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布基纳法索食用树种的空间明确多威胁评估:一种精细尺度方法。

Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach.

作者信息

Gaisberger Hannes, Kindt Roeland, Loo Judy, Schmidt Marco, Bognounou Fidèle, Da Sié Sylvestre, Diallo Ousmane Boukary, Ganaba Souleymane, Gnoumou Assan, Lompo Djingdia, Lykke Anne Mette, Mbayngone Elisée, Nacoulma Blandine Marie Ivette, Ouedraogo Moussa, Ouédraogo Oumarou, Parkouda Charles, Porembski Stefan, Savadogo Patrice, Thiombiano Adjima, Zerbo Guibien, Vinceti Barbara

机构信息

Bioversity International, Via dei Tre Denari 472/a, Maccarese (Rome), Italy.

World Agroforestry Centre (ICRAF), Nairobi, Kenya.

出版信息

PLoS One. 2017 Sep 7;12(9):e0184457. doi: 10.1371/journal.pone.0184457. eCollection 2017.

Abstract

Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana) and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change). We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs), climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as 'highly threatened' due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted regeneration in the central part where the current threat level is high due to overexploitation. In the same way, population-specific recommendations can be derived from the individual and combined threat maps of the other 15 food tree species. The approach can be easily transferred to other countries and can be used to analyze general and species specific threats at finer and more local as well as at broader (continental) scales in order to plan more selective and efficient conservation actions in time. The concept can be applied anywhere as long as appropriate spatial data are available as well as knowledgeable experts.

摘要

在过去几十年里,布基纳法索的农林间作公园受到了越来越大的人口和气候压力,这正威胁着当地的树种,而这些树种对农村家庭的收入和营养有着重大贡献。分析这些威胁以及物种对它们的脆弱性,对于保护规划中的优先级设定至关重要。在文献和当地专家的指导下,我们挑选了16种重要的食用树种(大穗相思、塞内加尔相思、猴面包树、塞内加尔番荔枝、埃及牛角瓜、圆叶梭罗、塞内加尔肉豆蔻、小果孪果藤、小果厚皮树、大叶合欢、乳木果、刺马钱子、罗望子、乳油木、美洲山榄、毛里求斯枣)以及对它们的六种主要威胁(过度开发、过度放牧、火灾、棉花种植、采矿和气候变化)。我们开发了一种特定物种且空间明确的方法,结合免费获取的数据集、物种分布模型(SDM)、气候模型和专家调查结果,以在精细尺度上预测这些威胁可能产生最大影响的地点。我们发现,所有物种在布基纳法索的大部分分布区域都面临严重威胁,从长期来看,气候变化预计将是最普遍的威胁,而过度开发和棉花种植是最重要的短期威胁。生长在因气候变化而被指定为“高度威胁”地区的树木种群,应用作迁地保护的种子来源,并在未来气候预测有适宜栖息地的地区进行种植。对于未来气候条件下适宜栖息地与因短期威胁而导致的高威胁水平相重合的地区的种群,建议进行辅助更新。对于乳油木,我们建议在其分布的北缘收集种子,并考虑在因过度开发而当前威胁水平较高的中部地区进行辅助更新。同样,可以从其他15种食用树种的单独和综合威胁地图中得出针对特定种群的建议。该方法可以轻松转移到其他国家,并可用于在更精细、更局部以及更广泛(大陆)的尺度上分析一般和特定物种的威胁,以便及时规划更具针对性和高效的保护行动。只要有合适的空间数据以及知识渊博的专家,这个概念可以在任何地方应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8be4/5589249/11c9e9f23397/pone.0184457.g001.jpg

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