Community Ecology Research Research Articles

Spot size, distance and emissivity errors in field applications of infrared thermography

Abstract Infrared thermography is increasingly emerging as an analytical approach within the thermal ecology research community, providing unique and rapid temperature information crucial to understanding how plants and animals exchange heat with their environment. What is difficult to appreciate are the numerous ways in which thermography may still yield inaccurate (i.e. deviation from the ‘correct’ value) information if certain tenets are not followed. In this paper, we examine, demonstrate and discuss these tenets with an aim to provide methodological advice to ecologists interested in employing thermography. We found that spot size and distance strongly influenced the surface temperature estimates of known, calibrated temperature sources, with similar results observed in maximum eye temperature measurements in wild birds. We also report on how the angle of incidence affects the apparent emissivity of various biological surfaces (fur, feather, skin, leaves), another source of uncertainty in thermography. The variation in temperature caused by variation in distance and uncertainty in emissivity are large enough to raise flags for field applications of thermography where accuracy is necessary but control over study subjects is limited. Since accurate emissivity and distance parameters are crucial to thermography calculations, our results should serve as a framework to assist ecologists in better experimental design with respect to the use of thermography.

Niche analysis of dominant species in alpine desert grassland communities in Qaidam Basin

Community dominant plants and their ecological niche research is the focus of community ecology research. To explore the niche characteristics of desert dominant plants and the relationship between them and soil factors in Qaidam Basin, and to provide a basis for the construction of desert plant communities and the sustainable management of natural resources in Qaidam Basin. Taking 13 desert plant communities in Qaidam Basin, Qinghai Province as the research objects, this paper analyzed the characteristics of desert plant communities and dominant species based on soil physical and chemical properties, and calculated the niche width and niche overlap of dominant plants. The dominant plants are, Haloxylon ammodendron, Tamarix chinensis, Achnatherum splendens, Poacynum hendersonii, Reaumuria songonica, Phragmites australiss, Sympegma regelii, and Ajania Tenuifolia, Artemisia sphaerocephala, Ceratoides latens, Pearl russianthistle, Scirpustriquter. There were different degree of niche overlap among species in the community. In addition, CCA sequencing showed that different species had different requirements on the environment, and the distribution of dominant species was mainly affected by soil total nitrogen and soil organic matter.

Microeco: an R package for data mining in microbial community ecology.

A large amount of sequencing data is produced in microbial community ecology studies using the high-throughput sequencing technique, especially amplicon-sequencing-based community data. After conducting the initial bioinformatic analysis of amplicon sequencing data, performing the subsequent statistics and data mining based on the operational taxonomic unit and taxonomic assignment tables is still complicated and time-consuming. To address this problem, we present an integrated R package-'microeco' as an analysis pipeline for treating microbial community and environmental data. This package was developed based on the R6 class system and combines a series of commonly used and advanced approaches in microbial community ecology research. The package includes classes for data preprocessing, taxa abundance plotting, venn diagram, alpha diversity analysis, beta diversity analysis, differential abundance test and indicator taxon analysis, environmental data analysis, null model analysis, network analysis and functional analysis. Each class is designed to provide a set of approaches that can be easily accessible to users. Compared with other R packages in the microbial ecology field, the microeco package is fast, flexible and modularized to use and provides powerful and convenient tools for researchers. The microeco package can be installed from CRAN (The Comprehensive R Archive Network) or github (https://github.com/ChiLiubio/microeco).

Mixed-species groups of Serengeti grazers: a test of the stress gradient hypothesis.

