Biodiversity monitoring,earth observations and the ecology of scale

Human activity and land‐use change are dramatically altering the sizes, geographical distributions and functioning of biological populations worldwide, with tremendous consequences for human well‐being. Yet our ability to measure, monitor and forecast biodiversity change – crucial to addressing it – remains limited. Biodiversity monitoring systems are being developed to improve this capacity by deriving metrics of change from an array of in situ data (e.g. field plots or species occurrence records) and Earth observations (EO; e.g. satellite or airborne imagery). However, there are few ecologically based frameworks for integrating these data into meaningful metrics of biodiversity change. Here, I describe how concepts of pattern and scale in ecology could be used to design such a framework. I review three core topics: the role of scale in measuring and modelling biodiversity patterns with EO, scale‐dependent challenges linking in situ and EO data and opportunities to apply concepts of pattern and scale to EO to improve biodiversity mapping. From this analysis emerges an actionable approach for measuring, monitoring and forecasting biodiversity change, highlighting key opportunities to establish EO as the backbone of global‐scale, science‐driven conservation.     

Genomic data reveal ancient microendemism in forest scorpions across the California Floristic Province

The California Floristic Province (CFP) in western North America is a globally significant biodiversity hotspot. Elucidating patterns of endemism and the historical drivers of this diversity has been an important challenge of comparative phylogeography for over two decades. We generated phylogenomic data using ddRADseq to examine genetic structure in Uroctonus forest scorpions, an ecologically restricted and dispersal‐limited organism widely distributed across the CFP north to the Columbia River. We coupled our genetic data with species distribution models (SDMs) to determine climatically suitable areas for Uroctonus both now and during the Last Glacial Maximum. Based on our analyses, Uroctonus is composed of two major genetic groups that likely diverged over 2 million years ago. Each of these groups itself contains numerous genetic groups that reveal a pattern of vicariance and microendemism across the CFP. Migration rates among these populations are low. SDMs suggest forest scorpion habitat has remained relatively stable over the last 21 000 years, consistent with the genetic data. Our results suggest tectonic plate rafting, mountain uplift, river drainage formation and climate‐induced habitat fragmentation have all likely played a role in the diversification of Uroctonus. The intricate pattern of genetic fragmentation revealed across a temporal continuum highlights the potential of low‐dispersing species to shed light on small‐scale patterns of biodiversity and the underlying processes that have generated this diversity in biodiversity hotspots.     

Tectonics,climate and the diversification of the tropical African terrestrial flora and fauna

Tropical Africa is home to an astonishing biodiversity occurring in a variety of ecosystems. Past climatic change and geological events have impacted the evolution and diversification of this biodiversity. During the last two decades, around 90 dated molecular phylogenies of different clades across animals and plants have been published leading to an increased understanding of the diversification and speciation processes generating tropical African biodiversity. In parallel, extended geological and palaeoclimatic records together with detailed numerical simulations have refined our understanding of past geological and climatic changes in Africa. To date, these important advances have not been reviewed within a common framework. Here, we critically review and synthesize African climate, tectonics and terrestrial biodiversity evolution throughout the Cenozoic to the mid-Pleistocene, drawing on recent advances in Earth and life sciences. We first review six major geo-climatic periods defining tropical African biodiversity diversification by synthesizing 89 dated molecular phylogeny studies. Two major geo-climatic factors impacting the diversification of the sub-Saharan biota are highlighted. First, Africa underwent numerous climatic fluctuations at ancient and more recent timescales, with tectonic, greenhouse gas, and orbital forcing stimulating diversification. Second, increased aridification since the Late Eocene led to important extinction events, but also provided unique diversification opportunities shaping the current tropical African biodiversity landscape. We then review diversification studies of tropical terrestrial animal and plant clades and discuss three major models of speciation: (i) geographic speciation via vicariance (allopatry); (ii) ecological speciation impacted by climate and geological changes, and (iii) genomic speciation via genome duplication. Geographic speciation has been the most widely documented to date and is a common speciation model across tropical Africa. We conclude with four important challenges faced by tropical African biodiversity research: (i) to increase knowledge by gathering basic and fundamental biodiversity information; (ii) to improve modelling of African geophysical evolution throughout the Cenozoic via better constraints and downscaling approaches; (iii) to increase the precision of phylogenetic reconstruction and molecular dating of tropical African clades by using next generation sequencing approaches together with better fossil calibrations; (iv) finally, as done here, to integrate data better from Earth and life sciences by focusing on the interdisciplinary study of the evolution of tropical African biodiversity in a wider geodiversity context.     

