Assembly of functional diversity in an oceanic island flora.

Oceanic island floras are well known for their morphological peculiarities and exhibit striking examples of trait evolution1-3. These morphological shifts are commonly attributed to insularity and are thought to be shaped by the biogeographical processes and evolutionary histories of oceanic islands2,4. However, the mechanisms through which biogeography and evolution have shaped the distribution and diversity of plant functional traits remain unclear5. Here we describe the functional trait space of the native flora of an oceanic island (Tenerife, Canary Islands, Spain) using extensive field and laboratory measurements, and relate it to global trade-offs in ecological strategies. We find that the island trait space exhibits a remarkable functional richness but that most plants are concentrated around a functional hotspot dominated by shrubs with a conservative life-history strategy. By dividing the island flora into species groups associated with distinct biogeographical distributions and diversification histories, our results also suggest that colonization via long-distance dispersal and the interplay between inter-island dispersal and archipelago-level speciation processes drive functional divergence and trait space expansion. Contrary to our expectations, speciation via cladogenesis has led to functional convergence, and therefore only contributes marginally to functional diversity by densely packing trait space around shrubs. By combining biogeography, ecology and evolution, our approach opens new avenues for trait-based insights into how dispersal, speciation and persistence shape the assembly of entire native island floras.

The ecological causes of functional distinctiveness in communities.

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.

The contribution of plant life and growth forms to global gradients of vascular plant diversity.

Plant life and growth forms (shortened to 'plant forms') represent key functional strategies of plants in relation to their environment and provide important insights into the ecological constraints acting on the distribution of biodiversity. Despite their functional importance, how the spectra of plant forms contribute to global gradients of plant diversity is unresolved. Using a novel dataset comprising > 295 000 species, we quantify the contribution of different plant forms to global gradients of vascular plant diversity. Furthermore, we establish how plant form distributions in different biogeographical regions are associated with contemporary and paleoclimate conditions, environmental heterogeneity and phylogeny. We find a major shift in representation of woody perennials in tropical latitudes to herb-dominated floras in temperate and boreal regions, following a sharp latitudinal gradient in plant form diversity from the tropics to the poles. We also find significant functional differences between regions, mirroring life and growth form responses to environmental conditions, which is mostly explained by contemporary climate (18-87%), and phylogeny (6-62%), with paleoclimate and heterogeneity playing a lesser role (< 23%). This research highlights variation in the importance of different plant forms to diversity gradients world-wide, shedding light on the ecological and evolutionary pressures constraining plant-trait distributions.

Links to rare climates do not translate into distinct traits for island endemics.

Current models of island biogeography treat endemic and non-endemic species as if they were functionally equivalent, focussing primarily on species richness. Thus, the functional composition of island biotas in relation to island biogeographical variables remains largely unknown. Using plant trait data (plant height, leaf area and flower length) for 895 native species in the Canary Islands, we related functional trait distinctiveness and climate rarity for endemic and non-endemic species and island ages. Endemics showed a link to climatically rare conditions that is consistent with island geological change through time. However, functional trait distinctiveness did not differ between endemics and non-endemics and remained constant with island age. Thus, there is no obvious link between trait distinctiveness and occupancy of rare climates, at least for the traits measured here, suggesting that treating endemic and non-endemic species as functionally equivalent in island biogeography is not fundamentally wrong.

Global models and predictions of plant diversity based on advanced machine learning techniques.

Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge of its global distribution is still incomplete, hampering basic research and biodiversity conservation. Here, we used machine learning (random forests, extreme gradient boosting, and neural networks) and conventional statistical methods (generalized linear models and generalized additive models) to test environment-related hypotheses of broad-scale vascular plant diversity gradients and to model and predict species richness and phylogenetic richness worldwide. To this end, we used 830 regional plant inventories including c. 300 000 species and predictors of past and present environmental conditions. Machine learning showed a superior performance, explaining up to 80.9% of species richness and 83.3% of phylogenetic richness, illustrating the great potential of such techniques for disentangling complex and interacting associations between the environment and plant diversity. Current climate and environmental heterogeneity emerged as the primary drivers, while past environmental conditions left only small but detectable imprints on plant diversity. Finally, we combined predictions from multiple modeling techniques (ensemble predictions) to reveal global patterns and centers of plant diversity at multiple resolutions down to 7774 km2 . Our predictive maps provide accurate estimates of global plant diversity available at grain sizes relevant for conservation and macroecology.

Functionally distinct tree species support long-term productivity in extreme environments.

Despite evidence of a positive effect of functional diversity on ecosystem productivity, the importance of functionally distinct species (i.e. species that display an original combination of traits) is poorly understood. To investigate how distinct species affect ecosystem productivity, we used a forest-gap model to simulate realistic temperate forest successions along an environmental gradient and measured ecosystem productivity at the end of the successional trajectories. We performed 10 560 simulations with different sets and numbers of species, bearing either distinct or indistinct functional traits, and compared them to random assemblages, to mimic the consequences of a regional loss of species. Long-term ecosystem productivity dropped when distinct species were lost first from the regional pool of species, under the harshest environmental conditions. On the contrary, productivity was more dependent on ordinary species in milder environments. Our findings show that species functional distinctiveness, integrating multiple trait dimensions, can capture species-specific effects on ecosystem productivity. In a context of an environmentally changing world, they highlight the need to investigate the role of distinct species in sustaining ecosystem processes, particularly in extreme environmental conditions.

The dimensionality and structure of species trait spaces.

Trait-based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade-off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.

What makes a weed a weed? A large-scale evaluation of arable weeds through a functional lens.

PREMISE OF THE STUDY: Despite long-term research efforts, a comprehensive perspective on the ecological and functional properties determining plant weediness is still lacking. We investigated here key functional attributes of arable weeds compared to non-weed plants, at large spatial scale. METHODS: We used an intensive survey of plant communities in cultivated and non-cultivated habitats to define a pool of plants occurring in arable fields (weeds) and one of plants occurring only in open non-arable habitats (non-weeds) in France. We compared the two pools based on nine functional traits and three functional spaces (LHS, reproductive and resource requirement hypervolumes). Within the weed pool, we quantified the trait variation of weeds along a continuum of specialization to arable fields. KEY RESULTS: Weeds were mostly therophytes and had higher specific leaf area, earlier and longer flowering, and higher affinity for nutrient-rich, sunny and dry environments compared to non-weeds, although functional spaces of weeds and non-weeds largely overlapped. When fidelity to arable fields increased, the spectrum of weed ecological strategies decreased as did the overlap with non-weeds, especially for the resource requirement hypervolume. CONCLUSIONS: Arable weeds constitute a delimited pool defined by a trait syndrome providing tolerance to the ecological filters of arable fields (notably, regular soil disturbances and fertilization). The identification of such a syndrome is of great interest to predict the weedy potential of newly established alien plants. An important reservoir of plants may also become weeds after changes in agricultural practices, considering the large overlap between weeds and non-weeds.