Understanding the role of species interactions within communities is a central focus of ecology. A key challenge is to understand variation in species interactions along environmental gradients. The stress gradient hypothesis posits that positive interactions increase and competitive interactions decrease with increasing consumer pressure or environmental stress. This hypothesis has received extensive attention in plant community ecology, but only a handful of tests in animals. Furthermore, few empirical studies have examined multiple co‐occurring stressors. Here we test predictions of the stress gradient hypothesis using the occurrence of mixed‐species groups in six common grazing ungulate species within the Serengeti‐Mara ecosystem. We use mixed‐species groups as a proxy for potential positive interactions because they may enhance protection from predators or increase access to high‐quality forage. Alternatively, competition for resources may limit the formation of mixed‐species groups. Using more than 115,000 camera trap observations collected over 5 yr, we found that mixed‐species groups were more likely to occur in risky areas (i.e., areas closer to lion vantage points and in woodland habitat where lions hunt preferentially) and during time periods when resource levels were high. These results are consistent with the interpretation that stress from high predation risk may contribute to the formation of mixed‐species groups, but that competition for resources may prevent their formation when food availability is low. Our results are consistent with support for the stress gradient hypothesis in animals along a consumer pressure gradient while identifying the potential influence of a co‐occurring stressor, thus providing a link between research in plant community ecology on the stress gradient hypothesis, and research in animal ecology on trade‐offs between foraging and risk in landscapes of fear.

Functional diversity metrics using kernel density n‐dimensional hypervolumes

Abstract The use of n‐dimensional hypervolumes in trait‐based ecology is rapidly increasing. By representing the functional space of a species or community as a Hutchinsonian niche, the abstract Euclidean space defined by a set of independent axes corresponding to individuals or species traits, these multidimensional techniques show great potential for the advance of functional ecology theory. In the panorama of existing methods for delineating multidimensional spaces, the r package hypervolume (Global Ecology and Biogeography, 23, 2014, 595–609) is currently the most used. However, functions for calculating the standard set of functional diversity (FD) indices—richness, divergence and regularity—have not been developed within the hypervolume framework yet. This gap is delaying its full exploitation in functional ecology, meanwhile preventing the possibility to compare its performance with that of other methods. We develop a set of functions to calculate FD indices based on n‐dimensional hypervolumes, including alpha (richness), beta (and respective components), dispersion, evenness, contribution and originality. Altogether, these indices provide a coherent framework to explore the primary mathematical components of FD within a multidimensional setting. These new functions can work either with hypervolume objects or with raw data (species presence or abundance and their traits) as input data, and are versatile in terms of input parameters and options. These functions are implemented within bat (Biodiversity Assessment Tools), an r package for biodiversity assessments. As a coherent corpus of functional indices based on a common algorithm, it opens the possibility to fully explore the strengths of the Hutchinsonian niche concept in community ecology research.

Seasonal changes in metacommunity assembly mechanisms of benthic macroinvertebrates in a subtropical river basin

Unraveling the ecological factors that control variation in local community structure in space and time is fundamental to metacommunity ecology. In this scenario, environmental filtering and spatial processes are recognized as important drivers of community assembly, yet their relative importance is anticipated to vary for biological communities in different seasons, network positions and organisms with distinct dispersal modes. In this study, we used a dataset (macroinvertebrate communities and environmental variables) collected in different seasons from the Ganjiang River in China to test the above ideas. We divided the whole metacommunity in each season into mainstream communities, tributary communities, strictly aquatic dispersers and aquatic/aerial dispersers, and subsequently used variation partitioning to examine the relative contribution of environmental and spatial factors separately for the overall and decomposed components of the metacommunity. Our results showed that both environmental filtering and spatial processes were important drivers of variation in community structure, yet their explanatory powers varied considerably among seasons. Environmental filtering was the primary driver of metacommunity organization in most scenarios, while the effects of spatial processes surpassing environmental filtering occurred only sporadically. For communities in different network positions, tributary communities were structured by both strong environmental filtering and profound effects of spatial processes via dispersal limitation. However, communities in mainstream sites were mainly determined by environmental filtering, and the effects of spatial processes were almost negligible. Moreover, environmental filtering was clearly more important for aquatic/aerial dispersers, while spatial processes were more influential for strictly aquatic dispersers. We thus concluded that environmental filtering, spatial processes, network position and dispersal mode can interact to regulate metacommunity organization of riverine macroinvertebrates. Considering that the relative contribution of these factors varied among seasons, we strongly uphold the idea that community ecology research should go beyond one-season snapshot surveys in river networks.

