John A. Finn

Ecosystem function enhanced by combining four functional types of plant species in intensively managed grassland mixtures: a 3‐year continental‐scale field experiment

1.A coordinated continental-scale field experiment across 31 sites was used to compare the biomass yield of monocultures and four species mixtures associated with intensively managed agricultural grassland systems. To increase complementarity in resource use, each of the four species in the experimental design represented a distinct functional type derived from two levels of each of two functional traits, nitrogen acquisition (N2-fixing legume or nonfixing grass) crossed with temporal development (fast-establishing or temporally persistent). Relative abundances of the four functional types in mixtures were systematically varied at sowing to vary the evenness of the same four species in mixture communities at each site and sown at two levels of seed density. 2.Across multiple years, the total yield (including weed biomass) of the mixtures exceeded that of the average monoculture in >97% of comparisons. It also exceeded that of the best monoculture (transgressive overyielding) in about 60% of sites, with a mean yield ratio of mixture to best-performing monoculture of 1·07 across all sites. Analyses based on yield of sown species only (excluding weed biomass) demonstrated considerably greater transgressive overyielding (significant at about 70% of sites, ratio of mixture to best-performing monoculture = 1·18). 3.Mixtures maintained a resistance to weed invasion over at least 3 years. In mixtures, median values indicate

Diversity–interaction modeling: estimating contributions of species identities and interactions to ecosystem function

We develop a modeling framework that estimates the effects of species identity and diversity on ecosystem function and permits prediction of the diversity-function relationship across different types of community composition. Rather than just measure an overall effect of diversity, we separately estimate the contributions of different species interactions. This is especially important when both positive and negative interactions occur or where there are patterns in the interactions. Based on different biological assumptions, we can test for different patterns of interaction that correspond to the roles of evenness, functional groups, and functional redundancy. These more parsimonious descriptions can be especially useful in identifying general diversity-function relationships in communities with large numbers of species. We provide an example of the application of the modeling framework. These models describe community-level performance and thus do not require separate measurement of the performance of individual species. This flexible modeling approach can be tailored to test many hypotheses in biodiversity research and can suggest the interaction mechanisms that may be acting.

Ex post environmental evaluation of agri-environment schemes using experts' judgements and multicriteria analysis

Assessing the environmental impact of agri-environment schemes (AESs) is complicated by the lack of both specific measurable objectives and dedicated environmental monitoring of the impacts. A methodology to estimate the environmental performance of AESs was applied in nine EU case study areas, and reduced the complexity of scheme structure into elements that were assessed by experts. Multi-criteria analysis (MCA) techniques helped produce aggregated judgements about single objectives or measures. Expert panels assessed the link between environmental measures and objectives by scoring specific criteria that reflect important factors for delivering environmental effectiveness: valid research models for measures (cause-and-effect); quality of implementation by farmers and institutions; extent of participation and degree of spatial targeting. Multi-criteria analysis enabled comparison of the degree to which environmental effectiveness (estimated from the criteria scores) within a scheme was achieved across environmental objectives of different importance. There were considerable differences in overall environmental performance across different case study areas, and the experts’ scores identified scope for improvement in one or more criteria in most measures. Higher priority environmental objectives (as assessed by stakeholders) did not necessarily demonstrate highest environmental performance. We discuss implications for learning how to improve the design and evaluation of AESs.

Current use of impact models for agri-environment schemes and potential for improvements of policy design and assessment.

Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES.

The functioning of European grassland ecosystems: Potential benefits of biodiversity to agriculture

About half the farmland of Europe is grassland pasture or hay meadow, and much is impoverished in plant species due to the addition of fertilizers and pesticides, agricultural re-sowing, habitat fragmentation, land abandonment and changes in grazing and mowing regimes. Given this widespread reduction, it is important to understand the effect that loss of biodiversity is having upon our wider environment. Here the authors summarize the main results from the BIODEPTH project, the first multinational, large-scale experiment to examine directly the relationship between plant diversity and the processes that determine the functioning of ecosystems. The results suggest that preserving and restoring grassland diversity may be beneficial to maintaining desirable levels of several ecosystem processes, and may therefore have applications in land management and agriculture.