A unifying quantitative framework for exploring the multiple facets of microbial biodiversity across diverse scales

Recent developments of molecular tools have revolutionized our knowledge of microbial biodiversity by allowing detailed exploration of its different facets and generating unprecedented amount of data. One key issue with such large datasets is the development of diversity measures that cope with different data outputs and allow comparison of biodiversity across different scales. Diversity has indeed three components: local (α), regional (γ) and the overall difference between local communities (β). Current measures of microbial diversity, derived from several approaches, provide complementary but different views. They only capture the β component of diversity, compare communities in a pairwise way, consider all species as equivalent or lack a mathematically explicit relationship among the α, β and γ components. We propose a unified quantitative framework based on the Rao quadratic entropy, to obtain an additive decomposition of diversity (γ = α + β), so the three components can be compared, and that integrate the relationship (phylogenetic or functional) among Microbial Diversity Units that compose a microbial community. We show how this framework is adapted to all types of molecular data, and we highlight crucial issues in microbial ecology that would benefit from this framework and propose ready‐to‐use R‐functions to easily set up our approach.     

Funding begets biodiversity

Aim Effective conservation of biodiversity relies on an unbiased knowledge of its distribution. Conservation priority assessments are typically based on the levels of species richness, endemism and threat. Areas identified as important receive the majority of conservation investments, often facilitating further research that results in more species discoveries. Here, we test whether there is circularity between funding and perceived biodiversity, which may reinforce the conservation status of areas already perceived to be important while other areas with less initial funding may remain overlooked. Location Eastern Arc Mountains, Tanzania. Methods We analysed time series data (1980–2007) of funding (n = 134 projects) and plant species records (n = 75,631) from a newly compiled database. Perceived plant diversity, over three decades, is regressed against funding and environmental factors, and variances decomposed in partial regressions. Cross‐correlations are used to assess whether perceived biodiversity drives funding or vice versa. Results Funding explained 65% of variation in perceived biodiversity patterns – six times more variation than accounted for by 34 candidate environmental factors. Cross‐correlation analysis showed that funding is likely to be driving conservation priorities and not vice versa. It was also apparent that investment itself may trigger further investments as a result of reduced start‐up costs for new projects in areas where infrastructure already exists. It is therefore difficult to establish whether funding, perceived biodiversity, or both drive further funding. However, in all cases, the results suggest that regional assessments of biodiversity conservation importance may be biased by investment. Funding effects might also confound studies on mechanisms of species richness patterns. Main conclusions Continued biodiversity loss commands urgent conservation action even if our knowledge of its whereabouts is incomplete; however, by concentrating inventory funds in areas already perceived as important in terms of biodiversity and/or where start‐up costs are lower, we risk losing other areas of underestimated or unknown value.     

Host plant richness explains diversity of ectomycorrhizal fungi: Response to the comment of Tedersoo et al. (2014)

Exploring the relationships between the biodiversity of groups of interacting organisms yields insight into ecosystem stability and function (Hooper et al. 2000 ; Wardle 2006 ). We demonstrated positive relationships between host plant richness and ectomycorrhizal (EM) fungal diversity both in a field study in subtropical China (Gutianshan) and in a meta‐analysis of temperate and tropical studies (Gao et al. 2013 ). However, based on re‐evaluation of our data sets, Tedersoo et al. ( 2014 ) argue that the observed positive correlation between EM fungal richness and EM plant richness at Gutianshan and also in our metastudies was based mainly from (i) a sampling design with inconsistent species pool and (ii) poor data compilation for the meta‐analysis. Accordingly, we checked our data sets and repeated the analysis performed by Tedersoo et al. ( 2014 ). In contrast to Tedersoo et al. ( 2014 ), our re‐analysis still confirms a positive effect of plant richness on EM fungal diversity in Gutianshan, temperate and tropical ecosystems, respectively.     

Appropriate application of information from biodiversity databases is critical when investigating species distributions and diversity: a comment on Dallas et al. ()

Using data from biodiversity informatics resources, Dallas et al. (Ecol. Lett., 20, 2017, 1526–1533) suggested limited relationships between climate and local abundance among several taxonomic groups. Investigation of a subset of these data suggests that their results may be misleading due to inappropriate application of the biodiversity data.     