A Primer for Microbiome Time-Series Analysis.

Time-series can provide critical insights into the structure and function of microbial communities. The analysis of temporal data warrants statistical considerations, distinct from comparative microbiome studies, to address ecological questions. This primer identifies unique challenges and approaches for analyzing microbiome time-series. In doing so, we focus on (1) identifying compositionally similar samples, (2) inferring putative interactions among populations, and (3) detecting periodic signals. We connect theory, code and data via a series of hands-on modules with a motivating biological question centered on marine microbial ecology. The topics of the modules include characterizing shifts in community structure and activity, identifying expression levels with a diel periodic signal, and identifying putative interactions within a complex community. Modules are presented as self-contained, open-access, interactive tutorials in R and Matlab. Throughout, we highlight statistical considerations for dealing with autocorrelated and compositional data, with an eye to improving the robustness of inferences from microbiome time-series. In doing so, we hope that this primer helps to broaden the use of time-series analytic methods within the microbial ecology research community.

Characterizing over Four Decades of Forest Disturbance in Minnesota, USA

Spatial information about disturbance driven patterns of forest structure and ages across landscapes provide a valuable resource for all land management efforts including cross-ownership collaborative forest treatments and restoration. While disturbance events in general are known to impact stand characteristics, the agent of change may also influence recovery and the supply of ecosystem services. Our study utilizes the full extent of the Landsat archive to identify the timing, extent, magnitude, and agent, of the most recent fast disturbance event for all forested lands within Minnesota, USA. To account for the differences in the Landsat sensors through time, specifically the coarser spatial, spectral, and radiometric resolutions of the early MSS sensors, we employed a two-step approach, first harmonizing spectral indices across the Landsat sensors, then applying a segmentation algorithm to fit temporal trends to the time series to identify abrupt forest disturbance events. We further incorporated spectral, topographic, and land protection information in our classification of the agent of change for all disturbance patches. After allowing two years for the time series to stabilize, we were able to identify the most recent fast disturbance events across Minnesota from 1974–2018 with a change versus no-change validation accuracy of 97.2% ± 1.9%, and higher omission (14.9% ± 9.3%) than commission errors (1.6% ± 1.9%) for the identification of change patches. Our classification of the agent of change exhibited an overall accuracy of 96.5% ± 1.9% with classes including non-disturbed forest, land conversion, fire, flooding, harvest, wind/weather, and other rare natural events. Individual class errors varied, but all class user and producer accuracies were above 78%. The unmatched nature of the Landsat archive for providing comparable forest attribute and change information across more than four decades highlights the value of the totality of the Landsat program to the larger geospatial, ecological research, and forest management communities.

A global database for metacommunity ecology, integrating species, traits, environment and space

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.

Taxonomic nestedness based on guilds? Bird assemblages of the Jardines de la Reina National Park, Cuba, as study case

Nestedness is a widely known structuring model in insular and fragmented biotas that has often been assessed, but most studies to date have used a taxonomic approach. However, the relevance of an approach using functional groups has become increasingly highlighted in community ecology research. In this study, we evaluated the occurrence of nested structure in the Jardines de la Reina National Park bird assemblages as a whole, and its trophic guilds by following three different grouping criteria. We constructed species presence–absence matrices for each guild and estimated the degree of nestedness with the metric based on the overlap and decreasing fill, assessing its significance by means of two null models. Overall bird assemblage was significantly nested (NODF = 76.99; p = 0.01) whereas terrestrial insectivores (NODF = 81.32) and insectivores (NODF = 80.04) were the only trophic guilds (out of 19) that showed significant nestedness (p ≤ 0.01). These results could provide evidence of the structural and functional cohesion of avifauna at the study site, especially among its insect–eating taxa. Taxonomic nestedness based on a guilds approach may help identify suitable conservation strategies for avian communities inhabiting naturally fragmented areas such as the Jardines de la Reina National Park.

