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Optimizing future cropland allocation in a biodiverse savanna by integrating agricultural benefits and ecological costs

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Producing sufficient food to meet a growing population while minimizing the ecological impacts of agricultural expansion is a major world challenge. We aim to optimize the spatial allocation of future cropland in a manner that balances agricultural and ecological priorities, and test scenarios to reduce the need for cropland expansion to meet future food demands. We design a spatial trade-off model that linearly aggregates multiple land use objectives with flexibly- assigned weights to identify optimal areas for cropland expansion. We apply this model in Tanzania, where conservation of its biodiverse ecosystems is often in conflict with agriculture, to evaluate how various decision-making factors impact future cropland allocation and the associated ecological impacts. The model considers potential yield of five key crops (maize, paddy rice, sorghum, cassava, and common beans) along with travel time to markets (as an indicator for market proximity), and costs to biodiversity, carbon sequestration and landscape connectivity. Results show that compared to only considering crop yields, a hybrid solution, which equally considers multiple factors in decision-making, reduced travel time to markets by 25.4%, biodiversity loss by 1.4%, carbon loss by 0.8%, and connectivity loss by 27.5%, while only increasing land demand by 2.6%. Furthermore, increasing cropland area usage intensity and expanding the cultivation of high-yield crops can effectively boost food production, with the potential to double the current production only using existing cropland.
Title: Optimizing future cropland allocation in a biodiverse savanna by integrating agricultural benefits and ecological costs
Description:
Producing sufficient food to meet a growing population while minimizing the ecological impacts of agricultural expansion is a major world challenge.
We aim to optimize the spatial allocation of future cropland in a manner that balances agricultural and ecological priorities, and test scenarios to reduce the need for cropland expansion to meet future food demands.
We design a spatial trade-off model that linearly aggregates multiple land use objectives with flexibly- assigned weights to identify optimal areas for cropland expansion.
We apply this model in Tanzania, where conservation of its biodiverse ecosystems is often in conflict with agriculture, to evaluate how various decision-making factors impact future cropland allocation and the associated ecological impacts.
The model considers potential yield of five key crops (maize, paddy rice, sorghum, cassava, and common beans) along with travel time to markets (as an indicator for market proximity), and costs to biodiversity, carbon sequestration and landscape connectivity.
Results show that compared to only considering crop yields, a hybrid solution, which equally considers multiple factors in decision-making, reduced travel time to markets by 25.
4%, biodiversity loss by 1.
4%, carbon loss by 0.
8%, and connectivity loss by 27.
5%, while only increasing land demand by 2.
6%.
Furthermore, increasing cropland area usage intensity and expanding the cultivation of high-yield crops can effectively boost food production, with the potential to double the current production only using existing cropland.

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