Relationship Between Aboveground Biomass and Multiple Measures of Biodiversity in Subtropical Forest of Puerto Rico

Anthropogenic activities have accelerated the rate of global loss of biodiversity, making it more important than ever to understand the structure of biodiversity hotspots. One current focus is the relationship between species richness and aboveground biomass (AGB) in a variety of ecosystems. Nonetheless, species diversity, evenness, rarity, or dominance represent other critical attributes of biodiversity and may have associations with AGB that are markedly different than that of species richness. Using data from large trees in four environmentally similar sites in the Luquillo Experimental Forest of Puerto Rico, we determined the shape and strength of relationships between each of five measures of biodiversity (i.e., species richness, Simpson's diversity, Simpson's evenness, rarity, and dominance) and AGB. We quantified these measures of biodiversity using either proportional biomass or proportional abundance as weighting factors. Three of the four sites had a unimodal relationship between species richness and AGB, with only the most mature site evincing a positive, linear relationship. The differences between the mature site and the other sites, as well as the differences between our richness–AGB relationships and those found at other forest sites, highlight the crucial role that prior land use and severe storms have on this forest community. Although the shape and strength of relationships differed greatly among measures of biodiversity and among sites, the strongest relationships within each site were always those involving richness or evenness.     

Cryptic species complexes,widespread species and conservation: lessons from Amazonian frogs of the Leptodactylus marmoratus group (Anura: Leptodactylidae)

Morphologically cryptic species act as a wild card when it comes to biodiversity assessments and conservation, with the capacity to dramatically alter our understanding of the biological landscape at the taxonomic, ecological, biogeographic, evolutionary, and conservation levels. We discuss the potential effects that cryptic species may have on biodiversity assessments and conservation, as well as some of the current issues involving the treatment of cryptic species both at taxonomic and conservation levels. In addition, using a combination of advertisement call and morphological data, we describe a new species of the Leptodactylus marmoratus group from the upper Amazon basin, and we assess how cryptic species can affect conservation assessments of species in the Leptodactylus marmoratus group by examining how recent findings affect our understanding of the distribution of what is assumed to be a widespread Amazonian species, Leptodactylus andreae.     

Towards robust and repeatable sampling methods in eDNA‐based studies

DNA‐based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three‐year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA‐based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies.     

Phytoplankton diversity loss along a gradient of future warming and brownification in freshwater mesocosms

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Tree biodiversity in protected and logged Bornean tropical rain forests and its measurement by satellite remote sensing

Aim Conservation activities have increasingly focused on issues at the level of the landscape but are constrained by limited data and knowledge relating to biodiversity at this scale. Satellite remote sensing has considerable, but under‐exploited, potential as a source of information on biodiversity at the landscape level. Remote sensing has generally been used to assess biodiversity indirectly, using approaches that often fail to fully exploit the information content of the imagery and typically only with regard to the species richness component of biodiversity. The aim of this paper was to assess the potential of remote sensing as a source of information on the richness, evenness and composition of tree species in a tropical rain forest. Location The test site was a c. 225 km² region centred on the Danum Valley Field Centre, Borneo. This test site contained regions of undisturbed and differentially logged rain forest. Methods Data on tree biodiversity had been acquired for fifty‐two sample plots by standard field survey methods and were used to derive summary indices of biodiversity for seedlings, saplings and mature trees. Differences between logged and unlogged sites were evaluated by comparison of the indices and species accumulation curves. A Landsat Thematic Mapper (TM) image of the site acquired close to the date of the field survey was obtained and rigorously pre‐processed. Feedforward neural networks were used to derive predictions of biodiversity indices from the imagery. A Kohonen self organizing map neural network was used to ordinate the field data to derive classes of forest defined by relative similarity in species composition. The separability of the defined classes in the Landsat TM image was evaluated with a discriminant analysis. Results Analyses of the field data revealed considerable variation in the biodiversity of seedlings, saplings and trees at the site, associated, in part, with differences in logging activities. This variation in biodiversity was manifest in the remotely sensed data. The analyses indicated an ability to (1) predict biodiversity indices, with the highest correlation between predicted and actual index observed for evenness described by Shannon entropy (r = 0.546), but especially to (2) classify nine forest classes defined on the basis of similarity in tree species composition (accuracy 95.8%). Main conclusions Logging activities impacted on biodiversity and the resulting variation in biodiversity was reflected in the remotely sensed imagery. Using methods that exploit more fully the information content of the imagery than those used in other previous studies, a richer representation of biodiversity may be derived. This representation includes estimates of key summary indices of biodiversity, notably richness and evenness, as well as information on species composition. The results indicate that remotely sensed data may be used as a source of information on biodiversity at the landscape scale that may be used to inform conservation science and management.     