Thirty years of the Journal of Vegetation Science

Thirty years of the Journal of Vegetation Science

Towards an ecological trait‐data standard

Abstract Trait‐based approaches are widespread throughout ecological research as they offer great potential to achieve a general understanding of a wide range of ecological and evolutionary mechanisms. Accordingly, a wealth of trait data is available for many organism groups, but this data is underexploited due to a lack of standardization and heterogeneity in data formats and definitions. We review current initiatives and structures developed for standardizing trait data and discuss the importance of standardization for trait data hosted in distributed open‐access repositories. In order to facilitate the standardization and harmonization of distributed trait datasets by data providers and data users, we propose a standardized vocabulary that can be used for storing and sharing ecological trait data. We discuss potential incentives and challenges for the wide adoption of such a standard by data providers. The use of a standard vocabulary allows for trait datasets from heterogeneous sources to be aggregated more easily into compilations and facilitates the creation of interfaces between software tools for trait‐data handling and analysis. By aiding decentralized trait‐data standardization, our vocabulary may ease data integration and use of trait data for a broader ecological research community and enable global syntheses across a wide range of taxa and ecosystems.

Achieving FAIR Data Principles at the Environmental Data Initiative, the US-LTER Data Repository

The Environmental Data Initiative (EDI) is a continuation and expansion of the original United Stated Long-Term Ecological Research Program (US-LTER) data repository which went into production in 2013. Building on decades of data management experience in LTER, EDI is addressing the challenge of publishing a diverse corpus of research data (Servilla et al. 2016). EDI’s accomplishments span all aspects of the data curation and publication lifecycle, including repository cyberinfrastructure, outreach and training, and enhancements to data documentation methodologies used by the environmental and ecological research communities. EDI is managing almost 43,000 unique data packages and their revisions from a community of nearly 2,300 individual data authors, most of which are contributed by LTER sites, and are openly accessible and documented with rich science metadata in the Ecological Metadata Language (EML) standard. Here we will present how EDI achieves FAIR data principles (Wilkinson et al. 2016, Stall et al. 2017), and report data use metrics as a measure of success. The FAIR principles serve as benchmarks for EDI’s operation and management: the data we curate are Findable because they reside in an open repository, with unique and persistent digital object identifiers (DOIs) and standard metadata indexed as a searchable resource; they are Accessible through industry standard protocols and are, in most cases, under an open-access license (access control is available if required); Interoperability is achieved by archiving data in commonly used file formats, and both metadata and data are machine readable and accessible; rich, high quality science metadata, with automated congruence and completeness checking, render data fit for Reuse in multiple contexts and environments, along with easily generated data provenance to document their lineage. The success of this approach is proven by the number and spatial and temporal extent of recent re-analyses and synthesis efforts of these data. Although formal data citations are not yet common practice, a Google Scholar search reveals over 400 journal articles crediting data re-use through an EDI DOI. However, despite improved data availability, researchers still report that the largest time investment in synthesis projects is discovering, cleaning and combining primary datasets until all data are completely understood and converted to a similar format. Starting with long-term biodiversity observation data EDI is addressing this issue by implementing a pre-harmonization of thematically similar data sets. Positioned between the data author’s specific data format and larger biodiversity data stores or synthesis projects, this approach allows uniform access without the loss of ancillary information. This pre-harmonization step may be accomplished by data managers because the dataset still contains all original information without any aggregation or science question specific decisions for data omission or cleaning. The data are still distributed into distinct datasets allowing for asynchronous updating of long-term observations. The addition of specific and standardized metadata makes them easily discoverable.

