The ability to explain why multispecies assemblages produce greater biomass compared to monocultures, has been a central goal in the quest to understand biodiversity effects on ecosystem function. ...Species contributions to ecosystem function can be driven by two processes: niche complementarity and a selection effect that is influenced by fitness (competitive) differences, and both can be approximated with measures of species’ traits. It has been hypothesised that fitness differences are associated with few, singular traits while complementarity requires multidimensional trait measures. Here, using experimental data from plant assemblages, I show that the selection effect was strongest when trait dissimilarity was low, while complementarity was greatest with high trait dissimilarity. Selection effects were best explained by a single trait, plant height. Complementarity was correlated with dissimilarity across multiple traits, representing above and below ground processes. By identifying the relevant traits linked to ecosystem function, we obtain the ability to predict combinations of species that will maximise ecosystem function.
There now is ample experimental evidence that speciose assemblages are more productive and provide a greater amount of ecosystem services than depauperate ones. However, these experiments often ...conclude that there is a higher probability of including complementary species combinations in assemblages with more species and lack a priori prediction about which species combinations maximize function. Here, I report the results of an experiment manipulating the evolutionary relatedness of constituent plant species across a richness gradient. I show that assemblages with distantly related species contributed most to the higher biomass production in multispecies assemblages, through species complementarity. Species produced more biomass than predicted from their monocultures when they were in plots with distantly related species and produced the amount of biomass predicted from monoculture when sown with close relatives. This finding suggests that in the absence of any other information, combining distantly related species in restored or managed landscapes may serve to maximize biomass production and carbon sequestration, thus merging calls to conserve evolutionary history and maximize ecosystem function.
1. The goal of conservation and restoration activities is to maintain biological diversity and the ecosystem services that this diversity provides. These activities traditionally focus on the ...measures of species diversity that include only information on the presence and abundance of species. Yet how diversity influences ecosystem function depends on the traits and niches filled by species. 2. Biological diversity can be quantified in ways that account for functional and phenotypic differences. A number of such measures of functional diversity (FD) have been created, quantifying the distribution of traits in a community or the relative magnitude of species similarities and differences. We review FD measures and why they are intuitively useful for understanding ecological patterns and are important for management. 3. In order for FD to be meaningful and worth measuring, it must be correlated with ecosystem function, and it should provide information above and beyond what species richness or diversity can explain. We review these two propositions, examining whether the strength of the correlation between FD and species richness varies across differing environmental gradients and whether FD offers greater explanatory power of ecosystem function than species richness. 4. Previous research shows that the relationship between FD and richness is complex and context dependent. Different functional traits can show individual responses to different gradients, meaning that important changes in diversity can occur with minimal change in richness. Further, FD can explain variation in ecosystem function even when richness does not. 5. Synthesis and applications. FD measures those aspects of diversity that potentially affect community assembly and function. Given this explanatory power, FD should be incorporated into conservation and restoration decision-making, especially for those efforts attempting to reconstruct or preserve healthy, functioning ecosystems.
Ecosystem stability in variable environments depends on the diversity of form and function of the constituent species. Species phenotypes and ecologies are the product of evolution, and the ...evolutionary history represented by co‐occurring species has been shown to be an important predictor of ecosystem function. If phylogenetic distance is a surrogate for ecological differences, then greater evolutionary diversity should buffer ecosystems against environmental variation and result in greater ecosystem stability. We calculated both abundance‐weighted and unweighted phylogenetic measures of plant community diversity for a long‐term biodiversity–ecosystem function experiment at Cedar Creek, Minnesota, USA. We calculated a detrended measure of stability in aboveground biomass production in experimental plots and showed that phylogenetic relatedness explained variation in stability. Our results indicate that communities where species are evenly and distantly related to one another are more stable compared to communities where phylogenetic relationships are more clumped. This result could be explained by a phylogenetic sampling effect, where some lineages show greater stability in productivity compared to other lineages, and greater evolutionary distances reduce the chance of sampling only unstable groups. However, we failed to find evidence for similar stabilities among closely related species. Alternatively, we found evidence that plot biomass variance declined with increasing phylogenetic distances, and greater evolutionary distances may represent species that are ecologically different (phylogenetic complementarity). Accounting for evolutionary relationships can reveal how diversity in form and function may affect stability.
