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Priority areas for restoring ecosystem services to enhance human well-being in a dry forest

机译:恢复生态系统服务的优先领域,以增强人类福祉在干燥的森林中

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Habitat destruction reduces biodiversity and affects ecosystem functioning, putting at risk the provision of ecosystem services (ESs) essential for human well-being. Ecological restoration using native species with multiple uses may offer a long-term supply of natural resources for vulnerable human populations. We selected priority areas for restoration in the Brazilian Seasonally Dry Tropical Forest (Caatinga), targeting areas with high ES demand but low supply. We estimated the supply and demand for three ESs: (1) food/medicine, (2) wood production, and (3) pollination. We estimated ES supply using maps of the potential geographical distribution of 194 native plant species used by the local population as a means of livelihood. For ES demand, we used maps of population density, rural municipalities, wood productivity, and crops dependent on pollination. We used a large-scale prioritization tool (Zonation) to select two scenarios for each ES: (1) ES supply-only and (2) ES supply + ES demand, selecting only nonvegetated areas. To select priority areas, where the potential occurrence of species (ES supply) corresponds to areas of high demand for the same services, we overlapped the maps of the two scenarios for each ES. The highest percentage of scenario overlap occurred for food/medicine ES (45%), whereas pollination showed the lowest percentage of overlap (10%), indicating little similarity between potential ES supply and demand areas. Our study shows the importance of including ES in ecological restoration opportunities, taking into account the vulnerable human population in dry regions and their demand for natural resources.
机译:栖息地破坏减少了生物多样性并影响生态系统运作,风险提供了对人类福祉至关重要的生态系统服务(ESS)。使用具有多种用途的本地物种的生态恢复可以为脆弱的人口提供长期供应自然资源。我们选择了在巴西季节性干燥的热带森林(CAINCEA)中恢复的优先领域,瞄准具有高ES需求但低供应的地区。我们估计了三个符号的供需:(1)食品/药物/药物,(2)木材生产和(3)授粉。我们使用当地人口为生计手段,使用194个本土植物物种的潜在地理分布的地图来估计ES供应。对于ES需求,我们使用人口密度,农村,木材生产力和富裕的作物地图依赖于授粉。我们使用了一个大规模的优先级化工具(分区)来选择每个ES的两个场景:(1)ES供电和(2)ES供应+ ES需求,仅选择非终端区域。选择优先级区域,其中物种的潜在发生(ES供应)对应于对同一服务的高需求领域,我们重叠了每个ES的两种情况的地图。食品/药物ES(45%)发生的场景重叠百分比最高,而授粉显示较低的重叠百分比(10%),表明潜在的ES供需区域之间的相似性很小。我们的研究表明,在生态恢复机会中介绍了包括ES的重要性,同时考虑到干旱地区的脆弱人群及其对自然资源的需求。

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