Enhancing collaboration between ecologists and computer scientists: lessons learned and recommendations forward

AbstractIn the era of big data, ecologists are increasingly relying on computational approaches and tools to answer existing questions and pose new research questions. These include both software applications (e.g., simulation models, databases and machine learning algorithms) and hardware systems (e.g., wireless sensor networks, supercomputing, drones and satellites), motivating the need for greater collaboration between computer scientists and ecologists. Here, we outline some synergistic opportunities for scientists in both disciplines that can be gained by building collaborations between the computer science and ecology research communities, with a focus on the benefits to ecology specifically. We also identify past contributions of computer science to ecology, including high‐frequency environmental sensor technology, advanced supercomputing capacity for ecological modeling, databases for long‐term and high‐frequency datasets, and software programs for ecological analyses, to anticipate future potential contributions. These examples highlight the power and potential for further integration of computer science technology and ideas into the ecological research community. Finally, we translate our own experiences working together as a team of computer scientists and ecologists over the past decade into a conceptual framework with recommendations for supporting productive collaborations at the interface of the two disciplines. We specifically focus on how to apply best practices of team science for bridging computer science and ecology, which we advocate will substantially benefit ecology long‐term.

An Unexplored Side of Regeneration Niche: Seed Quantity and Quality Are Determined by the Effect of Temperature on Pollen Performance.

In 1977, Peter Grubb introduced the regeneration niche concept, which assumes that a plant species cannot persist if the environmental conditions are only suitable for adult plant growth and survival, but not for seed production, dispersal, germination, and seedling establishment. During the last decade, this concept has received considerable research attention as it helps to better understand community assembly, population dynamics, and plant responses to environmental changes. Yet, in its present form, it focuses too much on the post-fertilization stages of plant sexual reproduction, neglecting the fact that the environment can operate as a constraint at many points in the chain of processes necessary for successful regeneration. In this review, we draw the attention of the plant ecology research community to the pre-fertilization stages of plant sexual reproduction, an almost ignored but important aspect of the regeneration niche, and their potential consequences for successful seed production. Particularly, we focus on how temperature affects pollen performance and determines plant reproduction success by playing an important role in the temporal and spatial variations in seed quality and quantity. We also review the pollen adaptations to temperature stresses at different levels of plant organization and discuss the plasticity of the performance of pollen under changing temperature conditions. The reviewed literature demonstrates that pre-fertilization stages of seed production, particularly the extreme sensitivity of male gametophyte performance to temperature, are the key determinants of a species’ regeneration niche. Thus, we suggest that previous views stating that the regeneration niche begins with the production of seeds should be modified to include the preceding stages. Lastly, we identify several gaps in pollen-related studies revealing a framework of opportunities for future research, particularly how these findings could be used in the field of plant biology and ecology.

Questionable research practices in ecology and evolution.

We surveyed 807 researchers (494 ecologists and 313 evolutionary biologists) about their use of Questionable Research Practices (QRPs), including cherry picking statistically significant results, p hacking, and hypothesising after the results are known (HARKing). We also asked them to estimate the proportion of their colleagues that use each of these QRPs. Several of the QRPs were prevalent within the ecology and evolution research community. Across the two groups, we found 64% of surveyed researchers reported they had at least once failed to report results because they were not statistically significant (cherry picking); 42% had collected more data after inspecting whether results were statistically significant (a form of p hacking) and 51% had reported an unexpected finding as though it had been hypothesised from the start (HARKing). Such practices have been directly implicated in the low rates of reproducible results uncovered by recent large scale replication studies in psychology and other disciplines. The rates of QRPs found in this study are comparable with the rates seen in psychology, indicating that the reproducibility problems discovered in psychology are also likely to be present in ecology and evolution.