Should Environmental Filtering be Abandoned? Cadotte, Marc W.; Tucker, Caroline M.
Trends in ecology & evolution (Amsterdam),
June 2017, 2017-06-00, 20170601, Volume:
32, Issue:
6
Journal Article
Peer reviewed
Environmental filtering, where the environment selects against certain species, is thought to be a major mechanism structuring communities. However, recent criticisms cast doubt on our ability to ...accurately infer filtering because competition can give rise to patterns identical to those caused by environmental filtering. While experiments can distinguish mechanisms, observational patterns are especially problematic. The environment determines community composition not only directly via survival, but also by influencing competition. If species population growth rates covary with environmental gradients, then outcomes of competitive exclusion will also vary with the environment. Here, we argue that observational studies remain valuable, but inferences about the importance of the environment cannot rely on compositional data alone, and that species abundances, population growth, or traits must be correlated with the environment.
The role of the environment for shaping community composition has been criticized recently.
Other mechanisms, such as competition, could produce similar patterns to environmental filtering.
We recognize that competition and the environment do not have separable affects on species and their interactions.
Researchers should use additional information to determine whether fitness–environment covariances influence composition.
Functional Rarity: The Ecology of Outliers Violle, Cyrille; Thuiller, Wilfried; Mouquet, Nicolas ...
Trends in ecology & evolution (Amsterdam),
05/2017, Volume:
32, Issue:
5
Journal Article
Peer reviewed
Open access
Rarity has been a central topic for conservation and evolutionary biologists aiming to determine the species characteristics that cause extinction risk. More recently, beyond the rarity of species, ...the rarity of functions or functional traits, called functional rarity, has gained momentum in helping to understand the impact of biodiversity decline on ecosystem functioning. However, a conceptual framework for defining and quantifying functional rarity is still lacking. We introduce 12 different forms of functional rarity along gradients of species scarcity and trait distinctiveness. We then highlight the potential key role of functional rarity in the long-term and large-scale maintenance of ecosystem processes, as well as the necessary linkage between functional and evolutionary rarity.
A framework for the definition and quantification of functional rarity is missing.
We define functional rarity using both species sparseness and trait distinctiveness.
We introduce 12 different forms of functional rarity.
We discuss the effect of each form of functional rarity on ecosystem function.
The necessary linkage between functional and evolutionary rarity is highlighted.
It is now commonplace in community ecology to assess patterns of phylogenetic or functional diversity in order to inform our understanding of the assembly mechanisms that structure communities. While ...both phylogenetic and functional approaches have been used in conceptually similar ways, it is not clear if they both in fact reveal similar community diversity patterns or support similar inferences. We review studies that use both measures to determine the degree to which they support congruent patterns and inferences about communities.
We performed a literature review with 188 analyses from 79 published papers that compared some facet of phylogenetic (PD) and functional diversity (FD) in community ecology. These studies generally report four main cases in which phylogenetic and functional information are used together in community analyses, to determine if: (a) there were phylogenetic signals in the measured traits in communities; (b) PD and FD were correlated with one another; (c) standardized PD and FD measures similarly revealed patterns of community over‐ or under‐dispersion; and (d) PD and FD were both related to other explanatory variables (e.g. elevation) similarly.
We found that the vast majority of studies found both strong phylogenetic signals in their traits and positive correlations of PD and FD measures across sites. However, and surprisingly, we found substantial incongruencies for the other tests. Phylogenetic and functional dispersion patterns were congruent only about half the time. Specifically, when communities were phylogenetically over‐dispersed, these same communities were more likely to be functionally under‐dispersed. Similarly, we found that phylogenetic and functional relationships with independent predictors were incongruent in about half of the analyses.
Synthesis. Phylogenetic signal tests and PD–FD correlations appear to strongly support the congruence between traits and phylogeny. It is surprising that strong phylogenetic signals appeared so ubiquitous given that ecological studies often analyse phylogenetically incomplete sets of species that have undergone ecological sorting. Despite the largely congruent findings based on phylogenetic signal tests and PD‐FD correlations, we found substantial incongruencies when researchers assessed either dispersion patterns or relationships with independent predictors. We discuss a number of potential ecological, evolutionary and methodological reasons for these incongruencies. Phylogenetic and functional information might reflect species ecological differences unequally with phylogenies better reflecting multivariate conserved elements of ecological similarity, and single traits better able to capture recent divergence, and both elements influence ecological patterns.
