Hierarchical Modelling Of Species Communities Research Articles

Traits mediate environmental responses of benthic ciliates in dynamic coastal habitats

AbstractAimUnderstanding how species' traits mediate environmental responses provides a mechanistic perspective on community assembly processes. Although traits that influence the response of multicellular organisms to environments have been studied, the identification of such traits in unicellular organisms, like ciliates, is underexplored. Since ciliates are dominant animals in coastal sandy sediments and contribute significantly to interstitial community respiration, identifying links between their occurrence and sandy‐coast characteristics is crucial for conserving biodiversity and protecting coastal habitats.LocationCoasts of China.MethodsWe used Hierarchical Modelling of Species Communities, a trait‐based joint species distribution model, to analyse ciliate community data collected from 344 sites belonging to 31 beaches across the Chinese coastline.ResultsWe found that physical variables play the most important role in determining ciliate occurrence. The beach index combines the tidal range, sediment grain size and beach slope of beach‐selected species based on body size as well as feeding type, while sediment grain size constrained different mobility types, with swimming species favouring fine sandy sediments. The significant contribution of phylogeny in explaining the residual variation among species responses indicates that there are phylogenetically conserved but unmeasured traits too that influence species' responses. Species richness of benthic ciliates was higher in dissipative beaches with high primary productivity.Main ConclusionsBased on our research, ciliate occurrence in coastal beaches is mediated by their traits which are filtered by local environmental variables. The beach index is essential in predicting distribution patterns and species richness of benthic ciliates. Nevertheless, further research is needed to identify additional traits that will enhance the accuracy of predicting ciliate niches. Our study provides insights into the mechanisms driving ciliate community assembly processes and has implications for the conservation of biodiversity in sandy coastal habitats.

How non-target chironomid communities respond to mosquito control: Integrating DNA metabarcoding and joint species distribution modelling

The conservation and management of riparian ecosystems rely on understanding the ecological consequences of anthropogenic stressors that impact natural communities. In this context, studies investigating the effects of anthropogenic stressors require reliable methods capable of mapping the relationships between taxa occurrence or abundance and environmental predictors within a spatio-temporal framework. Here, we present an integrative approach using DNA metabarcoding and Hierarchical Modelling of Species Communities (HMSC) to unravel the intricate dynamics and resilience of chironomid communities exposed to Bacillus thuringiensis var. israelensis (Bti). Chironomid emergence was sampled from a total of 12 floodplain pond mesocosms, half of which received Bti treatment, during a 16-week period spanning spring and summer of 2020. Subsequently, we determined the community compositions of chironomids and examined their genus-specific responses to the Bti treatment, considering their phylogenetic affiliations and ecological traits of the larvae. Additionally, we investigated the impact of the Bti treatment on the body size distribution of emerging chironomids. Our study revealed consistent responses to Bti among different chironomid genera, indicating that neither phylogenetic affiliations nor larval feeding strategies significantly contributed to the observed patterns. Both taxonomic and genetic diversity were positively correlated with the number of emerged individuals. Furthermore, our findings demonstrated Bti-related effects on chironomid body size distribution, which could have relevant implications for size-selective terrestrial predators. Hence, our study highlights the value of employing a combination of DNA metabarcoding and HMSC to unravel the complex dynamics of Bti-related non-target effects on chironomid communities. The insights gained from this integrated framework contribute to our understanding of the ecological consequences of anthropogenic stressors and provide a foundation for informed decision-making regarding the conservation and management of riparian ecosystems.

