Including community composition in biodiversity–productivity models

Studies on biodiversity and ecosystem functioning (BEF) have elicited debate over the interpretation of the positive relationship between species richness and plant productivity. Manipulating richness cannot be achieved without affecting composition; it is thus essential to consider the latter in statistical models.We firstly review existing approaches that use species richness as an explanatory variable and propose modifications to improve their performance. We use an original data set to illustrate the analyses. The classical method where composition is coded as a factor with a level for each different species mixture can be improved by defining the levels using clustering. Methods based on ordinations reduce the dimensionality of plant composition and use the new coordinates as fixed effects; they provide a much better fit to our observations.Secondly, we develop a new method where composition is included as a similarity matrix affecting the residual variance–covariance. Similarity in composition between plots is treated in the same way as shared evolutionary history between species in phylogenetic regression. We find that it outperforms the other models.We discuss the different approaches and suggest that our method is particularly suited for observational studies or for manipulative studies where plant diversity is not kept constant by weeding. By treating species composition in an intuitive and sensible way, it offers a valuable and powerful complement to existing models

The relative contributions of species richness and species composition to ecosystem functioning

How species diversity influences ecosystem functioning has been the subject of many experiments and remains a key question for ecology and conservation biology. However, the fact that diversity cannot be manipulated without affecting species composition makes this quest methodologically challenging. Here, we evaluate the relative importance of diversity and of composition on biomass production, by using partial Mantel tests for one variable while controlling for the other. We analyse two datasets, from the Jena (2002–2008) and the Grandcour (2008–2009) Experiments. In both experiments, plots were sown with different numbers of species to unravel mechanisms underlying the relationship between biodiversity and ecosystem functioning (BEF). Contrary to Jena, plots were neither mowed nor weeded in Grandcour, allowing external species to establish. Based on the diversity–ecosystem functioning and competition theories, we tested two predictions: 1) the contribution of composition should increase with time; 2) the contribution of composition should be more important in non-weeded than in controlled systems. We found support for the second hypothesis, but not for the first. On the contrary, the contribution of species richness became markedly more important few years after the start of the Jena Experiment. This result can be interpreted as suggesting that species complementarity, rather than intraspecific competition, is the driving force in this system. Finally, we explored to what extent the estimated relative importance of both factors varied when measured on different spatial scales of the experiment (in this case, increasing the number of plots included in the analyses). We found a strong effect of scale, suggesting that comparisons between studies, and more generally the extrapolation of results from experiments to natural situations, should be made with caution

Understanding negative biodiversity–ecosystem functioning relationship in semi-natural wildflower strips

Studies on biodiversity–ecosystem functioning (BEF) in highly controlled experiments often yield results incompatible with observations from natural systems: experimental results often reveal positive relationships between diversity and productivity, while for natural systems, zero or even negative relationships have been reported. The discrepancy may arise due to a limited or closed local species pool in experiments, while natural systems in meta-community contexts experience dynamic processes, i.e., colonization and extinctions. In our study, we analysed plant community properties and above-ground biomass within a semi-natural (i.e., not weeded) experiment in an agricultural landscape. Eleven replicates with four different diversity levels were created from a species pool of 20 wildflower species. We found an overall significant negative relationship between total diversity and productivity. This relationship likely resulted from invasion resistance: in plots sown with low species numbers, we observed colonization by low-performing species; colonization increased species richness but did not contribute substantially to productivity. Interestingly, when analysing the biomass of the sown and the colonizer species separately, we observed in both cases positive BEF relationships, while this relationship was negative for the whole system. A structural equation modelling approach revealed that higher biomass of the sown species was linked to higher species richness, while the positive BEF relationship of the colonizers was indirect and constrained by the sown species biomass. Our results suggest that, in semi-natural conditions common in extensive agroecosystems, the negative BEF relationship results from the interplay between local dominant species and colonization from the regional species pool by subordinate species

Diversity protects plant communities against generalist molluscan herbivores

Wildflower strips are used to increase natural enemies of crop pests and to conserve insect diversity on farmland. Mollusks, especially slugs, can affect the vegetation development in these strips considerably. Although recent theoretical work suggests that more diverse plant communities will exhibit greater resistance against herbivore pressure, empirical studies are scarce. We conducted a semi-natural experiment in wildflower strips, manipulating trophic structure (reduction in herbivorous mollusks and reduction in major predators) and plant diversity (2, 6, 12, 20 and 24 sown species). This design allowed us to assess the effect of plant diversity, biomass and composition on mollusks, and vice versa, the effect of mollusc abundance on vegetation. Seven species of mollusks were found in the strips, with the slugs Arion lusitanicus, Deroceras reticulatum and Deroceras panormitanum being most frequent. We found a negative relationship between plant diversity and mollusk abundance, which was due predominantly to a decrease in the agricultural pest species A. lusitanicus. These results are consistent with the hypothesis that plant diversity can reduce the impact of herbivores. However, plant identity also had an effect on mollusks, and accounted for a much larger fraction of the variation in mollusk communities than biodiversity effects. While overall plant diversity decreased during the 3 years of the study, in the final year the highest plant diversity was found in the plots where mollusk populations were experimentally reduced. We conclude that selective feeding by generalist herbivores leads to changes in plant community composition and hence reduced plant diversity. Our results highlight the importance of plant biodiversity as protection against generalist herbivores, which if abundant can in the long term negatively impact plant diversity, driving the system along a “low plant diversity – high mollusk abundance” trajectory

