26 research outputs found

    What does Life-Cycle Assessment of agricultural products need for more meaningful inclusion of biodiversity?

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    peer-reviewedDecision‐makers increasingly use life‐cycle assessment (LCA) as a tool to measure the environmental sustainability of products. LCA is of particular importance in globalized agricultural supply chains, which have environmental effects in multiple and spatially dispersed locations. Incorporation of impacts on biodiversity that arise from agricultural production systems into environmental assessment methods is an emerging area of work in LCA, and current approaches have limitations, including the need for (i) improved assessment of impacts to biodiversity associated with agricultural production, (ii) inclusion of new biodiversity indicators (e.g. conservation value, functional diversity, ecosystem services) and (iii) inclusion of previously unaccounted modelling variables that go beyond land‐use impacts (e.g. climate change, water and soil quality). Synthesis and applications. Ecological models and understanding can contribute to address the limitations of current life‐cycle assessment (LCA) methods in agricultural production systems and to make them more ecologically relevant. This will be necessary to ensure that biodiversity is not neglected in decision‐making that relies on LCA

    Concilier production agricole et biodiversité : le rôle de l’intensité et de son allocation spatiale

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    During the past several decades, agricultural intensification has been crucial to increase the food supply. Several processes related to intensification are very detrimental to the environment, particularly biodiversity. Today, agriculture is facing the challenge of satisfying its demand for food while improving its environmental sustainability. Knowledge of the shape of the relationship between biodiversity and intensity is necessary to determine both where conservation policies will be most effective and how to allocate intensity to reconcile production and biodiversity. Few empirical studies on this relationship exist, and the influence of the spatial arrangement of intensity on biodiversity remains untested. This Ph.D. thesis determined how to target both agricultural intensity and its spatial allocation for meeting production and conservation objectives of farmlands. To answer this research question, we used a country-scaled approach that combined two France-scaled databases that describe agriculture and farmland birds. We characterized a nationwide gradient of agricultural intensity and studied a farmland bird community along this gradient, using several trait-based descriptors (specialization, trophic level, and species main habitat). Agricultural intensity and bird communities were described at the Small Agricultural Region (SAR; mean width = 22.4 km) level. As a first step, we developed a novel method to estimate an intensity indicator that was based on Input Costs/ha, with SAR resolution. This indicator provides a continuous intensity measure that is relevant across different types of agricultural systems. Secondly, we investigated the effects of a gradient of land uses (grassland to arable land) and its heterogeneity on the bird community. We found habitat specialists suffered from habitat loss, while generalists benefited from heterogeneity. Thirdly, we showed that the community responded significantly to intensity, with winner species replacing loser species along the gradient. The shift between losers and winners was sharper at low intensities. Interestingly, spatial aggregation of intensity had a strengthening effect on the bird community. Finally, the relationships linking intensity to the bird community, food production, and economic performance were integrated into a model aimed at optimizing intensity allocation. Optimal allocations reached win-no-lose solutions with the three criteria. They corresponded to targeted intensity modifications: many small changed, favoring homogeneous, extensive clusters, were optimal within an extensification scenario; while a few large changes, favoring heterogeneity, were optimal within an intensification scenario. We provide one of the first studies demonstrating that spatial aggregation of intensity can influence the biodiversity/intensity relationship. Our results also provide an opportunity to improve the effectiveness of conservation policies, at national scales, with spatial targeting: opposite targeting should be performed either to maximize biodiversity benefits or to increase production, while mitigating biodiversity impacts. Our results highlight the importance of mixed allocation strategies between land sparing/sharing extremes. In order to put these opportunities into effect, further research should address the technical solutions that achieve intensity modification at the farm level and design targeted policies that benefit biodiversity and other environmental criteriaL'intensification de l'agriculture a joué un rôle crucial pour augmenter la production alimentaire au cours des dernières décennies. Plusieurs processus liés à l'intensification ont aussi causé d'importants dommages environnementaux, sur la biodiversité en particulier. L'agriculture doit aujourd'hui faire face au défi de satisfaire à une demande alimentaire croissante tout en améliorant son impact environnemental et sa durabilité. Il est nécessaire de connaître la forme de la relation entre biodiversité et intensité agricole pour déterminer où les politiques de conservation seront les plus efficaces et quelles allocations spatiales de l'intensité permettront de concilier production et biodiversité. Il existe peu de preuves empiriques de la forme de cette relation, de plus, l'influence de l'arrangement spatial de l'intensité sur la biodiversité demeure inconnue. Cette thèse avait pour objectif de déterminer comment cibler l'intensité agricole et son allocation spatiale afin d'atteindre des objectifs à la fois productifs et environnementaux. Afin de répondre à cette question, nous avons adopté une approche à l'échelle de la France entière, en couplant des bases de données décrivant l'agriculture et des oiseaux spécialistes des milieux agricoles à cette échelle. Nous avons caractérisé un gradient d'intensité à l'échelle du pays et étudié une communauté d'oiseaux spécialistes des milieux agricoles tout au long de ce gradient. Plusieurs descripteurs de cette communauté ont été utilisés, renseignant sa taille (richesse spécifique) mais aussi sa composition (spécialisation, niveau trophique, habitat). L'intensité agricole et les communautés d'oiseaux ont été reliées au niveau de la Petite Région Agricole (PRA; largeur moyenne = 22.4 km). Tout d'abord, nous avons développé une méthode permettant d'estimer un indicateur d'intensité agricole basé sur le coût intrant par hectare, au niveau de la PRA. Cet indicateur fournit une valeur d'intensité continue, pertinente à la fois pour les systèmes d'élevage et de culture. Ensuite, nous avons examiné les effets d'un gradient d'utilisation des sols (des prairies aux grandes cultures) et de leur hétérogénéité, sur la communauté d'oiseaux. L'hétérogénéité a un effet négatif sur les espèces spécialistes car elle entraine la perte de leur habitat. En revanche, elle avantage les espèces généralistes. Lors d'une troisième étape, nous avons montré que la communauté d'oiseaux était significativement influencée par l'intensité. Le long du gradient des espèces « gagnantes » remplacent des espèces « perdantes », ce changement étant plus marqué aux faibles intensités. L'effet de l'intensité sur la communauté d'oiseaux est renforcé par son agrégation spatiale. Enfin, les relations entre l'intensité, la communauté d'oiseaux, et les performances productives et économiques ont été intégrées dans un modèle d'optimisation de l'allocation de l'intensité. Les allocations optimales révèlent des solutions gagnant-non-perdant entre les trois critères de performance (biodiversité, production et économie). Ces allocations optimales correspondent à des modifications d'intensité ciblées: beaucoup de petits changements, favorisant des zones homogènes et extensives dans le cas d'un scénario d'extensification, à l'opposé de changements importants et moins nombreux, favorisant plus d'hétérogénéité, dans le cas d'un scénario d'intensification. Cette thèse apporte une des premières démonstrations de l'influence de l'agrégation spatiale de l'intensité sur la relation entre biodiversité et intensité. Nos résultats révèlent une opportunité pour améliorer l'efficacité des politiques de conservation de la biodiversité à l'échelle nationale. Il s'agit d'un ciblage de ces politiques, qui devra être différent pour maximiser la biodiversité à coût productif réduit ou pour augmenter la production tout en limitant les dommages sur la biodiversit