Can the habitat Ecological Infrastructure’s Diversity Index predict ant and bat biodiversity in Mediterranean agricultural floodplains? A multi-taxon approach using hierarchical modelling

Ecological Infrastructures (EIs) form a network of natural and semi-natural areas crucial to support biodiversity in human-altered landscapes. Several indices have been proposed to assess the ecological quality of EIs, but these have been seldom tested using animal biodiversity as a response variable. The Habitat Ecological Infrastructure's Diversity Index (HEIDI) was recently developed to assess the potential of EIs in supporting biological communities with distinct dispersal abilities. In this study, we evaluated the strength of the HEIDI as a proxy of ant (short-range dispersers) and bat (long-range dispersers) activity in two Mediterranean agricultural areas. For this, we applied a Hierarchical Modelling of Species Communities (HMSC) approach and modelled the multispecific response of ant and bat communities to the HEIDI values and to the scores of the individual categories that compose it. We additionally adopted a functional methodological approach by selecting as response variables the activity of functional guilds, namely animal community regulators, decomposers, and seed dispersers for the ant community, and the activity of echolocation guilds, such as short-range (BAT_SRE), mid-range (BAT_MRE), and long-range echolocators (BAT_LRE) for the bat community. Besides the HEIDI, we also used physiognomic and structural EI attributes, as well as the percentage of the agricultural matrix in the ecological area of influence as covariates in the HMSC approach. Our results showed that the HEIDI formula was particularly accurate in predicting bat activity (posterior mean estimates, βBAT_SRE = 2.80, βBAT_MRE = 0.61, βBAT_LRE = 2.76), but no significant relation was found between HEIDI values and ant activity. In the context of Mediterranean floodplain management, we recommend that practitioners may use the individual HEIDI categorical scores to identify key habitat features that promote ant and bat activity, such as vegetation and aquatic habitats, whilst final HEIDI values may be broadly used to estimate global bat activity.

Drivers behind co-occurrence patterns between pathogenic bacteria, protozoa, and helminths in populations of the multimammate mouse, Mastomys natalensis

Advances in experimental and theoretical work increasingly suggest that parasite interactions within a single host can affect the spread and severity of wildlife diseases. Yet empirical data to support predicted co-infection patterns are limited due to the practical challenges of gathering convincing data from animal populations and the stochastic nature of parasite transmission. Here, we investigated co-infection patterns between micro- (bacteria and protozoa) and macroparasites (gastro-intestinal helminths) in natural populations of the multimammate mouse (Mastomys natalensis). Fieldwork was performed in Morogoro (Tanzania), where we trapped 211 M. natalensis and tested their behaviour using a modified open-field arena. All animals were checked for the presence of helminths in their gastro-intestinal tract, three bacteria (Anaplasma, Bartonella, and Borrelia) and two protozoan genera (Babesia and Hepatozoon). Besides the presence of eight different helminth genera (reported earlier), we found that 19% of M. natalensis were positive for Anaplasma, 10% for Bartonella, and 2% for Hepatozoon species. Hierarchical modelling of species communities was used to investigate the effect of the different host-related factors on these parasites’ infection probability and community structure. Our results show that the infection probability of Bartonella increased with the host's age, while the infection probability of Anaplasma peaked when individuals reached adulthood. We also observed that less explorative and stress-sensitive individuals had a higher infection probability with Bartonella. Finally, we found limited support for within-host interactions between micro-and macroparasites, as most co-infection patterns could be attributed to host exposure time.

Macrosystem community change in lake phytoplankton and its implications for diversity and function.

We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints. Finland. 1977-2017. Phytoplankton. We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a "region of common profile" approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development. We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities. Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novelcommunity types, but only a minor part of this reshuffling could be linked to temporal environmental change.

Tick microbial associations at the crossroad of horizontal and vertical transmission pathways

