found that trait hierarchy outweighed trait dissimilarity in structuring pairwise spatial associations, suggesting that hierarchical competition played a more important role in structuring our forest community than environmental filtering across life stages.
4. This study employed a novel method, by offering the integration of pairwise spatial association and trait dissimilarity as well as trait hierarchy, to disentangle the relative importance of multiple assembly mechanisms in structuring co‐occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co‐occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.

     

Spatial hierarchical approach in community ecology: a way beyond high context-dependency and low predictability in local phenomena

Patterns and functioning of communities, which are determined by a set of processes operating at a large variety of spatial and temporal scales, exhibit quite high context-dependency and low predictability at the fine spatial scales at which recent studies have concentrated. More attention to broader scale and across-scale phenomena may be useful to search for general patterns and rules in communities. In this context, it is effective to incorporate hierarchical spatial scale explicitly into the experimental and sampling design of field studies, an approach referred to here as the spatial hierarchical approach, focusing on a particular assemblage in which biological interaction and species life history are well known. The spatial hierarchical approach can provide insight into the effects of scale in operating processes and answers to a number of important questions in community ecology such as: (1) detection of patterns and processes in spatiotemporal variability in communities, including how to explain the partitioning of pattern information of species diversity at a broad scale into finer scales, and the pattern of spatial variability of community properties at the finest spatial scale; (2) evaluation of changes in patterns observed in macroecology at finer scales; (3) testing of models explaining the coexistence of competing species; and (4) detection of latitudinal patterns in spatiotemporal variability in communities and their causal processes.     

宏观生态学研究的特点与方法

宏观生态学是研究生态系统以上层次的生态学,研究对象为大尺度复杂系统,研究内容和方法都具有不同于传统生态学的明显特点。重视对空间异质性的研究,重视人类的生态作用,注意运用等级结构理论,其研究结果常常是非实验性和非稳定性的。遥感和地理信息系统是空间数据采集和管理、分析的主要手段,景观分析和景观模型是宏观生态研究的重要方法,定位观测试验的网络研究则是实现宏观整体研究的必由之路。     

The problem and promise of scale in multilayer animal social networks

Scale remains a foundational concept in ecology.Spatial scale,for instance,has become a central consideration in the way we understand landscape ecology and animal space use.Meanwhile,scale-dependent social processes can range from fine scale interactions to co-occurrence and overlapping home ranges.Furthermore,sociality can vary within and across seasons.Multilayer networks promise the explicit integration of the social,spatial,and temporal contexts.Given the complex interplay of sociality and animal space use in heterogeneous landscapes,there remains an important gap in our understanding of the influence of scale on animal social networks.Using an empirical case study,we discuss ways of considering social,spatial,and temporal scale in the context of multilayer caribou social networks.Effective integration of social and spatial processes,including biologically meaningful scales,within the context of animal social networks is an emerging area of research.We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.     

Scale‐dependent spatial patterns in benthic communities around a tropical island seascape

Understanding and predicting patterns of spatial organization across ecological communities is central to the field of landscape ecology, and a similar line of inquiry has begun to evolve sub‐tidally among seascape ecologists. Much of our current understanding of the processes driving marine community patterns, particularly in the tropics, has come from small‐scale, spatially‐discrete data that are often not representative of the broader seascape. Here we expand the spatial extent of seascape ecology studies and combine spatially‐expansive in situ digital imagery, oceanographic measurements, spatial statistics, and predictive modeling to test whether predictable patterns emerge between coral reef benthic competitors across scales in response to intra‐island gradients in physical drivers. We do this around the entire circumference of a remote, uninhabited island in the central Pacific (Jarvis Island) that lacks the confounding effects of direct human impacts. We show, for the first time, that competing benthic groups demonstrate predictable scaling patterns of organization, with positive autocorrelation in the cover of each group at scales < ~1 km. Moreover, we show how gradients in subsurface temperature and surface wave power drive spatially‐abrupt transition points in group dominance, explaining 48–84% of the overall variation in benthic cover around the island. Along the western coast, we documented ten times more sub‐surface cooling‐hours than any other part of the coastline, with events typically resulting in a drop of 1–4°C over a period of < 5 h. These high frequency temperature fluctuations are indicative of upwelling induced by internal waves and here result in localized nitrogen enrichment (NO₂ + NO₃) that promotes hard coral dominance around 44% of the island's perimeter. Our findings show that, in the absence of confounding direct human impacts, the spatial organization of coral reef benthic competitors are predictable and somewhat bounded across the seascape by concurrent gradients in physical drivers.     