    The Response of Farmland Bird Communities to Agricultural Intensity as Influenced by Its Spatial Aggregation

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    International audienceThe shape of the relationship between biodiversity and agricultural intensity determines the range of intensities that should be targeted by conservation policies to obtain the greatest environmental benefits. Although preliminary evidence of this relationship exists, the influence of the spatial arrangement of intensity on biodiversity remains untested. We conducted a nationwide study linking agricultural intensity and its spatial arrangement to a farmland bird community of 22 species. Intensity was described with a continuous indicator based on Input Cost per hectare, which was relevant for both livestock and crop production. We used the French Breeding Bird Survey to compute several descriptors of the farmland bird community along the intensity gradient and tested for the significance of an interaction effect between intensity and its spatial aggregation on these descriptors. We found that the bird community was comprised of both winner and loser species with regard to intensity. The community composition descriptors (trophic level, specialisation, and specialisation for grassland indices) displayed non-linear relationships to intensity, with steeper slopes in the lower intensity range. We found a significant interaction effect between intensity and its spatial aggregation on the grassland specialisation index of the bird community; the effect of agricultural intensity was strengthened by its spatial aggregation. We suggest that an opportunity to improve the effectiveness of conservation policies exists by targeting measures in areas where intensity is moderate to low and aggregated. The effect of the aggre-gation of agricultural intensity on biodiversity should be considered in other scales and taxa when developing optimal policy targeting and intensity allocation strategies

    Concilier production agricole et biodiversité (le rôle de l intensité et de son allocation spatiale)