BackgroundMicrobial communities can affect disease risk by interfering with the transmission or maintenance of pathogens in blood-feeding arthropods. Here, we investigated whether bacterial communities vary between Ixodes ricinus nymphs which were or were not infected with horizontally transmitted human pathogens.MethodsTicks from eight forest sites were tested for the presence of Borrelia burgdorferi sensu lato, Babesia spp., Anaplasma phagocytophilum, and Neoehrlichia mikurensis by quantitative polymerase chain reaction (qPCR), and their microbiomes were determined by 16S rRNA amplicon sequencing. Tick bacterial communities clustered poorly by pathogen infection status but better by geography. As a second approach, we analysed variation in tick microorganism community structure (in terms of species co-infection) across space using hierarchical modelling of species communities. For that, we analysed almost 14,000 nymphs, which were tested for the presence of horizontally transmitted pathogens B. burgdorferi s.l., A. phagocytophilum, and N. mikurensis, and the vertically transmitted tick symbionts Rickettsia helvetica, Rickettsiella spp., Spiroplasma ixodetis, and CandidatusMidichloria mitochondrii.ResultsWith the exception of Rickettsiella spp., all microorganisms had either significant negative (R. helvetica and A. phagocytophilum) or positive (S. ixodetis, N. mikurensis, and B. burgdorferi s.l.) associations with M. mitochondrii. Two tick symbionts, R. helvetica and S. ixodetis, were negatively associated with each other. As expected, both B. burgdorferi s.l. and N. mikurensis had a significant positive association with each other and a negative association with A. phagocytophilum. Although these few specific associations do not appear to have a large effect on the entire microbiome composition, they can still be relevant for tick-borne pathogen dynamics.ConclusionsBased on our results, we propose that M. mitochondrii alters the propensity of ticks to acquire or maintain horizontally acquired pathogens. The underlying mechanisms for some of these remarkable interactions are discussed herein and merit further investigation.Graphical Positive and negative associations between and within horizontally and vertically transmitted symbionts

Preserving wintering frugivorous birds in agro‐ecosystems under land use change: Lessons from intensive and super‐intensive olive orchards

Abstract Fleshy fruit production is becoming more intensive worldwide, but how this affects frugivorous birds is poorly known. In the Mediterranean region, intensive and super‐intensive olive orchards are fast expanding, potentially affecting millions of wintering songbirds. Here, we test the idea that intensification may benefit frugivorous birds, at least locally, due to increased fruit availability, while negatively affecting the wider wintering bird community due to intensive management, structural simplification and landscape homogenisation. We estimated olive abundance and surveyed birds in early, mid‐ and late winter, at traditional, intensive and super‐intensive orchards in southern Portugal. We used Hierarchical Modelling of Species Communities to relate species richness, prevalence and abundance to management intensity, winter period, olive availability and landscape context, and evaluated the role of frugivory in modulating observed responses. Olive availability was much higher throughout the winter in more intensive than in traditional orchards, both in trees and on the ground. Frugivorous bird abundance was higher in more intensive orchards, and the most abundant frugivorous species (blackcap, song thrush, robin) were positively affected by olive availability and/or increasing landscape cover by olive orchards, while intensification level had relatively minor effects after accounting for other variables. Non‐frugivorous richness and abundance were higher in traditional orchards, and many non‐frugivorous species had lower prevalence in more intensive orchards or were negatively affected by landscapes dominated by olive cultivation. Synthesis and applications. While negatively affecting the wider bird community, our results suggest that olive farming intensification can contribute to sustaining large numbers of frugivorous birds in the Mediterranean region. As frugivorous birds are not seen as damaging by olive farmers, there is an opportunity to promote their conservation in intensive and super‐intensive orchards, which requires management to increase habitat heterogeneity, and to reduce risks such as mortality associated with mechanical harvest and contamination with pesticide residues. Overall, we recommend that efforts to manage farmland biodiversity should consider the impacts and conservation opportunities of fruit crop intensification.

Responses of phytoplankton community structure and association to variability in environmental drivers in a tropical coastal lagoon