An improved model to predict the effects of changing biodiversity levels on ecosystem function

Summary 1. The development of models of the relationship between biodiversity and ecosystem function (BEF) has advanced rapidly over the last 20 years, incorporating insights gained through extensive experimental work. We propose Generalised Diversity-Interactions models that include many of the features of existing models and have several novel features. Generalised Diversity-Interactions models characterise the contribution of two species to ecosystem function as being proportional to the product of their relative abundances raised to the power of a coefficient h. 2. A value of h < 1 corresponds to a stronger than expected contribution of species’ pairs to ecosystem functioning, particularly at low relative abundance of species. 3. Varying the value of h has profound consequences for community-level properties of BEF relationships, including: (i) saturation properties of the BEF relationship; (ii) the stability of ecosystem function across communities; (iii) the likelihood of transgressive overyielding. 4. For low values of h, loss of species can have a much greater impact on ecosystem functioning than loss of community evenness. 5. Generalised Diversity-Interactions models serve to unify the modelling of BEF relationships as they include several other current models as special cases. 6. Generalised Diversity-Interactions models were applied to seven data sets and three functions: total biomass (five grassland experiments), community respiration (one bacterial experiment) and nitrate leaching (one earthworm experiment). They described all the nonrandom structure in the data in six experiments, and most of it in the seventh experiment and so fit as well or better than competing BEF models for these data. They were significantly better than Diversity-Interactions models in five experiments. 7. Synthesis. We show that Generalized Diversity-Interactions models quantitatively integrate several methods that separately address effects of species richness, evenness and composition on ecosystem function. They describe empirical data at least as well as alternative models and improve the ability to quantitatively test among several theoretical and practical hypotheses about the effects of

Phylogenetically diverse grasslands are associated with pairwise interspecific processes that increase biomass

Biodiversity is an important determinant of primary productivity in experimental ecosystems. We combine two streams of research on understanding the effects of biodiversity on ecosystem function: quantifying phylogenetic diversity as a predictor of biodiversity effects in species-rich systems and the contribution of pairwise interspecific interactions to ecosystem function. We developed a statistical model that partitions the effect of biodiversity into effects due to community phylogenetic diversity and other community properties (e.g., average pairwise interaction, between- and within-functional-group effects, and so forth). The model provides phylogenetically based species-level explanations of differences in ecosystem response for communities with differing species composition. In two well-known grassland experiments, the model approach provides a parsimonious description of the effects of diversity as being due to the joint effect of the average pairwise statistical interaction and to community phylogenetic diversity. Effects associated with functional groupings of species in communities are largely explained by community phylogenetic diversity. The model approach quantifies a direct link between a measure of the evolutionary diversity of species and their interactive contribution to ecosystem function. It proves a useful tool in developing a mechanistic understanding of variation in ecosystem function.

Lethal and sub‐lethal effects of ivermectin on north temperate dung beetles, Aphodius ater and Aphodius rufipes (Coleoptera: Scarabaeidae)

Abstract.  1. Ivermectin is an anthelmintic veterinary medicine, and is excreted in the dung of treated livestock in a mainly unmetabolised form. Ivermectin is known to have toxic effects on dung beetles, but most studies to date have been conducted on tropical and sub‐tropical species. Relatively few laboratory studies have focused on the specific effects of ivermectin on survival and development of north temperate dung beetles.

Benefits of sward diversity for agricultural grasslands

Abstract A pan-European experiment carried out at 28 sites across Europe showed strong benefits of sward diversity in agricultural grasslands. We systematically varied the relative abundance of four agronomic plant species (sown species evenness), and found that 4-species mixtures yielded more forage than could be expected on the basis of the monoculture yields. Mixtures generally yielded more than even the best performing monoculture (transgressive overyielding). Mixtures strongly reduced the incidence of unsown species in the sward. These diversity effects were consistent over the wide range of environmental conditions and persisted over three harvest years and in highly fertilized conditions. These results indicate a strong potential for agronomic mixtures to contribute to more sustainable agricultural systems. Agronomic diversity can improve forage yield and reduce weed invasion in intensively managed grasslands, and may also enhance the provision of other ecosystem services.

A review of evidence on the environmental impact of Ireland’s Rural Environment Protection Scheme (REPS)

Received 19 October 2009. Accepted 28 February 2011. Published 29 March 2012. Since its inception in 1994, there has been strong demand for evidence of the environmental effectiveness of the Rural Environment Protection Scheme (REPS), which has paid farmers in the Republic of Ireland over €3 billion up to 2010. A variety of research projects have been undertaken that investigate the environmental effects of REPS through an examination of either specific environmental measures or specific geographical areas. A review of available publications has confirmed the absence of a comprehensive, national-scale study of the environmental impacts of REPS. For this reason, there is insufficient evidence with which to judge the environmental effectiveness of the national-scale implementation of the whole scheme. For some specific meas ures, however, sufficient evidence is available to inform an objective assessment in some cases, and to help learn how to improve environmental effectiveness in most cases. The majority of the REPS payments are now dedicated to biodiversity objectives. Thus, biodiversity measures and options should be a priority for any national-scale environmental assessment of the scheme. Such a study would help identify the environmental benefits of REPS, the specific elements of REPS that are performing adequately, and those elements that are in need of improvement. Given the considerable overlap between REPS measures and options and those included in the 2010 Agri Environment Options Scheme (AEOS), the assessment of REPS measures could also be used to inform the likely environmental performance of the AEOS.