    No full text
    L'intensification de l'agriculture a joué un rôle crucial pour augmenter la production alimentaire au cours des dernières décennies. Plusieurs processus liés à l'intensification ont aussi causé d'importants dommages environnementaux, sur la biodiversité en particulier. L'agriculture doit aujourd'hui faire face au défi de satisfaire à une demande alimentaire croissante tout en améliorant son impact environnemental et sa durabilité. Il est nécessaire de connaître la forme de la relation entre biodiversité et intensité agricole pour déterminer où les politiques de conservation seront les plus efficaces et quelles allocations spatiales de l'intensité permettront de concilier production et biodiversité. Il existe peu de preuves empiriques de la forme de cette relation, de plus, l'influence de l'arrangement spatial de l'intensité sur la biodiversité demeure inconnue. Cette thèse avait pour objectif de déterminer comment cibler l'intensité agricole et son allocation spatiale afin d'atteindre des objectifs à la fois productifs et environnementaux. Afin de répondre à cette question, nous avons adopté une approche à l'échelle de la France entière, en couplant des bases de données décrivant l'agriculture et des oiseaux spécialistes des milieux agricoles à cette échelle. Nous avons caractérisé un gradient d'intensité à l'échelle du pays et étudié une communauté d'oiseaux spécialistes des milieux agricoles tout au long de ce gradient. Plusieurs descripteurs de cette communauté ont été utilisés, renseignant sa taille (richesse spécifique) mais aussi sa composition (spécialisation, niveau trophique, habitat). L'intensité agricole et les communautés d'oiseaux ont été reliées au niveau de la Petite Région Agricole (PRA; largeur moyenne = 22.4 km). Tout d'abord, nous avons développé une méthode permettant d'estimer un indicateur d'intensité agricole basé sur le coût intrant par hectare, au niveau de la PRA. Cet indicateur fournit une valeur d'intensité continue, pertinente à la fois pour les systèmes d'élevage et de culture. Ensuite, nous avons examiné les effets d'un gradient d'utilisation des sols (des prairies aux grandes cultures) et de leur hétérogénéité, sur la communauté d'oiseaux. L'hétérogénéité a un effet négatif sur les espèces spécialistes car elle entraine la perte de leur habitat. En revanche, elle avantage les espèces généralistes. Lors d'une troisième étape, nous avons montré que la communauté d'oiseaux était significativement influencée par l'intensité. Le long du gradient des espèces gagnantes remplacent des espèces perdantes , ce changement étant plus marqué aux faibles intensités. L'effet de l'intensité sur la communauté d'oiseaux est renforcé par son agrégation spatiale. Enfin, les relations entre l'intensité, la communauté d'oiseaux, et les performances productives et économiques ont été intégrées dans un modèle d'optimisation de l'allocation de l'intensité. Les allocations optimales révèlent des solutions gagnant-non-perdant entre les trois critères de performance (biodiversité, production et économie). Ces allocations optimales correspondent à des modifications d'intensité ciblées: beaucoup de petits changements, favorisant des zones homogènes et extensives dans le cas d'un scénario d'extensification, à l'opposé de changements importants et moins nombreux, favorisant plus d'hétérogénéité, dans le cas d'un scénario d'intensification. Cette thèse apporte une des premières démonstrations de l'influence de l'agrégation spatiale de l'intensité sur la relation entre biodiversité et intensité. Nos résultats révèlent une opportunité pour améliorer l'efficacité des politiques de conservation de la biodiversité à l'échelle nationale. Il s'agit d'un ciblage de ces politiques, qui devra être différent pour maximiser la biodiversité à coût productif réduit ou pour augmenter la production tout en limitant les dommages sur la biodiversitéDuring the past several decades, agricultural intensification has been crucial to increase the food supply. Several processes related to intensification are very detrimental to the environment, particularly biodiversity. Today, agriculture is facing the challenge of satisfying its demand for food while improving its environmental sustainability. Knowledge of the shape of the relationship between biodiversity and intensity is necessary to determine both where conservation policies will be most effective and how to allocate intensity to reconcile production and biodiversity. Few empirical studies on this relationship exist, and the influence of the spatial arrangement of intensity on biodiversity remains untested. This Ph.D. thesis determined how to target both agricultural intensity and its spatial allocation for meeting production and conservation objectives of farmlands. To answer this research question, we used a country-scaled approach that combined two France-scaled databases that describe agriculture and farmland birds. We characterized a nationwide gradient of agricultural intensity and studied a farmland bird community along this gradient, using several trait-based descriptors (specialization, trophic level, and species main habitat). Agricultural intensity and bird communities were described at the Small Agricultural Region (SAR; mean width = 22.4 km) level. As a first step, we developed a novel method to estimate an intensity indicator that was based on Input Costs/ha, with SAR resolution. This indicator provides a continuous intensity measure that is relevant across different types of agricultural systems. Secondly, we investigated the effects of a gradient of land uses (grassland to arable land) and its heterogeneity on the bird community. We found habitat specialists suffered from habitat loss, while generalists benefited from heterogeneity. Thirdly, we showed that the community responded significantly to intensity, with winner species replacing loser species along the gradient. The shift between losers and winners was sharper at low intensities. Interestingly, spatial aggregation of intensity had a strengthening effect on the bird community. Finally, the relationships linking intensity to the bird community, food production, and economic performance were integrated into a model aimed at optimizing intensity allocation. Optimal allocations reached win-no-lose solutions with the three criteria. They corresponded to targeted intensity modifications: many small changed, favoring homogeneous, extensive clusters, were optimal within an extensification scenario; while a few large changes, favoring heterogeneity, were optimal within an intensification scenario. We provide one of the first studies demonstrating that spatial aggregation of intensity can influence the biodiversity/intensity relationship. Our results also provide an opportunity to improve the effectiveness of conservation policies, at national scales, with spatial targeting: opposite targeting should be performed either to maximize biodiversity benefits or to increase production, while mitigating biodiversity impacts. Our results highlight the importance of mixed allocation strategies between land sparing/sharing extremes. In order to put these opportunities into effect, further research should address the technical solutions that achieve intensity modification at the farm level and design targeted policies that benefit biodiversity and other environmental criteriaPARIS5-Bibliotheque electronique (751069902) / SudocSudocFranceF