湖南单子叶植物1新记录科——闭鞘姜科及其分类学研究

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An ED-based Protocol for Optimal Sampling of Biodiversity

While conservation planning requires good biodiversity data, our knowledge of most living groups is scarce and patchy even in well-sampled regions. Therefore, we need methodologies for rapid assessments for particular groups and regions. Maps of any biodiversity surrogate can be interpolated from even a few well-known sites, but such places are usually lacking. We therefore propose a protocol for designing field surveys to obtain good coverage of pattern variations of biodiversity in a given region. To represent biodiversity patterns comprehensively, we use a rule step site-allocation procedure, partially based on Faith and Walker's ED criterion that takes environmental and spatial variation into account, together with other criteria such as survey costs. A preliminary assessment of the adequacy of this site sampling strategy is made. Then a set of complementary sites is selected for further sampling. Using the ED criterion, during the stepwise process a p-median analysis is applied both to an environmental distance matrix and to a spatial distance matrix, to maximize the amount of variation covered by our survey planning. This rule-set allocation procedure is integrated into a continuous sampling design protocol directed to ensure we can sample all biodiversity of a region. This protocol requires the gathering of both biological and environmental information, an assessment of previously available information, the choice of sampling methods and dates, and a continuous assessment of the success of the survey being carried out. An example of the application of this protocol to the survey design of dung beetle (Coleoptera, Scarabaeoidea) diversity in the Comunidad de Madrid (Spain) is included.     

Diversity of Dominant Bacterial Taxa in Activated Sludge Promotes Functional Resistance following Toxic Shock Loading

Examining the relationship between biodiversity and functional stability (resistance and resilience) of activated sludge bacterial communities following disturbance is an important first step towards developing strategies for the design of robust biological wastewater treatment systems. This study investigates the relationship between functional resistance and biodiversity of dominant bacterial taxa by subjecting activated sludge samples, with different levels of biodiversity, to toxic shock loading with cupric sulfate (Cu[II]), 3,5-dichlorophenol (3,5-DCP), or 4-nitrophenol (4-NP). Respirometric batch experiments were performed to determine the functional resistance of activated sludge bacterial community to the three toxicants. Functional resistance was estimated as the 30 min IC₅₀ or the concentration of toxicant that results in a 50% reduction in oxygen utilization rate compared to a referential state represented by a control receiving no toxicant. Biodiversity of dominant bacterial taxa was assessed using polymerase chain reaction-terminal restriction fragment length polymorphism (PCR-T-RFLP) targeting the 16S ribosomal RNA (16S rRNA) gene. Statistical analysis of 30 min IC₅₀ values and PCR-T-RFLP data showed a significant positive correlation (P < 0.05) between functional resistance and microbial diversity for each of the three toxicants tested. To our knowledge, this is the first study showing a positive correlation between biodiversity of dominant bacterial taxa in activated sludge and functional resistance. In this system, activated sludge bacterial communities with higher biodiversity are functionally more resistant to disturbance caused by toxic shock loading.     

Assessing the performance of DNA barcoding using posterior predictive simulations

Accurate estimates of biodiversity are required for research in a broad array of biological subdisciplines including ecology, evolution, systematics, conservation and biodiversity science. The use of statistical models and genetic data, particularly DNA barcoding, has been suggested as an important tool for remedying the large gaps in our current understanding of biodiversity. However, the reliability of biodiversity estimates obtained using these approaches depends on how well the statistical models that are used describe the evolutionary process underlying the genetic data. In this study, we utilize data from the Barcode of Life Database and posterior predictive simulations to assess the performance of DNA barcoding under commonly used substitution models. We demonstrate that the success of DNA barcoding varies widely across DNA substitution models and that model choice has a substantial impact on the number of operational taxonomic units identified (changing results by ~4–31%). Additionally, we demonstrate that the widely followed practice of a priori assuming the Kimura 2‐parameter model for DNA barcoding is statistically unjustified and should be avoided. Using both data‐based and inference‐based test statistics, we detect variation in model performance across taxonomic groups, clustering algorithms, genetic divergence thresholds and substitution models. Taken together, these results illustrate the importance of considering both model selection and model adequacy in studies quantifying biodiversity.     