Species\u2013habitat associations in an old-growth temperate forest in northeastern China

BackgroundSpecies coexistence mechanisms and maintenance of biodiversity have long been considered important components of community ecology research. As one of the important mechanisms, species coexistence theory based on niche differentiation has received attention in past years. Thus, topography, through the formation of habitat heterogeneity, affects species distributions and coexistence. A 30-ha dynamic plot of mixed broadleaved-Korean pine (Pinus koraiensis) forest is located in the Heilongjiang Fenglin National Nature Reserve. We examined species–habitat associations using the torus-translation method. We aim to understand the habitat associations of different species, life forms (shrubs, trees), and shade tolerance (light-demanding, midtolerant, shade-tolerant) across life stages (sapling, juvenile and mature), providing further evidence for the role of niche theory in temperate forests.ResultsOf the 33 species we tested, 28 species (84.8%) were at least significantly associated with one habitat type. Positive associations were more frequent in the valley and slope (shady and sunny) and less frequent on the ridge. Thirty-four significant positive associations with the five habitats were detected at three life stages (11, 11 and 12 at the sapling stage, juvenile stage, and mature stage, respectively). The trees were positively associated with the valley, and the shrubs were positively associated with sunny and ridge. The majority of species’ habitat preferences shifted among different life stages; the exceptions were Corylus mandshurica, Maackia amurensis, Quercus mongolica, Picea jezoensis and Acer ukurunduense, which had consistent associations with the same habitat at all stages. The midtolerant trees and midtolerant shrubs were positively correlated with sunny across the three life stages.ConclusionsMost species show habitat preferences in the plot. These results indicate that niche theory plays an important role in species coexistence. Most species have no consistent association with habitat at different life stages.

Sample Management Across the National Ecological Observatory Network

From 81 study sites across the United States, the US National Ecological Observatory Network (NEON), generates >75,000 samples per year. Samples range from soil and dust deposition material, tissue samples (e.g., small mammals and fish), DNA extracts, and whole organisms (e.g., ground beetles and ticks). Samples are collected, processed, and documented according to protocols that are standardized across study sites and according to the needs of the ecological research community for future studies. NEON has faced numerous challenges with managing data related to these many diverse physical samples, particularly when data are gathered at numerous steps throughout processing. Here, we share these challenges as well as solutions, including innovative semantically driven software tools and processing pipelines that manage data from each sample's point of collection to its ultimate fate (consumption, archive facility, or partnering data repository) while maintaining links across sample hierarchies.

On the development of a predictive functional trait approach for studying terrestrial arthropods.

The characterization of ecological communities with functional traits allows to consider simultaneously the ability of a species to survive and reproduce in an environment, its interactions with other species and its effects on the ecosystem. Functional traits have been studied mainly by plant ecologists, but are increasingly common in the study of other taxa including arthropods. Arthropods represent a group for which a functional trait approach could be highly profitable because of their high diversity, abundance, ubiquity and role in many important ecological processes. This review synthesizes two decades of functional trait research on terrestrial arthropods. We show that while the approach has gained popularity, particularly in the last decade, the absence of clearly postulated hypotheses is a recurrent problem limiting generalization. Furthermore, studied traits are often poorly related to studied functions. To address these problems, we propose a step-by-step protocol to postulate clear hypotheses prior to trait selection and emphasize the need for a common set of more generalizable traits in future studies. Extending the functional trait approach to arthropods opens the door to improving our understanding of interspecific interactions and potential links between response and effect traits. We present the concept of trait-matching with several examples of arthropod traits known to be effective predictors of consumer-resource interactions. The development of a successful functional trait approach for terrestrial arthropods will necessitate an understanding of relevant traits, standardized measurement protocols and open access databases to share this information. Such progress will provide ecologists with a new set of tools to answer broad questions in several fields including the study of community assembly, ecological networks and multitrophic functionality.

A family of (dis)similarity measures based on evenness and its relationship with beta diversity

In this paper, I propose a new evenness-based method for calculating plot-to-plot (dis)similarity coefficients. The method is very flexible, as (dis)similarity can be calculated for any kind of species abundance data (also including functional or phylogenetic differences between species), and can be easily generalized to multiple sites. To show how the proposed method works in practice, the behavior of two similarity coefficients based on Pielou's and Williams’ evenness is examined with simulated data representing an ideal ecological gradient. Being derived from classical evenness indices, which have been used in ecology for decades, this new family of measures has a great potential for future research in community ecology and multivariate analysis.