    Freshwater fisheries harvest replacement estimates (Land and Water) for protein and the micronutrients contribution in the lower mekong river basin and related countries

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    International audienceFreshwater capture fisheries in the lower Mekong River basin (LMRB) contribute from 17% to 22% of the officially reported global inland capture fisheries catch. Several dams have been proposed on the Mekong River and its tributaries that will impact these fisheries. It has been estimated that the harvest from freshwater capture fisheries in the LMRB could decline by 880,000 metric tons in 2030 if all dam construction proceeds as planned. To reflect the consequences of lost fisheries in the LMRB, we reviewed existing data and calculated the contribution freshwater fisheries make to human protein, nutrient, and mineral requirements. We further calculated how much additional land and water would be required to replace lost fish protein in the LMRB with four other animal protein sources: beef, chicken, pork, and milk. Replacing fish with beef was found to be the most costly; to replace the fish harvest in the LMRB estimated to be lost due to dam construction with beef would require 3.6% of the total discharge of the Mekong River, which is equivalent to a 28% increase in water withdrawal compared to current levels. To replace all of the fish harvested in the LMRB with beef would require an additional 395,048 km(2) of land (equivalent to 65% of the total area of the Mekong River basin) and a 63% increase in water withdrawal. Replacing the fish with chicken would require the least additional land and water but still would require more than 36,000 km2 of land and an 8% increase in total water withdrawal from the Mekong River. The replacement analysis for the fish consumed in the four countries demonstrates that Cambodia would have the highest requirements in terms of increased use of land and water followed by Thailand and Vietnam, whereas Laos have lower requirements but would still need to increase its land use significantly. Overall, our analysis shows that freshwater fish is a highly valuable source of animal protein and micronutrients in LMRB. Replacing the fish protein with other sources of animal protein will require a substantially higher use of land and water

    Performance summary of the GLMs computing the interaction effect between agricultural intentity (<i>Input Cost / ha</i> indicator, IC/ha) and its spatial aggregation on the grassland specialisation index of the community (CSIg).

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    <p>“Aggregation” is the difference in intercept and “IC/ha*Aggregation” is the difference in slope in non aggregated SARs compared to aggregated SARs. n = 332 points for all models; CSI: community specialisation index, CTI: community trophic index, CSIg = grassland specialisation index of the community.</p><p>Performance summary of the GLMs computing the interaction effect between agricultural intentity (<i>Input Cost / ha</i> indicator, IC/ha) and its spatial aggregation on the grassland specialisation index of the community (CSIg).</p

    Effects of the <i>Input Cost/ha</i> (IC/ha) intensity indicator on size and composition of the bird community.

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    <p>Effect on (a) species richness, (b) community specialisation index, (c) community trophic level, and (d) grassland specialisation index of the bird community. Black curves: responses to the IC/ha intensity indicator as predicted by the GAM, and plotted with 95% confidence intervals (dotted lines) and partial residuals (grey points).</p

    Agricultural intensity value (<i>Input Cost/ha</i>, IC/ha) of SARs and FBBS sample sites (black dots) included in our analysis.

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    <p>Sample sites were surveyed between 2006 and 2008 and located in SARs dominated by industrial crops, cereals, bovine dairy, bovine meat, and mixed (crop/bovine) productions. SARs dominated by other production types appear in white. Continuous IC/ha values are shown as six classes, from lowest (green) to highest (red) intensity (see legend). SAR borders appear in grey.</p

    List of all explanatory variables.

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    <p>CLC = CORINE land cover</p><p>List of all explanatory variables.</p
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