Spatial and seasonal heterogeneity in phytoplankton communities are governed by many biotic and abiotic drivers. However, the identification of long-term spatial and temporal trends in abiotic drivers, and their interdependencies with the phytoplankton communities' structure is understudied in tropical brackish coastal lagoons. We examined phytoplankton communities' spatiotemporal dynamics from a 5-year dataset (n = 780) collected from 13 sampling stations in Chilika Lagoon, India, where the salinity gradient defined the spatial patterns in environmental variables. Generalized additive models showed a declining trend in phytoplankton biomass, pH, and dissolved PO4 in the lagoon. Hierarchical modelling of species communities revealed that salinity (44.48 ± 28.19%), water temperature (4.37 ± 5.65%), and season (4.27 ± 0.96%) accounted for maximum variation in the phytoplankton composition. Bacillariophyta (Indicator Value (IV): 0.74) and Dinophyta (IV: 0.72) emerged as top indicators for polyhaline regime whereas, Cyanophyta (IV: 0.81), Euglenophyta (IV: 0.79), and Chlorophyta (IV: 0.75) were strong indicators for oligohaline regime. The responses of Dinophyta and Chrysophyta to environmental drivers were much more complex as random effects accounted for ~70–75% variation in their abundances. Prorocentrum minimum (IV: 0.52), Gonyaulax sp. (IV: 0.52), and Alexandrium sp. (IV: 0.51) were potential indicators of P-limitation. Diploneis weissflogii (IV: 0.43), a marine diatom, emerged as a potential indicator of N-limitation. Hierarchical modelling revealed the positive association between Cyanophyta, Chlorophyta, and Euglenophyta whereas, Dinophyta and Chrysophyta showed a negative association with Cyanophyta, Chlorophyta, and Euglenophyta. Landsat 8-Operational Land Imager satellite models predicted the highest and lowest Cyanophyta abundances in northern and southern sectors, respectively, which were in accordance with the near-coincident field-based measurements from the lagoon. This study highlighted the dynamics of phytoplankton communities and their relationships with environmental drivers by separating the signals of habitat filtering and biotic interactions in a monsoon-regulated tropical coastal lagoon.

Environmental DNA diffusion of reef fishes along a distance gradient from four isolated islands of the Western Indian Ocean

Islands have traditionally served as model systems to study ecological and evolutionary processes (Warren et al. 2015) and could also represent a relevant system to study environmental DNA (eDNA). Isolated island reefs that are affected by climatic threats would particularly benefit from cost- and time-efficient biodiversity surveys to set priorities for their conservation. Among time efficiency methods, eDNA has emerged as a novel molecular metabarcoding technique to detect biodiversity from simple environmental samples even in remote marine environments. However, eDNA monitoring techniques for marine environments are at a developmental phase, with a few remaining unknowns related to DNA residence time and movement. In particular, the redistribution of eDNA, via ocean currents, could blur the composition signal and its association with local environmental conditions (Goldberg et al. 2016). Here, we investigated the detection variation of eDNA along a distance gradient across four islands in the French Scattered Islands. We collected 30 L of surface water per filter at an increasing distance from the islands reefs (0m, 250m, 500m, 750m). Using a metabarcoding protocol, we used the teleo primers to target a fraction of 12S mitochondrial DNA to detect Actinopterygii and Elasmobranchii. We then applied a sequence clustering approach to generate Molecular Taxonomic Units (MOTUs), which were assigned to a taxonomic group using a reference database. By assigning eDNA sequences to species using a public reference database, we classified species according to their preferred habitat types between benthic/demersal and pelagic. Our results show no significant relationship between distance and MOTUs richness for both habitat types. By using a Joint Species Distribution Modelling approach (JSDM, Hierarchical Modelling of Species Communities), we retained the multidimensional information captured by eDNA and detect species- and family-specific responses to distance (Fig. 1). We showed that benthic MOTUs were found in closer proximity to the reef, while typical pelagic MOTUs were found at greater distances from the reef. Hence, MOTU-level analyses coupled with JSDM were more informative that when aggregating it into coarser richness. Altogether, our eDNA distance sampling gradient detected an ecological signal of habitat selection by fish species, which suggest that eDNA could help understand the behavior of species and their distribution in marine environments at a fine spatial scale.

