Ecological assembly rules in plant communities--approaches, patterns and prospects.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

Assembly rules for protein networks derived from phylogenetic-statistical analysis of whole genomes

Background: We report an analysis of a protein network of functionally linked proteins, identified from a phylogenetic statistical analysis of complete eukaryotic genomes. Phylogenetic methods identify pairs of proteins that co-evolve on a phylogenetic tree, and have been shown to have a high probability of correctly identifying known functional links. Results: The eukaryotic correlated evolution network we derive displays the familiar power law scaling of connectivity. We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species. We find that the connectivity distribution of proteins at the point they arise on the tree and join the network follows a power law, as does the connectivity distribution of proteins at the time they are lost from the network. Proteins resident in the network acquire connections over time, but we find no evidence that 'preferential attachment' - the phenomenon of newly acquired connections in the network being more likely to be made to proteins with large numbers of connections - influences the network structure. We derive a 'variable rate of attachment' model in which proteins vary in their propensity to form network interactions independently of how many connections they have or of the total number of connections in the network, and show how this model can produce apparent power-law scaling without preferential attachment. Conclusion: A few simple rules can explain the topological structure and evolutionary changes to protein-interaction networks: most change is concentrated in satellite proteins of low connectivity and small phenotypic effect, and proteins differ in their propensity to form attachments. Given these rules of assembly, power law scaled networks naturally emerge from simple principles of selection, yielding protein interaction networks that retain a high-degree of robustness on short time scales and evolvability on longer evolutionary time scales.

Scale decisions can reverse conclusions on community assembly processes.

AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.

Species divergence and trait convergence in experimental plant community assembly

Despite decades of research, it remains controversial whether ecological communities converge towards a common structure determined by environmental conditions irrespective of assembly history. Here, we show experimentally that the answer depends on the level of community organization considered. In a 9-year grassland experiment, we manipulated initial plant composition on abandoned arable land and subsequently allowed natural colonization. Initial compositional variation caused plant communities to remain divergent in species identities, even though these same communities converged strongly in species traits. This contrast between species divergence and trait convergence could not be explained by dispersal limitation or community neutrality alone. Our results show that the simultaneous operation of trait-based assembly rules and species-level priority effects drives community assembly, making it both deterministic and historically contingent, but at different levels of community organization.

Exploring community assembly through an individual-based model for trophic interactions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Assembly processes of invertebrate communities in springs across different spatial scales