Phylogenetic signal tests and PD–FD correlations appear to strongly support the congruence between traits and phylogeny. It is surprising that strong phylogenetic signals appeared so ubiquitous given that ecological studies often analyse phylogenetically incomplete sets of species that have undergone ecological sorting. Despite the largely congruent findings based on phylogenetic signal tests and PD–FD correlations, we found substantial incongruencies when researchers assessed either dispersion patterns or relationships with independent predictors. We discuss a number of potential ecological, evolutionary and methodological reasons for these incongruencies. Phylogenetic and functional information might reflect species ecological differences unequally with phylogenies better reflecting multivariate conserved elements of ecological similarity, and single traits better able to capture recent divergence.
The Anthropocene epoch is partly defined by anthropogenic spread of crops beyond their centres of origin. At global scales, evidence indicates that species-level taxonomic diversity of crops being ...cultivated on large-scale agricultural lands has increased linearly over the past 50 years. Yet environmental and socio-economic differences support expectations that temporal changes in crop diversity vary across regions. Ecological theory also suggests that changes in crop taxonomic diversity may not necessarily reflect changes in the evolutionary diversity of crops. We used data from the Food and Agricultural Organization (FAO) of the United Nations to assess changes in crop taxonomic- and phylogenetic diversity across 22 subcontinental-scale regions from 1961-2014. We document certain broad consistencies across nearly all regions: i) little change in crop diversity from 1961 through to the late 1970s; followed by ii) a 10-year period of sharp diversification through the early 1980s; followed by iii) a "levelling-off" of crop diversification beginning in the early 1990s. However, the specific onset and duration of these distinct periods differs significantly across regions and are unrelated to agricultural expansion, indicating that unique policy or environmental conditions influence the crops being grown within a given region. Additionally, while the 1970s and 1980s are defined by region-scale increases in crop diversity this period marks the increasing dominance of a small number of crop species and lineages; a trend resulting in detectable increases in the similarity of crops being grown across regions. Broad similarities in the species-level taxonomic and phylogenetic diversity of crops being grown across regions, primarily at large industrial scales captured by FAO data, represent a unique feature of the Anthropocene epoch. Yet nuanced asymmetries in regional-scale trends suggest that environmental and socio-economic factors play a key role in shaping observed macro-ecological changes in the plant diversity on agricultural lands.
ABSTRACT
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub‐disciplines, particularly conservation, community ecology ...and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub‐disciplines hampers potential meta‐analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo‐diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information.
Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo‐diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α‐diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
Context
Environmental filtering is an important assembly process that structures plant communities and is commonly inferred from taxonomic, functional trait and phylogenetic patterns. However, while ...these approaches can be informative, the influence of other co-occurring processes on community diversity, such as competitive exclusion, remains poorly understood.
Objectives
By combing functional traits and a phylogeny of woody plants across anthropogenically created islands, we aim to explore the ways in which environmental filtering and competitive exclusion can simultaneously influence community assembly processes. We expect that communities on smaller islands, where competition for limited space and resources is more intense, should be functionally and phylogenetically less clustered than those on larger islands because this more intense competition should reduce the coexistence of the most closely related or functionally similar species.
Methods
We used ten functional traits and a phylogeny of 76 woody plant species to assess species diversity and similarity within communities across an island area gradient. We combed functional traits and phylogeny into a functional–phylogenetic distance matrix and calculated the communities’ mean functional-phylogenetic distance (MFPD) and its standardized effect size (SES.MFPD) as measures of ecological similarity.
Results
As expected, species were more phylo-functionally similar to one another than expected by chance within islands and this underdispersion grew stronger with island area, indicating that while islands generally contained clustered communities, environmental filtering and competitive exclusion were both likely occurring. By integrating species abundance distributions with community similarity, we found that the most abundant species were phylo-functionally similar to the least abundant species. Species richness increased with island area, as expected, but the additional species found only on larger islands tended to have low abundances, providing opportunities for rare species to persist.
Conclusions
With environmental filtering narrowing the number of species that can persist, the loss of phylo-functionally closely related rare species on smaller islands was likely caused by competition or stochastic removals, leading to greater species dissimilarity than on larger islands. On larger islands, the clustered patterns are likely to be the result of a combination of competitive exclusion caused by resource limitation and environmental filtering.
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