Improving prediction of rare species\u2019 distribution from community data

Species distribution models (SDMs) have been increasingly used to predict the geographic distribution of a wide range of organisms; however, relatively fewer research efforts have concentrated on rare species despite their critical roles in biological conservation. The present study tested whether community data may improve modelling rare species by sharing information among common and rare ones. We chose six SDMs that treat community data in different ways, including two traditional single-species models (random forest and artificial neural network) and four joint species distribution models that incorporate species associations implicitly (multivariate random forest and multi-response artificial neural network) or explicitly (hierarchical modelling of species communities and generalized joint attribute model). In addition, we evaluated two approaches of data arrangement, species filtering and conditional prediction, to enhance the selected models. The model predictions were tested using cross validation based on empirical data collected from marine fisheries surveys, and the effects of community data were evaluated by comparing models for six selected rare species. The results demonstrated that the community data improved the predictions of rare species’ distributions to certain extent but might also be unhelpful in some cases. The rare species could be appropriately predicted in terms of occurrence, whereas their abundance tended to be underestimated by most models. Species filtering and conditional predictions substantially benefited the predictive performances of multiple- and single-species models, respectively. We conclude that both the modelling algorithms and community data need to be carefully selected in order to deliver improvement in modelling rare species. The study highlights the opportunity and challenges to improve prediction of rare species’ distribution by making the most of community data.

Elevation shapes biodiversity patterns through metacommunity-structuring processes

Stochastic (e.g., via species dispersal and ecological drift) and deterministic (e.g., via environmental and biotic filtering) processes can produce diversity patterns related to changes in elevation. However, existing studies have not generally examined these processes within a compressive framework. Stream macroinvertebrates are an important and diverse component of freshwater environments in high-mountain systems. By considering metacommunity-structuring processes using Hierarchical Modelling of Species Communities (HMSC), we investigated changes in taxon richness of stream macroinvertebrates along elevational gradients in streams of the Cangshan mountain range in Southwest China. We found that increasing taxon richness along the elevation gradient until the optimum was reached could be modeled using the integrated actions of full structuring processes within the metacommunity modeling. Consistent increases in taxon-richness along the elevation gradient were able to be modeled considering environmental filtering alone. In addition, the importance of structuring processes on shaping communities decreased along spatial hierarchical-scales (from local habitat to mountain-aspect levels). These results suggest that stochastic and biotic-filtering processes can confound environmental filtering in shaping macroinvertebrate communities in high-mountain streams. A comprehensive understanding of the mechanisms underlying elevational biodiversity patterns of riverine communities can be improved through quantitative frameworks (e.g., HMSC) linking metacommunity theory to the real-world systems.

Saproxylic beetle assemblages in recently dead Scots pines: How traits modulate species’ response to forest management?

Boreal forests have been intensively managed, influencing the spatiotemporal occurrence of dead wood, and leading to changes in saproxylic species assemblages. Some particular traits, such as habitat specialization, can be expected to make species sensitive to alterations in the amount, dynamics and heterogeneity of dead-wood habitats. We compared the saproxylic beetle assemblages of 320 dead standing Scots pines within 52 pine forest stands in three regions in Finland and Russia with contrasting forest-use history. We used the joint species distribution model of Hierarchical Modelling of Species Communities (HMSC) to analyze how the beetle communities respond to alteration of forest structure. We applied scenario simulations to examine relationships between selected species traits and environmental gradients. Our results show that tree-level characteristics were the most important variables shaping the community composition in dead standing pines, but that also the characteristics of the forest stand as well as the larger-scale landscape context affected assemblage composition. Most importantly, managed forest stands and managed forest landscapes had lost species that are specialized in their resource use. The generalist species thriving in managed forest stands and managed forest landscapes were able to utilize dead wood of small diameter and man-made dead wood types, such as cut stumps and logging residues. We conclude that forest management not only reduces the amount of resources for saproxylic beetles locally, but has also landscape-level effects so that the most vulnerable species with specialized resource use and short-lived substrates can be lost also from remnant natural forest patches embedded in managed landscapes.

