Biodiversity-based cropping systems: A long-term perspective is necessary.

Biodiversity-based cropping systems are an interesting option to address the many challenges that agriculture faces. However, benefits of these systems should not obscure the fact that creating biodiversity-based cropping systems represents a major change for farmers. To address this challenge, we argue that designing biodiversity-based cropping systems requires transforming ecological concepts into technical opportunities. Indeed, integrating ecological concepts such as plant-soil feedback and plant functional traits more strongly into cropping system design offers promising opportunities for the provision of ecosystem services, such as pest and disease control, crop production (including crop yield stability), climate regulation and regulation of soil quality. Accordingly, we demonstrate that designing biodiversity-based cropping systems requires considering not only the short term but also the long term. This would ensure that the expected ecosystem services have enough time to build up and provide their full effects, that the cropping systems are resilient and that they avoid the limitations of short-term assessments, which do not sufficiently consider multi-year effects. Considering long-term consequences of system change - induced by biodiversity - is essential to identify potential trade-offs between ecosystem services, as well as agricultural obstacles to and mechanisms of change. Including farmers and other food-chain actors in cropping system design would help find acceptable compromises that consider not only the provision of ecosystem services, but also other dimensions related to economic viability, workload or the technical feasibility of crops, which are identified as major obstacles to crop diversification. This strategy represents an exciting research front for the development of agroecological cropping systems.

A dataset for sustainability assessment of agroecological practices in a crop-livestock farming system.

This article presents data designed by European researchers who performed a literature review and interpreted the results to determine impact factors of many agroecological practices on a wide variety of sustainability indicators. The impact factors are represented in a matrix that connects practices to indicators. The indicators are related to environmental, economic and social sustainability of a typical European integrated crop-livestock farm. The data are included in the serious game SEGAE to learn agroecology, as described in "SEGAE: a serious game to learn agroecology" [1]. The data can be modified to adapt the game to other agricultural systems. Finally, the data can be re-used in research projects as a basis to assess impacts of agroecological practices.

Contribution of LCA to decision making: A scenario analysis in territorial agricultural production systems.

Territorial Life Cycle Assessment (TLCA) appears a promising method to support informed decision making of local actors in territorial agricultural production systems (TAPS), by assessing environmental impacts of agricultural activities and potential strategies. The objectives of this study were to i) adapt TLCA methodology to integrated environmental assessment of TAPS and ii) evaluate TLCA's contribution to supporting informed decision making by assessing scenarios of change in TAPS. A TLCA of the agricultural sector was performed for a territory in the Aube department in France, including main crops and animal production types from raw material extraction to the first stage of processing. Exchanges of agricultural products and by-products among agricultural subsectors were considered by allocating impacts, which prevented double-counting them. Two contrasting scenarios were assessed with TLCA - development of on-farm biogas production and reintroduction of sheep grazing - and compared to the current situation. Results were expressed per unit area (ha), per unit biomass produced (kg) and per percentage contribution to total impacts of the territory before and after processing (at and beyond the farm gate, respectively). The main contributors (cereal and oilseed crops) did not have the highest impact at the farm scale (per ha and per kg), which highlights that contribution to total impacts of the territory is a relevant addition to the impacts per functional unit. Consideration of exchanges showed that TLCA can be used to assess effects of material interactions (biomass flows) between sectors. Scenario results showed no significant differences in impacts, except for higher water resource depletion for the biogas scenario, because most differences between scenarios were smaller than uncertainties in the input data. Other challenges were identified, such as the need to evaluate consequences of changes beyond the territory gate when performing TLCA of scenarios or the utility of characterizing the network of biomass flows in more detail. In conclusion, the methodological framework that was developed successfully identified environmental hotspots and reflected environmental impacts of material interactions between actors. Finally, it can estimate environmental impacts of future strategies, as long as uncertainty is reduced; thus, it shows potential as a decision-support tool.

Survey data from 38 integrated crop-livestock farming systems in Western France.

This paper presents data collected from 38 integrated crop-livestock farming systems in Ille-et-Vilaine, Brittany, France, during face-to-face surveys. Surveys were conducted using a quantitative questionnaire to collect information about farm management practices that affect nitrogen (N) inputs, N outputs, and internal N flows. The data were used to develop new indicators of N efficiency (SyNE, System N Efficiency) and of N balance (SyNB, System N Balance), as described in "SyNE: An improved indicator to assess nitrogen efficiency of farming systems" [1]. Also, the data were used to test an online tool developed to calculate these indicators, as described in "A free online tool to calculate three nitrogen-related indicators for farming systems" [2]. The data are provided with this article.