Il presente lavoro ha lo scopo di comprendere i processi sottesi ai pattern di coesistenza tra le specie di invertebrati sorgentizi, distinguendo tra dinamiche stocastiche e deterministiche. Le sorgenti sono ecosistemi complessi e alcune loro caratteristiche (ad esempio l’insularità, la stabilità termica, la struttura ecotonale “a mosaico”, la frequente presenza di specie rare ed endemiche, o l’elevata diversità in taxa) le rendono laboratori naturali utili allo studio dei processi ecologici, tra cui i processi di assembly. Al fine di studiare queste dinamiche è necessario un approccio multi-scala, per questo motivi sono state prese in considerazione tre scale spaziali. A scala locale è stato compiuto un campionamento stagionale su sette sorgenti (quattro temporanee e tre permanenti) del Monte Prinzera, un affioramento ofiolitico vicino alla città di Parma. In questa area sono stati valutati l’efficacia e l’impatto ambientale di diversi metodi di campionamento e sono stati analizzati i drivers ecologici che influenzano le comunità. A scala più ampia sono state campionate per due volte 15 sorgenti della regione Emilia Romagna, al fine di identificare il ruolo della dispersione e la possibile presenza di un effetto di niche-filtering. A scala continentale sono state raccolte informazioni di letteratura riguardanti sorgenti dell’area Paleartica occidentale, e sono stati studiati i pattern biogeografici e l’influenza dei fattori climatici sulle comunità. Sono stati presi in considerazione differenti taxa di invertebrati (macroinvertebrati, ostracodi, acari acquatici e copepodi), scegliendo tra quelli che si prestavano meglio allo studio dei diversi processi in base alle loro caratteristiche biologiche e all’approfondimento tassonomico raggiungibile. I campionamenti biologici in sorgente sono caratterizzati da diversi problemi metodologici e possono causare impatti sugli ambienti. In questo lavoro sono stati paragonati due diversi metodi: l’utilizzo del retino con un approccio multi-habitat proporzionale e l’uso combinato di trappole e lavaggio di campioni di vegetazione. Il retino fornisce dati più accurati e completi, ma anche significativi disturbi sulle componenti biotiche e abiotiche delle sorgenti. Questo metodo è quindi raccomandato solo se il campionamento ha come scopo un’approfondita analisi della biodiversità. D’altra parte l’uso delle trappole e il lavaggio della vegetazione sono metodi affidabili che presentano minori impatti sull’ecosistema, quindi sono adatti a studi ecologici finalizzati all’analisi della struttura delle comunità. Questo lavoro ha confermato che i processi niche-based sono determinanti nello strutturare le comunità di ambienti sorgentizi, e che i driver ambientali spiegano una rilevante percentuale della variabilità delle comunità. Infatti le comunità di invertebrati del Monte Prinzera sono influenzate da fattori legati al chimismo delle acque, alla composizione e all’eterogeneità dell’habitat, all’idroperiodo e alle fluttuazioni della portata. Le sorgenti permanenti mostrano variazioni stagionali per quanto riguarda le concentrazioni dei principali ioni, mentre la conduttività, il pH e la temperatura dell’acqua sono più stabili. È probabile che sia la stabilità termica di questi ambienti a spiegare l’assenza di variazioni stagionali nella struttura delle comunità di macroinvertebrati. L’azione di niche-filtering delle sorgenti è stata analizzata tramite lo studio della diversità funzionale delle comunità di ostracodi dell’Emilia-Romagna. Le sorgenti ospitano più del 50% del pool di specie regionale, e numerose specie sono state rinvenute esclusivamente in questi habitat. Questo è il primo studio che analizza la diversità funzionale degli ostracodi, è stato quindi necessario stilare una lista di tratti funzionali. Analizzando il pool di specie regionale, la diversità funzionale nelle sorgenti non è significativamente diversa da quella misurata in comunità assemblate in maniera casuale. Le sorgenti non limitano quindi la diversità funzionale tra specie coesistenti, ma si può concludere che, data la soddisfazione delle esigenze ecologiche delle diverse specie, i processi di assembly in sorgente potrebbero essere influenzati da fattori stocastici come la dispersione, la speciazione e le estinzioni locali. In aggiunta, tutte le comunità studiate presentano pattern spaziali riconoscibili, rivelando una limitazione della dispersione tra le sorgenti, almeno per alcuni taxa. Il caratteristico isolamento delle sorgenti potrebbe essere la causa di questa limitazione, influenzando maggiormente i taxa a dispersione passiva rispetto a quelli a dispersione attiva. In ogni caso nelle comunità emiliano-romagnole i fattori spaziali spiegano solo una ridotta percentuale della variabilità biologica totale, mentre tutte le comunità risultano influenzate maggiormente dalle variabili ambientali. Il controllo ambientale è quindi prevalente rispetto a quello attuato dai fattori spaziali. Questo risultato dimostra che, nonostante le dinamiche stocastiche siano importanti in tutte le comunità studiate, a questa scala spaziale i fattori deterministici ricoprono un ruolo prevalente. I processi stocastici diventano più influenti invece nei climi aridi, dove il disturbo collegato ai frequenti eventi di disseccamento delle sorgenti provoca una dinamica source-sink tra le diverse comunità. Si è infatti notato che la variabilità spiegata dai fattori ambientali diminuisce all’aumentare dell’aridità del clima. Disturbi frequenti potrebbero provocare estinzioni locali seguite da ricolonizzazioni di specie provenienti dai siti vicini, riducendo la corrispondenza tra gli organismi e le loro richieste ambientali e quindi diminuendo la quantità di variabilità spiegata dai fattori ambientali. Si può quindi concludere che processi deterministici e stocastici non si escludono mutualmente, ma contribuiscono contemporaneamente a strutturare le comunità di invertebrati sorgentizi. Infine, a scala continentale, le comunità di ostracodi sorgentizi mostrano chiari pattern biogeografici e sono organizzate lungo gradienti ambientali principalmente collegati altitudine, latitudine, temperatura dell’acqua e conducibilità. Anche la tipologia di sorgente (elocrena, reocrena o limnocrena) è influente sulla composizione delle comunità. La presenza di specie rare ed endemiche inoltre caratterizza specifiche regioni geografiche.