Integrating conservation and development: incorporating vulnerability into biodiversity-assessment of areas

Protection of regional biodiversity requires that priority for protection of individual areas be based on both the contribution the area can make to representing overall biodiversity and the degree to which the area, in the absence of action, is vulnerable to loss of its biodiversity. Attempts to apply these criteria together largely have been ad hoc. A solution to this problem is presented for environmental surrogate data, based on environmental diversity (ED). ED uses a standard ecological continuum model to link environmental pattern to species-level biodiversity, so that a set of areas can be characterized by its relative expected biodiversity. This allows explicit incorporation of estimates of area-vulnerability, interpreted as the relative probability that any member species will not persist, into biodiversity assessments. The contribution of a given area to regional expected biodiversity is influenced not only by its own vulnerability value, but also by the vulnerability of other areas. Increasing the degree of protection of any area (reducing its vulnerability) will increase expected biodiversity: however, expected regional biodiversity sometimes may be maximized when limited resources for protection are directed to an area with lower vulnerability rather than to one with higher vulnerability.The allocation of land uses in a region need not be viewed as an all-or-nothing assignment of protection. The effect of a particular management regime on the biodiversity of a given area can be equated with some consequent degree of vulnerability; viewed positively, a management regime that offers some degree of biodiversity protection can make a measurable contribution to the protection of the biodiversity of a region.     

Evidence for rapid evolution in a grassland biodiversity experiment

In long‐term grassland experiments, positive biodiversity effects on plant productivity commonly increase with time. Subsequent glasshouse experiments showed that these strengthened positive biodiversity effects persist not only in the local environment but also when plants are transferred into a common environment. Thus, we hypothesized that community diversity had acted as a selective agent, resulting in the emergence of plant monoculture and mixture types with differing genetic composition. To test our hypothesis, we grew offspring from plants that were grown for eleven years in monoculture or mixture environments in a biodiversity experiment (Jena Experiment) under controlled glasshouse conditions in monocultures or two‐species mixtures. We used epiGBS, a genotyping‐by‐sequencing approach combined with bisulphite conversion, to provide integrative genetic and epigenetic (i.e., DNA methylation) data. We observed significant divergence in genetic and DNA methylation data according to selection history in three out of five perennial grassland species, namely Galium mollugo, Prunella vulgaris and Veronica chamaedrys, with DNA methylation differences mostly reflecting the genetic differences. In addition, current diversity levels in the glasshouse had weak effects on epigenetic variation. However, given the limited genome coverage of the reference‐free bisulphite method epiGBS, it remains unclear how much of the differences in DNA methylation was independent of underlying genetic differences. Our results thus suggest that selection of genetic variants, and possibly epigenetic variants, caused the rapid emergence of monoculture and mixture types within plant species in the Jena Experiment.     

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence‐only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi‐source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter‐ or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi‐source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA‐based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.     

A new integrative framework for large‐scale assessments of biodiversity and community dynamics,using littoral gastropods and crabs of British Columbia,Canada

Improving our understanding of species responses to environmental changes is an important contribution ecologists can make to facilitate effective management decisions. Novel synthetic approaches to assessing biodiversity and ecosystem integrity are needed, ideally including all species living in a community and the dynamics defining their ecological relationships. Here, we present and apply an integrative approach that links high‐throughput, multicharacter taxonomy with community ecology. The overall purpose is to enable the coupling of biodiversity assessments with investigations into the nature of ecological interactions in a community‐level data set. We collected 1195 gastropods and crabs in British Columbia. First, the General mixed Yule‐coalescent (GMYC) and the Poisson Tree Processes (PTP) methods for proposing primary species‐hypotheses based on cox1 sequences were evaluated against an integrative taxonomic framework. We then used data on the geographic distribution of delineated species to test species co‐occurrence patterns for nonrandomness using community‐wide and pairwise approaches. Results showed that PTP generally outperformed GMYC and thus constitutes a more effective option for producing species‐hypotheses in community‐level data sets. Nonrandom species co‐occurrence patterns indicative of ecological relationships or habitat preferences were observed for grazer gastropods, whereas assemblages of carnivorous gastropods and crabs appeared influenced by random processes. Species‐pair associations were consistent with current ecological knowledge, thus suggesting that applying community assembly within a large taxonomical framework constitutes a valuable tool for assessing ecological interactions. Combining phylogenetic, morphological and co‐occurrence data enabled an integrated view of communities, providing both a conceptual and pragmatic framework for biodiversity assessments and investigations into community dynamics.