The Influence of Climate, Soils, Weather, and Land Use on Primary Production and Biomass Seasonality in the US Great Plains

Identifying the conditions and mechanisms that control ecosystem processes, such as net primary production, is a central goal of ecosystem ecology. Ideas have ranged from single limiting-resource theories to colimitation by nutrients and climate, to simulation models with edaphic, climatic, and competitive controls. Although some investigators have begun to consider the influence of land-use practices, especially cropping, few studies have quantified the impact of cropping at large scales relative to other known controls over ecosystem processes. We used a 9-year record of productivity, biomass seasonality, climate, weather, soil conditions, and cropping in the US Great Plains to quantify the controls over spatial and temporal patterns of net primary production and to estimate sensitivity to specific driving variables. We considered climate, soil conditions, and long-term average cropping as controls over spatial patterns, while weather and interannual cropping variations were used as controls over temporal variability. We found that variation in primary production is primarily spatial, whereas variation in seasonality is more evenly split between spatial and temporal components. Our statistical (multiple linear regression) models explained more of the variation in the amount of primary production than in its seasonality, and more of the spatial than the temporal patterns. Our results indicate that although climate is the most important variable for explaining spatial patterns, cropping explains a substantial amount of the residual variability. Soil texture and depth contributed very little to our models of spatial variability. Weather and cropping deviation both made modest contributions to the models of temporal variability. These results suggest that the controls over seasonality and temporal variation are not well understood. Our sensitivity analysis indicates that production is more sensitive to climate than to weather and that it is very sensitive to cropping intensity. In addition to identifying potential gaps in out knowledge, these results provide insight into the probable long- and short-term ecosystem response to changes in climate, weather, and cropping.     

Pattern formation in a spatial plant-wrack model with tide effect on the wrack

Spatial patterns are a subfield of spatial ecology, and these patterns modify the temporal dynamics and stability properties of population densities at a range of spatial scales. Localized ecological interactions can generate striking large-scale spatial patterns in ecosystems through spatial self-organization. Possible mechanisms include oscillating consumer–resource interactions, localized disturbance–recovery processes, and scale-dependent feedback. However, in this paper, our main aim is to study the effect of tide on the pattern formation of a spatial plant-wrack model. We discuss the changes of the wavelength, wave speed, and the conditions of the spatial pattern formation, according to the dispersion relation formula. Both the mathematical analysis and numerical simulations reveal that the tide has great influence on the spatial pattern. More specifically, typical traveling spatial patterns can be obtained. Our obtained results are consistent with the previous observation that wracks exhibit traveling patterns, which is useful to help us better understand the dynamics of the real ecosystems.     

Local climate mediates spatial and temporal variation in carabid beetle communities in three forests in Mount Odaesan,Korea

1. Global environmental change can dramatically alter the composition of floral and faunal communities, and elucidating the mechanisms underlying this process is important for predicting its outcomes. Studies on global climate change have mostly focused on statistical summaries within wide spatial and temporal scales; less attention has been paid to variability in microclimates at narrower spatial and temporal scales. 2. The microclimate is the suite of climatic conditions measured in a local area. Environmental variables at the microclimatic scale can be critical for the ecology of organisms inhabiting each area. The effect of spatial and temporal changes in the microclimate on the ecology of carabid beetle communities in three sites on Mount Odaesan, Korea was examined. 3. Carabid beetle communities and quantified site‐specific environmental factors from measurements of air temperature, air humidity, light intensity and soil temperature over 5 years (2010–2015) were surveyed. 4. It was found that microclimatic variables and the patterns of temporal changes in carabid beetle communities differed between the three sites within the single mountain system. Microclimatic variables influencing temporal changes in beetle communities also differed between the sites. Therefore, it is suggested that variation in local microclimates affects spatial and temporal variation in carabid beetle communities at a local scale. 5. The present results demonstrate the importance of regular surveys of communities at local scales. Such surveys are expected to reveal an additional fraction of variation in communities and underlying processes that have been overlooked in studies of global community patterns and change.     

Developing a flexible learning activity on biodiversity and spatial scale concepts using open‐access vegetation datasets from the National Ecological Observatory Network

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.     

Quantitative approaches in climate change ecology

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer‐reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non‐climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.     

Environmental filtering by pH and soil nutrients drives community assembly in fungi at fine spatial scales

Whether niche processes, like environmental filtering, or neutral processes, like dispersal limitation, are the primary forces driving community assembly is a central question in ecology. Here, we use a natural experimental system of isolated tree “islands” to test whether environment or geography primarily structures fungal community composition at fine spatial scales. This system consists of isolated pairs of two distantly related, congeneric pine trees established at varying distances from each other and the forest edge, allowing us to disentangle the effects of geographic distance vs. host and edaphic environment on associated fungal communities. We identified fungal community composition with Illumina sequencing of ITS amplicons, measured all relevant environmental parameters for each tree—including tree age, size and soil chemistry—and calculated geographic distances from each tree to all others and to the nearest forest edge. We applied generalized dissimilarity modelling to test whether total and ectomycorrhizal fungal (EMF) communities were primarily structured by geographic or environmental filtering. Our results provide strong evidence that as in many other organisms, niche and neutral processes both contribute significantly to turnover in community composition in fungi, but environmental filtering plays the dominant role in structuring both free‐living and symbiotic fungal communities at fine spatial scales. In our study system, we found pH and organic matter primarily drive environmental filtering in total soil fungal communities and that pH and cation exchange capacity—and, surprisingly, not host species—were the largest factors affecting EMF community composition. These findings support an emerging paradigm that pH may play a central role in the assembly of all soil‐mediated systems.     

Local and Regional Effects on Community Structure of Dung Beetles in a Mainland-Island Scenario

Understanding the ecological mechanisms driving beta diversity is a major goal of community ecology. Metacommunity theory brings new ways of thinking about the structure of local communities, including processes occurring at different spatial scales. In addition to new theories, new methods have been developed which allow the partitioning of individual and shared contributions of environmental and spatial effects, as well as identification of species and sites that have importance in the generation of beta diversity along ecological gradients. We analyzed the spatial distribution of dung beetle communities in areas of Atlantic Forest in a mainland-island scenario in southern Brazil, with the objective of identifying the mechanisms driving composition, abundance and biomass at three spatial scales (mainland-island, areas and sites). We sampled 20 sites across four large areas, two on the mainland and two on the island. The distribution of our sampling sites was hierarchical and areas are isolated. We used standardized protocols to assess environmental heterogeneity and sample dung beetles. We used spatial eigenfunctions analysis to generate the spatial patterns of sampling points. Environmental heterogeneity showed strong variation among sites and a mild increase with increasing spatial scale. The analysis of diversity partitioning showed an increase in beta diversity with increasing spatial scale. Variation partitioning based on environmental and spatial variables suggests that environmental heterogeneity is the most important driver of beta diversity at the local scale. The spatial effects were significant only at larger spatial scales. Our study presents a case where environmental heterogeneity seems to be the main factor structuring communities at smaller scales, while spatial effects are more important at larger scales. The increase in beta diversity that occurs at larger scales seems to be the result of limitation in species dispersal ability due to habitat fragmentation and the presence of geographical barriers.     

Using historical ecology to understand patterns of biodiversity in fragmented agricultural landscapes

Aim To enhance current attempts to understand biodiversity patterns by using an historical ecology approach to highlight the over‐riding influence of land‐use history in creating past, current and future patterns of biodiversity in fragmented agricultural landscapes. Methods We develop an integrative conceptual framework for understanding spatial and temporal variations in landscape patterns in fragmented agricultural landscapes by presenting five postulates (hypotheses) which highlight the important role of historical, anthropogenic disturbance regimes. We then illustrate each of these postulates with examples drawn from fragmented woodlands in agricultural areas of south‐eastern Australia, and discuss these findings in an international context. Location examples are drawn from agricultural areas in south‐eastern Australia. Results We conclude that there is limited potential to refine our understanding of patterns of biodiversity in human‐modified landscapes based on traditional concepts of island biogeography, or simple assumptions of ongoing destruction and degradation. Instead, we propose that in agricultural landscapes that were largely cleared over a century ago: (1) present‐day remnant vegetation patterns are not accidental, but are logically arrayed due to historic land‐use decisions, (2) historic anthropogenic disturbances have a major influence on current ecosystem conditions and diversity patterns, and (3) the condition of remnant ecosystems is not necessarily deteriorating rapidly. Main conclusions An historical ecology approach can enhance our understanding of why different species and ecosystem states occur where they do, and can explain internal variations in ecological conditions within remnant ecosystems, too often casually attributed to the ‘mess of history’. This framework emphasizes temporal changes (both past and future) in biotic patterns and processes in fragmented agricultural landscapes. Integration of spatially and temporally explicit historical land‐use information into ecological studies can prove extremely useful to test hypotheses of the effects of changes in landscape processes, and to enhance future research, restoration and conservation management activities.     

Isolation by resistance across a complex coral reef seascape

A detailed understanding of the genetic structure of populations and an accurate interpretation of processes driving contemporary patterns of gene flow are fundamental to successful spatial conservation management. The field of seascape genetics seeks to incorporate environmental variables and processes into analyses of population genetic data to improve our understanding of forces driving genetic divergence in the marine environment. Information about barriers to gene flow (such as ocean currents) is used to define a resistance surface to predict the spatial genetic structure of populations and explain deviations from the widely applied isolation-by-distance model. The majority of seascape approaches to date have been applied to linear coastal systems or at large spatial scales (more than 250 km), with very few applied to complex systems at regional spatial scales (less than 100 km). Here, we apply a seascape genetics approach to a peripheral population of the broadcast-spawning coral Acropora spicifera across the Houtman Abrolhos Islands, a high-latitude complex coral reef system off the central coast of Western Australia. We coupled population genetic data from a panel of microsatellite DNA markers with a biophysical dispersal model to test whether oceanographic processes could explain patterns of genetic divergence. We identified significant variation in allele frequencies over distances of less than 10 km, with significant differentiation occurring between adjacent sites but not between the most geographically distant ones. Recruitment probabilities between sites based on simulated larval dispersal were projected into a measure of resistance to connectivity that was significantly correlated with patterns of genetic divergence, demonstrating that patterns of spatial genetic structure are a function of restrictions to gene flow imposed by oceanographic currents. This study advances our understanding of the role of larval dispersal on the fine-scale genetic structure of coral populations across a complex island system and applies a methodological framework that can be tailored to suit a variety of marine organisms with a range of life-history characteristics.     

The possible combined effects of land-use changes and climate conditions on the spatial–temporal patterns of primary production in a natural protected area

Multifunctional landscapes are characterized by various functions and values that sustain directly or indirectly the quality of human life, through the provision of natural capital flow. Primary production (PP), representing a measure of the solar energy captured by the system and available to drive its functioning, is recognized as a fundamental supporting service. Several biophysical modification and conversion altering the primary production are due to land-use change. Natural protected areas with a sustainable management of land-use could be able to guarantee the persistence of structure and processes (primary production) fundamental for the provision of natural capital. In this context, the aims of this paper are to investigate the spatial–temporal patterns of PP variability (1986–2010) in the Natural Protected Area of “Torre Guaceto” (southern Italy), taking into account land-cover change and climate conditions and looking at PP as a supporting service able to guarantee natural capital flow. In dealing with this issue, this paper aims at testing whether NDVI (Normalized Difference Vegetation Index) integrated with NDII (Normalized Difference Infrared Index) can be suitable surrogates for the assessment of shifts in the spatial–temporal dynamics of PP, useful to explore possible feedbacks related to conservation management choices in supporting natural capital flow. Therefore, the assessment of the complex spatial–temporal dynamics of natural vegetation has been performed by using NDVI and NDII. The results showed that after the establishment of the Natural Protected Area of “Torre Guaceto” in 2000, there has been an increase of NDVI that could represent an increase of PP. However, since PP depends also on water content, measured by NDII, a Pearson correlation analysis between NDII and land Surface Temperature (TS) has been carried out, demonstrating that low level of PP in 2005 was not imputable to climate conditions but to the worse quality of vegetation associated to the wetland due to aging phenomenon. In conclusion, to make the conservation management more effective it is not enough to identify and quantify the major landscape transformations and the underlying causes, but rather to detect the capability of new landscape patterns, in terms of configuration and composition, to sustain ecosystem services. The analysis of conservation management based on NDVI and NDII, used as surrogate to detect the maintenance of PP, appears to be very promising in order to develop better strategies for the adaptive management of natural protected areas.     

The Challenge to Restore Processes in Face of Nonlinear Dynamics—On the Crucial Role of Disturbance Regimes

Increasingly, restoration ecologists and managers are challenged to restore ecological processes that lead to self‐sustaining ecosystem dynamics. Due to changing environmental conditions, however, restoration goals need to include novel regimes beyond prior reference conditions or reference dynamics. In face of these fundamental challenges in process‐based restoration ecology, disturbance ecology can offer useful insights. Here, I discuss the contribution of disturbance ecology to understanding assembly rules, ecosystem dynamics, regime shifts, and nonlinear dynamics. Using the patch and multipatch concept, all insights are organized according to two spatial and two temporal categories: “patch–event,”“patch–multievent,”“multipatch–event,” and “multipatch–multievent.” This concept implies the consideration of both spatial patterns and temporal rhythms inside and outside of a restoration site. Emerging issues, such as uncoupling of internal and external dynamics, are considered.     

Geographical and Temporal Body Size Variation in a Reptile: Roles of Sex,Ecology, Phylogeny and Ecology Structured in Phylogeny

Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann''s cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.