Functional biogeography of oceanic islands and the scaling of functional diversity in the Azores

Analyses of species-diversity patterns of remote islands have been crucial to the development of biogeographic theory, yet little is known about corresponding patterns in functional traits on islands and how, for example, they may be affected by the introduction of exotic species. We collated trait data for spiders and beetles and used a functional diversity index (FRic) to test for nonrandomness in the contribution of endemic, other native (also combined as indigenous), and exotic species to functional-trait space across the nine islands of the Azores. In general, for both taxa and for each distributional category, functional diversity increases with species richness, which, in turn scales with island area. Null simulations support the hypothesis that each distributional group contributes to functional diversity in proportion to their species richness. Exotic spiders have added novel trait space to a greater degree than have exotic beetles, likely indicating greater impact of the reduction of immigration filters and/or differential historical losses of indigenous species. Analyses of species occurring in native-forest remnants provide limited indications of the operation of habitat filtering of exotics for three islands, but only for beetles. Although the general linear (not saturating) pattern of trait-space increase with richness of exotics suggests an ongoing process of functional enrichment and accommodation, further work is urgently needed to determine how estimates of extinction debt of indigenous species should be adjusted in the light of these findings.

Incompletely resolved phylogenetic trees inflate estimates of phylogenetic conservatism.

The tendency for more closely related species to share similar traits and ecological strategies can be explained by their longer shared evolutionary histories and represents phylogenetic conservatism. How strongly species traits co-vary with phylogeny can significantly impact how we analyze cross-species data and can influence our interpretation of assembly rules in the rapidly expanding field of community phylogenetics. Phylogenetic conservatism is typically quantified by analyzing the distribution of species values on the phylogenetic tree that connects them. Many phylogenetic approaches, however, assume a completely sampled phylogeny: while we have good estimates of deeper phylogenetic relationships for many species-rich groups, such as birds and flowering plants, we often lack information on more recent interspecific relationships (i.e., within a genus). A common solution has been to represent these relationships as polytomies on trees using taxonomy as a guide. Here we show that such trees can dramatically inflate estimates of phylogenetic conservatism quantified using S. P. Blomberg et al.'s K statistic. Using simulations, we show that even randomly generated traits can appear to be phylogenetically conserved on poorly resolved trees. We provide a simple rarefaction-based solution that can reliably retrieve unbiased estimates of K, and we illustrate our method using data on first flowering times from Thoreau's woods (Concord, Massachusetts, USA).

Large-scale patterns in morphological diversity and species assemblages in Neotropical Triatominae (Heteroptera: Reduviidae)

We analysed the spatial variation in morphological diversity (MDiv) and species richness (SR) for 91 species of Neotropical Triatominae to determine the ecological relationships between SR and MDiv and to explore the roles that climate, productivity, environmental heterogeneity and the presence of biomes and rivers may play in the structuring of species assemblages. For each 110 km x 110 km-cell on a grid map of America, we determined the number of species (SR) and estimated the mean Gower index (MDiv) based on 12 morphological attributes. We performed bootstrapping analyses of species assemblages to identify whether those assemblages were more similar or dissimilar in their morphology than expected by chance. We applied a multi-model selection procedure and spatial explicit analyses to account for the association of diversity-environment relationships. MDiv and SR both showed a latitudinal gradient, although each peaked at different locations and were thus not strictly spatially congruent. SR decreased with temperature variability and MDiv increased with mean temperature, suggesting a predominant role for ambient energy in determining Triatominae diversity. Species that were more similar than expected by chance co-occurred near the limits of the Triatominae distribution in association with changes in environmental variables. Environmental filtering may underlie the structuring of species assemblages near their distributional limits.

SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

Making better biogeographical predictions of species' distributions

1. Biogeographical models of species' distributions are essential tools for assessing impacts of changing environmental conditions on natural communities and ecosystems. Practitioners need more reliable predictions to integrate into conservation planning (e.g. reserve design and management). 2. Most models still largely ignore or inappropriately take into account important features of species' distributions, such as spatial autocorrelation, dispersal and migration, biotic and environmental interactions. Whether distributions of natural communities or ecosystems are better modelled by assembling individual species' predictions in a bottom-up approach or modelled as collective entities is another important issue. An international workshop was organized to address these issues. 3. We discuss more specifically six issues in a methodological framework for generalized regression: (i) links with ecological theory; (ii) optimal use of existing data and artificially generated data; (iii) incorporating spatial context; (iv) integrating ecological and environmental interactions; (v) assessing prediction errors and uncertainties; and (vi) predicting distributions of communities or collective properties of biodiversity. 4. Synthesis and applications. Better predictions of the effects of impacts on biological communities and ecosystems can emerge only from more robust species' distribution models and better documentation of the uncertainty associated with these models. An improved understanding of causes of species' distributions, especially at their range limits, as well as of ecological assembly rules and ecosystem functioning, is necessary if further progress is to be made. A better collaborative effort between theoretical and functional ecologists, ecological modellers and statisticians is required to reach these goals.

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints.