Increasing crop heterogeneity enhances multitrophic diversity across agricultural regions.

Agricultural landscape homogenization has detrimental effects on biodiversity and key ecosystem services. Increasing agricultural landscape heterogeneity by increasing seminatural cover can help to mitigate biodiversity loss. However, the amount of seminatural cover is generally low and difficult to increase in many intensively managed agricultural landscapes. We hypothesized that increasing the heterogeneity of the crop mosaic itself (hereafter "crop heterogeneity") can also have positive effects on biodiversity. In 8 contrasting regions of Europe and North America, we selected 435 landscapes along independent gradients of crop diversity and mean field size. Within each landscape, we selected 3 sampling sites in 1, 2, or 3 crop types. We sampled 7 taxa (plants, bees, butterflies, hoverflies, carabids, spiders, and birds) and calculated a synthetic index of multitrophic diversity at the landscape level. Increasing crop heterogeneity was more beneficial for multitrophic diversity than increasing seminatural cover. For instance, the effect of decreasing mean field size from 5 to 2.8 ha was as strong as the effect of increasing seminatural cover from 0.5 to 11%. Decreasing mean field size benefited multitrophic diversity even in the absence of seminatural vegetation between fields. Increasing the number of crop types sampled had a positive effect on landscape-level multitrophic diversity. However, the effect of increasing crop diversity in the landscape surrounding fields sampled depended on the amount of seminatural cover. Our study provides large-scale, multitrophic, cross-regional evidence that increasing crop heterogeneity can be an effective way to increase biodiversity in agricultural landscapes without taking land out of agricultural production.

Is there an optimum scale for predicting bird species' distribution in agricultural landscapes?

Changes in forest cover in agricultural landscapes affect biodiversity. Its management needs some indications about scale to predict occurrence of populations and communities. In this study we considered a forest cover index to predict bird species and community patterns in agricultural landscapes in south-western France. We used generalized linear models for that purpose with prediction driven by wooded areas' spatial distribution at nine different radii. Using 1064 point counts, we modelled the distribution of 10 bird species whose habitat preferences are spread along a landscape opening gradient. We also modelled the distribution of species richness for farmland species and for forest species. We used satellite images to construct a 'wood/non-wood' map and calculated a forest index, considering the surface area of wooded areas at nine radii from 110m to 910m. The models' predictive quality was determined by the AUC (for predicted presences) and ρ (for predicted species richness) criteria. We found that the forest cover was a good predictor of the distribution of seven bird species in agricultural landscapes (mean AUC for the seven species = 0.74 for the radius 110m). Species richness of farmland and forest birds was satisfactorily predicted by the models (ρ = 0.55 and 0.49, respectively, for the radius 110m). The presence of the studied species and species richness metrics were better predicted at smaller scales (i.e. radii between 110 m and 310 m) within the range tested. These results have implications for bird population management in agricultural landscapes since better pinpointing the scale to predict species distributions will enhance targeting efforts to be made in terms of landscape management.

Contrasting spatial and temporal responses of bird communities to landscape changes.

Quantifying the impact of land-use changes on biodiversity is a major challenge in conservation ecology. Static spatial relationships between bird communities and agricultural landscapes have been extensively studied. Yet, their ability to mirror the effects of temporal land-use dynamics remains to be demonstrated. Here, we test whether such space-for-time substitution approaches are relevant for explaining temporal variations in farmland bird communities. We surveyed 256 bird communities in an agricultural landscape in southwest France at the same locations in 1982 and 2007, and quantified the same seven landscape descriptors for each period. We compared the effects of spatial and temporal landscape changes over this 25-year period on bird species distributions and three community-level metrics: species richness and two community indices reflecting birds' specialisation regarding local vegetation structure (local CSI) and landscape composition (landscape CSI). Landscape heterogeneity decreased between 1982 and 2007 and crop area increased sharply at the expense of grassland as a result of agricultural intensification. We found that the correlations between temporal changes in bird distributions or community metrics and landscape components were less consistent than their spatial relationships in each year. This result advocates caution when using a space-for-time substitution approach to assess the effects of landscape changes on biodiversity. Additionally, community metrics showed contrasted responses to landscape changes. Species richness and local CSI for each period were negatively related to the area of crops and positively related to landscape heterogeneity. Conversely, the landscape CSI was positively related to the area of crop and negatively to landscape heterogeneity. To understand the ecological processes linked to changes in farm landscapes, our study underlines the need to develop long-term studies with bird and habitat data collected during several periods, and particularly to consider multiple community indices in monitoring change.

Trait-independent habitat associations explain low co-occurrence in native and exotic birds on a tropical volcanic island.

On oceanic islands, strong human impacts on habitats, combined with introductions of exotic species, modify the composition of terrestrial bird assemblages and threaten their ecological functions. In La Réunion, an oceanic island located in the Madagascan region, a national park was established in 2007 to counter the ecosystem-level effects of three centuries of habitat conversion, native species destruction and exotic species introductions. Here, we investigated how bird assemblages were structured in these human-modified landscapes, 10 years before the national park set out its first conservation measures. We used a combination of multivariate statistics and generalized additive models to describe variations in the taxonomic and functional composition and diversity of 372 local bird assemblages, encompassing 20 species, along gradients of habitat composition and configuration. We found that native species were tied to native habitats while exotic species were associated with urban areas and man-modified landscape mosaics, with some overlap at mid-elevations. Species' trophic preferences were segregated along habitat gradients, but ecological traits had an overall weak role in explaining the composition of species assemblages. Hence, at the time of the survey, native and exotic species in La Réunion formed two spatially distinct species assemblages with contrasting ecological trait suites that benefited from antagonistic habitat compositions and dynamics. We conclude that our results support the analysis of historical data sets to establish reference points to monitor human impacts on insular ecosystems.

A real-world implementation of a nationwide, long-term monitoring program to assess the impact of agrochemicals and agricultural practices on biodiversity.

Biodiversity has undergone a major decline throughout recent decades, particularly in farmland. Agricultural practices are recognized to be an important pressure on farmland biodiversity, and pesticides are suspected to be one of the main causes of this decline in biodiversity. As part of the national plan for reduction of pesticides use (Ecophyto), the French ministry of agriculture launched the 500 ENI (nonintended effects) monitoring program in 2012 in order to assess the unintended effects of agricultural practices, including pesticide use, on biodiversity represented by several taxonomic groups of interest for farmers. This long-term program monitors the biodiversity of nontargeted species (earthworms, plants, coleoptera, and birds), together with a wide range of annual data on agricultural practices (crop rotation, soil tillage, weed control, fertilizers, chemical treatments, etc.). Other parameters (e.g., landscape and climatic characteristics) are also integrated as covariates during the analyses. This monitoring program is expected to improve our understanding of the relative contribution of the different drivers of population and community trends. Here, we present the experience of setting up the 500 ENI network for this ambitious and highly complex monitoring program, as well as the type of data it collects. The issue of data quality control and some first results are discussed. With the aim of being useful to readers who would like to set up similar monitoring schemes, we also address some questions that have arisen following the first five years of the implementation phase of the program.

Temporal Beta Diversity of Bird Assemblages in Agricultural Landscapes: Land Cover Change vs. Stochastic Processes.

Temporal variation in the composition of species assemblages could be the result of deterministic processes driven by environmental change and/or stochastic processes of colonization and local extinction. Here, we analyzed the relative roles of deterministic and stochastic processes on bird assemblages in an agricultural landscape of southwestern France. We first assessed the impact of land cover change that occurred between 1982 and 2007 on (i) the species composition (presence/absence) of bird assemblages and (ii) the spatial pattern of taxonomic beta diversity. We also compared the observed temporal change of bird assemblages with a null model accounting for the effect of stochastic dynamics on temporal beta diversity. Temporal assemblage dissimilarity was partitioned into two separate components, accounting for the replacement of species (i.e. turnover) and for the nested species losses (or gains) from one time to the other (i.e. nestedness-resultant dissimilarity), respectively. Neither the turnover nor the nestedness-resultant components of temporal variation were accurately explained by any of the measured variables accounting for land cover change (r(2)<0.06 in all cases). Additionally, the amount of spatial assemblage heterogeneity in the region did not significantly change between 1982 and 2007, and site-specific observed temporal dissimilarities were larger than null expectations in only 1% of sites for temporal turnover and 13% of sites for nestedness-resultant dissimilarity. Taken together, our results suggest that land cover change in this agricultural landscape had little impact on temporal beta diversity of bird assemblages. Although other unmeasured deterministic process could be driving the observed patterns, it is also possible that the observed changes in presence/absence species composition of local bird assemblages might be the consequence of stochastic processes in which species populations appeared and disappeared from specific localities in a random-like way. Our results might be case-specific, but if stochastic dynamics are generally dominant, the ability of correlative and mechanistic models to predict land cover change effects on species composition would be compromised.

Assessing community-level and single-species models predictions of species distributions and assemblage composition after 25 years of land cover change.

To predict the impact of environmental change on species distributions, it has been hypothesized that community-level models could give some benefits compared to species-level models. In this study we have assessed the performance of these two approaches. We surveyed 256 bird communities in an agricultural landscape in southwest France at the same locations in 1982 and 2007. We compared the ability of CQO (canonical quadratic ordination; a method of community-level GLM) and GLMs (generalized linear models) to i) explain species distributions in 1982 and ii) predict species distributions, community composition and species richness in 2007, after land cover change. Our results show that models accounting for shared patterns between species (CQO) slightly better explain the distribution of rare species than models that ignore them (GLMs). Conversely, the predictive performances were better for GLMs than for CQO. At the assemblage level, both CQO and GLMs overestimated species richness, compared with that actually observed in 2007, and projected community composition was only moderately similar to that observed in 2007. Species richness projections tended to be more accurate in sites where land cover change was more marked. In contrast, the composition projections tended to be less accurate in those sites. Both modelling approaches showed a similar but limited ability to predict species distribution and assemblage composition under conditions of land cover change. Our study supports the idea that our community-level model can improve understanding of rare species patterns but that species-level models can provide slightly more accurate predictions of species distributions. At the community level, the similar performance of both approaches for predicting patterns of assemblage variation suggests that species tend to respond individualistically or, alternatively, that our community model was unable to effectively account for the emergent community patterns.