Evaluating the influence of spatially varying catchability on multispecies distribution modelling

Abstract Varying catchability is a common feature in fisheries and has great impacts on fisheries assessments and species distribution models. However, spatial variations in catchability have been rarely evaluated, especially in the multispecies context. We advocate that the need for multispecies models stands for both challenges and opportunities to handle spatial catchability. This study evaluated the influence of spatially varying catchability on the performance of a novel joint species distribution model, namely Hierarchical Modelling of Species Communities (HMSC). We implemented the model under nine simulation scenarios to account for diverse spatial patterns of catchability and conducted empirical tests using survey data from Yellow Sea, China. Our results showed that ignoring variability in catchability could lead to substantial errors in the inferences of species response to environment. Meanwhile, the models’ predictive power was less impacted, yielding proper predictions of relative abundance. Incorporating a spatially autocorrelated structure substantially improved the predictability of HMSC in both simulation and empirical tests. Nevertheless, combined sources of spatial catchabilities could largely diminish the advantage of HMSC in inference and prediction. We highlight situations where catchability needs to be explicitly accounted for in modelling fish distributions, and suggest directions for future applications and development of JSDMs.

Effects of illegal logging on Amazonian medium and large-sized terrestrial vertebrates

Selective logging is a major form of land use in tropical rainforests, with more than half of the world’s tropical forest already explored. In the Brazilian Amazon, most logging operations are illegal and highly damaging to forests. However, the effects of illegal logging on wildlife are poorly studied. Here we investigate the effects of illegal logging on the assemblage of medium- to large-bodied terrestrial vertebrates at the Gurupi Biological Reserve, a protected area in extreme eastern Amazonia that has been subjected to three decades of illegal logging. We used camera traps to survey the terrestrial vertebrate assemblage and visual interpretation of Landsat time series data (1984–2016) to assess the history of illegal logging (number of logging bouts and recovery time) for each camera trap site. Hierarchical Modelling of Species Communities (HMSC) indicates that logging had a minor effect on both the assemblage composition and individual species abundance. At the local level, the study demonstrates that the reserve effectively safeguards a significant portion of the regional biodiversity even though it suffered degradation by illegal logging. At a wider scale, the results suggest that illegally logged forests can retain much of their conservation value, if they are protected from further anthropogenic impacts such as hunting, fragmentation and fires. However, our study represents a best-case scenario, unlikely to be met in most other illegally logged areas in the tropics, where logging is usually followed by secondary effects that amplify its impacts.

Marine epibenthic functional diversity on Flemish Cap (north‐west Atlantic)—Identifying trait responses to the environment and mapping ecosystem functions

AbstractAimTo characterize the functional diversity and selected ecological functions of marine epibenthic invertebrate communities at the ecosystem scale and to evaluate the relative contributions of environmental filtering, including bottom‐contact fishing, and competitive interactions to benthic community assembly.LocationFlemish Cap, an ecosystem production unit and fishing bank in the high seas of the north‐west Atlantic Ocean.MethodsThrough the use of Hierarchical Modelling of Species Communities (HMSC), we have explored seven community response traits to the environment applied to 105 epibenthic species and evaluated the influence of such traits on the community assembly processes. Assumed bioturbation, nutrient cycling and habitat provision functions, linked to individual or a combination of biological traits, were mapped using random forest modelling.ResultsFunctional richness within benthic communities reached an asymptote for trawl sets with roughly more than 30 species. Assemblages on top of the Flemish Cap (<500 m depth) were characterized by higher biomass of small‐ and medium‐sized species with short life spans, whereas large species with longer life spans and broadcast spawners were dominant in the deeper assemblages (500–1,500 m depth). The amount of variation explained by the species’ responses to the covariates mediated by the traits was relatively high (25%) indicating their relevance to community assembly. Community‐weighted mean trait values changed with depth and physical oceanographic variables, indicating that environmental filtering was occurring. Interspecific interactions, as inferred from the random effect at the sample level, accounted for 16.3% of the variance in the model, while fishing effort explained only 5.2% of the variance but conferred strong negative impacts for most species.Main conclusionsOur results suggest that while bottom‐contact fishing impacts have an effect on functional diversity, changes to the physical oceanography of the system are likely to have more profound impacts. The maps of benthic functioning can aid assessments of ecosystem impacts of fishing.