Plant diversity in a nutshell: testing for small-scale effects on trap nesting wild bees and wasps

Declining plant species richness in agro-ecosystems and thus reduced habitat quality can have cascading effects on ecosystem functioning, leading to reduced pollination and biological control. Here we test if plant diversity can affect arthropod diversity and abundance on a very small scale, manipulating plant species richness (2, 6, 12 and 20 sown species) in small adjacent subplots (6 × 9 m) in 10 wildflower strips in an agricultural landscape. We simultaneously analyzed the effect of plant species richness, vegetation structure, and plant composition on the species richness and abundance of cavity-nesting wild bees, wasps, their prey and natural enemies, and on the structure of their food webs. By separating the trap-nesting species into functional groups according to their prey, we aimed to understand the underlying patterns for the effects of plant diversity. Increasing plant species richness had a significant effect only on spider-predating wasps, the group of wasps trophically most distant from plants. In contrast, bees and food-web structure were unaffected by plant diversity. Spider-predating wasp abundance negatively correlated with the abundance of spiders, suggesting top-down control. Interestingly, the abundance of spiders was the only variable that was strongly affected by plant composition. The hypothesis that the effect of plant diversity decreases with increasing trophic level is not supported by our study, and the mobility of species appears to play a greater role at this small spatial scale

A landscape-scale assessment of the relationship between grassland functioning, community diversity, and functional traits

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity–productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity–insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape-scale. Here, we provide a landscape-scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape-scale grassland productivity

Including community composition in biodiversity-productivity models

Studies on biodiversity and ecosystem functioning (BEF) have elicited debate over the interpretation of the positive relationship between species richness and plant productivity. Manipulating richness cannot be achieved without affecting composition; it is thus essential to consider the latter in statistical models. We firstly review existing approaches that use species richness as an explanatory variable and propose modifications to improve their performance. We use an original data set to illustrate the analyses. The classical method where composition is coded as a factor with a level for each different species mixture can be improved by defining the levels using clustering. Methods based on ordinations reduce the dimensionality of plant composition and use the new coordinates as fixed effects; they provide a much better fit to our observations. Secondly, we develop a new method where composition is included as a similarity matrix affecting the residual variance-covariance. Similarity in composition between plots is treated in the same way as shared evolutionary history between species in phylogenetic regression. We find that it outperforms the other models. We discuss the different approaches and suggest that our method is particularly suited for observational studies or for manipulative studies where plant diversity is not kept constant by weeding. By treating species composition in an intuitive and sensible way, it offers a valuable and powerful complement to existing models. © 2014 British Ecological Society.BEF; Biodiversity; Composition; Ecosystem function; Ecosystem services;Mixed effects models; Residual correlation structure; Species richnessPeer Reviewe

Direct and indirect bottom-up and top-down forces shape the abundance of the orb-web spider Argiope bruennichi

Species abundance in local communities is determined by bottom-up and top-down processes, which can act directly and indirectly on the focal species. Studies examining these effects simultaneously are rare. Here we explore the direct top-down and direct and indirect bottom-up forces regulating the abundance and predation success of an intermediate predator, the web- building spider Argiope bruennichi (Araneae: Araneidae). We manipulated plant diversity (2, 6, 12 or 20 sown species) in 9 wildflower strips in a region of intensive farmland. To identify the major factors regulating the distribution and abundance of A. bruennichi, we quantified three characteristics of vegetation (species diversity, composition and vegetation structure) as well as the spider’s prey community and natural enemies. The distribution and abundance of A. bruennichi was regulated by combined bottom-up and top-down processes as well as by direct and indirect interactions between trophic levels. Four main factors were identified: (1) the strong direct effect of vegetation structure, (2) the positive effect of plant species diversity, which affected spider abundance directly and indirectly through increased densities and size of flower-visiting prey species, (3) the positive or negative direct effects of different plant species, and (4) the strongly negative direct effect of predacious hornets. The advantage of taking a global approach to understand the regulation of species abundance is highlighted first by the quantification of the relative importance of factors, with a surprisingly strong effect of hornet predators, and second by the discovery of a direct effect of plant diversity, which raises intriguing questions about habitat selection by this spider

Data from: Including community composition in biodiversity-productivity models

1. Studies on biodiversity and ecosystem functioning (BEF) have elicited debate over the interpretation of the positive relationship between species richness and plant productivity. Manipulating richness cannot be achieved without affecting composition; it is thus essential to consider the latter in statistical models. 2. We firstly review existing approaches that use species richness as an explanatory variable and propose modifications to improve their performance. We use an original dataset to illustrate the analyses. The classical method where composition is coded as a factor with a level for each different species mixture can be improved by defining the levels using clustering. Methods based on ordinations reduce the dimensionality of plant composition and use the new coordinates as fixed effects; they provide a much better fit to our observations. 3. Secondly, we develop a new method where composition is included as a similarity matrix affecting the residual variance-covariance. Similarity in composition between plots is treated in the same way as shared evolutionary history between species in phylogenetic regression. We find that it outperforms the other models. 4. We discuss the different approaches and suggest that our method is particularly suited for observational studies or for manipulative studies where plant diversity is not kept constant by weeding. By treating species composition in an intuitive and sensible way, it offers a valuable and powerful complement to existing models