Biodiversity indicators in organic and conventional farming systems: main results from the European project BIOBIO

In the framework of the European project BIOBIO, we compared between countries habitat and cumulated species richnesses of plants, wild bees, spiders and earthworms, measured in 169 conventional and organic farms belonging to 10 case studies in 10 European countries. For the French case study (Gascony Valleys and Hills), correlations between direct (habitat and taxonomic richnesses) and indirect (agricultural practices) indicators of biodiversity within 8 conventional and 8 organic farms, were calculated. Results showed that the main driver of biodiversity at the farm level was the number of cultivated and above all semi-natural habitats, inthe French case study region as well as inthe other regions. This factor partially explained the highest biodiversity level of the French case study region. However, farming practices, specific or not to the organic and conventional systems, most often drove biodiversity parameters at the habitat level. In fine, the project proposed the BIOBIO method for monitoring biodiversity in farms

GrassPlot v. 2.00 – first update on the database of multi-scale plant diversity in Palaearctic grasslands

Abstract: GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). Following a previous Long Database Report (Dengler et al. 2018, Phyto- coenologia 48, 331–347), we provide here the first update on content and functionality of GrassPlot. The current version (GrassPlot v. 2.00) contains a total of 190,673 plots of different grain sizes across 28,171 independent plots, with 4,654 nested-plot series including at least four grain sizes. The database has improved its content as well as its functionality, including addition and harmonization of header data (land use, information on nestedness, structure and ecology) and preparation of species composition data. Currently, GrassPlot data are intensively used for broad-scale analyses of different aspects of alpha and beta diversity in grassland ecosystems

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe

Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non‐crop habitats, and species’ dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7‐ and 1.4‐fold respectively. Arable‐dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield‐enhancing ecosystem services

CropPol: a dynamic, open and global database on crop pollination

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry weight, number of fruits and kg per hectare, among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), Northern America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-05 (21 studies), 2006-10 (40), 2011-15 (88), and 2016-20 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA). This article is protected by copyright. All rights reserved

Biodiversity in organic and low-input farming systems. Handbook for recording key indicators

This Handbook describes the methods required to measure the direct and indirect indicators of biodiversity in the field or through farmer interviews on organic, low-input and conventional (control) farms during 2010. It is the result of editing and revision of the BIOBIO deliverable D2.2. A total of twelve Case Study regions were selected in eleven countries. A standard habitat mapping procedure for the European scale based on General Habitat Categories (GHCs) was applied. This method has been adapted further to deal with the assessment of organic/low-input farm holdings. An initial classification of farmed and non-farmed land has been used to direct the selection of the samples. After mapping the farm area, in each habitat type selected for flora and fauna surveys, all species indicators were sampled for vegetation, earthworms, bees and spiders. Farm practices and genetic diversity were measured through interviews with the farmer. A digitising protocol was provided to prepare all data for analysis. The practicality and suitability of these methods for sampling plants and selected animals on very different farm types and habitats was evaluated. Lessons learned are described shortly after each chapter indicating difficulties encountered during the field work and giving practical suggestions. Further reports will be available in due course presenting the implication of analyses and results. The cost efficiency of the methodology was measured through reports on input of staff time and material

Estimating the cost of different strategies for measuring farmland biodiversity: Evidence from a Europe-wide field evaluation

Fourty percent of the EU land area is currently considered to be agriculturally managed, and there is growing attention to the environmental performance of farming practices. This involves the need for farm-scale monitoring programmes for sustainability, but their implementation is hampered by a number of difficulties such as the identification of indicators for different latitudes and environments and the evaluation of the effectiveness and costs of different monitoring approaches. In this paper, we focus on the costs of farm-scale biodiversity monitoring, presenting results from a Europe-wide cost data collection in the EU FP7 BioBio Project. Firstly, we propose an analytical assessment of resources consumed by the research units and a cost estimation for the measurement of six biodiversity-related parameters: habitat mapping, vegetation, wild bees and bumblebees, spiders, earthworms and a farm management questionnaire. Thereafter, we estimate a standardised cost for an ordinary measurement of the six parameters at farm-scale. In doing so, we highlight the cost differences between three strategies involving different potential actors (professional agencies, farmers, volunteers). This analysis shows that producing reliable data on monitoring costs requires a large sample pool of farms and farming systems as was the case in the BioBio project. The cost standardisation allows us to estimate the cost range between the different strategies ranging between €2700 and €8200 per far