Joint species distribution modelling with the r-package Hmsc.

Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio‐temporal context of the study, providing predictive insights into community assembly processes from non‐manipulative observational data of species communities.The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user‐friendly r implementation.We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio‐temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single‐species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence–absence data.The package, along with the extended vignettes, makes JSDM fitting and post‐processing easily accessible to ecologists familiar with r.

Using hierarchical joint models to study reproductive interactions in plant communities

Abstract Pollinator‐mediated reproductive interactions among co‐flowering plant species are prime examples of how species interactions may affect fitness and community assembly. Despite considerable interest in these issues, statistical methods for assessing signal of reproductive interactions in observational data on co‐flowering species are currently lacking. We propose a flexible method for quantifying potential reproductive interactions among co‐flowering plant species using the hierarchical latent‐variable joint models implemented in the Hierarchical Modelling of Species Communities (HMSC) framework. The method accommodates any measure of reproductive success, including pollinator visitation, stigma pollen loads, and seed set. We demonstrate the method by analysing a dataset on bumblebee visitation to a set of co‐flowering plant species in a species‐rich meadow in Norway, and provide R tutorials for this and additional data types. The example analysis revealed both positive and negative effects of heterospecific flower abundances on visitation to co‐flowering species, which we interpret as potential reproductive interactions. Synthesis. Hierarchical joint models provide a flexible approach to analysing patterns of covariation in the reproductive success of co‐flowering species, thus identifying potential species interactions. Important strengths include explicit consideration of community‐level effects and the assessment of residual fitness correlations after controlling for covariates such as flower abundances and phenotypic traits, yielding more complete insights into pollinator‐mediated reproductive interactions.

Long-term shifts in water quality show scale-dependent bioindicator responses across Russia – Insights from 40 year-long bioindicator monitoring program

Scale-related assessment strategies are important contributions to successful ecosystem management. With varying impact of environmental drivers from local to regional scales, a focal task is to understand scale-dependent responses when assessing the state of an ecosystem. In this study we use large-scale monitoring data, spanning 40 years and including four aquatic bioindicator groups (phytoplankton, zooplankton, periphyton, zoobenthos) to expose the long-term changes of water quality across Russia. We include four hierarchical spatial scales (region, basin, waterbody and observation point) to identify the relative importance of different spatio-temporal scales for the variation of each bioindicator and patterns of co-variation among the bioindicators at different hierarchical levels. We analysed the data with Hierarchical Modelling of Species Communities (HMSC), an approach that belongs to the framework of joint species distribution models. We performed a cross validation to reveal the predictive power of modelled bioindicator variation, partitioned explained variance among the fixed effects (waterbody type, and influence of human population density) and the random effects (spatial and spatio-temporal variation at the four hierarchical scales), and examined the co-variation among bioindicators at each spatio-temporal scale. We detected generally decreasing water quality across Russian freshwaters, yet with region and bioindicator specific trends. For all bioindicators, the dominating part of the variation was attributed the largest (region) and smallest (observation point) hierarchical scales, the region particularly important for benthic and the observation point for pelagic bioindicators. All bioindicators captured the same spatial variation in water quality at the smallest scale of observation point, with phytoplankton, zooplankton and periphyton being associated positively to each other and negatively to zoobenthos. However, at larger spatial scales and at spatio-temporal scales, the associations among the bioindicators became more complex, with phytoplankton and zooplankton showing opposite trends over time. Our study reveals the sensitivity of bioindicators to spatial and temporal scales. While delivering unidirectional robust water quality assessments at the local scale, bioindicator co-variation is more complex over larger geographic scales and over time.

How to make more out of community data? A conceptual framework and its implementation as models and software.

Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R- and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples.