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首页> 外文期刊>Ecological Applications >MAPPING OF SPECIES RICHNESS FOR CONSERVATION OF BIOLOGICAL DIVERSITY - CONCEPTUAL AND METHODOLOGICAL ISSUES
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MAPPING OF SPECIES RICHNESS FOR CONSERVATION OF BIOLOGICAL DIVERSITY - CONCEPTUAL AND METHODOLOGICAL ISSUES

机译：物种丰富度的映射保护生物多样性-概念和方法论问题

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Biodiversity mapping (e.g., the Gap Analysis Program [GAP]), in which vegetative features and categories of land use are mapped at coarse spatial scales, has been proposed as a reliable tool for land use decisions (e.g., reserve identification, selection, and design). This implicitly assumes that species richness data collected at coarse spatiotemporal scales provide a first-order approximation to community and ecosystem representation and persistence. This assumption may be false because (1) species abundance distributions and species richness are poor surrogates for community/ecosystem processes, and are scale dependent; (2) species abundance and richness data are unreliable because of unequal and unknown sampling probabilities and species-habitat models of doubtful reliability; (3) mapped species richness data may be inherently resistant to ''scaling up'' or ''scaling down''; and (4) decision-making based on mapped species richness patterns may be sensitive to errors from unreliable data and models, resulting in suboptimal conservation decisions. We suggest an approach in which mapped data are linked to management via demographic models, multiscale sampling, and decision theory. We use a numerical representation of a system in which vegetation data are assumed to be known and mapped without error, a simple model relating habitat to predicted species persistence, and statistical decision theory to illustrate use of mapped data in conservation decision-making and the impacts of uncertainty in data or models on the decision outcome. [References: 47]
机译：已经提出了生物多样性制图（例如，差距分析计划[GAP]），其中以粗略的空间尺度绘制了土地利用的营养特征和类别，这是进行土地利用决策（例如，保护区识别，选择和保护）的可靠工具。设计）。这隐含地假设以时空粗尺度收集的物种丰富度数据为群落和生态系统的表征和持久性提供了一阶近似。这种假设可能是错误的，因为（1）物种的丰富度分布和物种丰富度对于社区/生态系统过程而言是不良的替代物，并且与规模有关; （2）由于采样概率不均等和未知以及可靠性怀疑的物种栖息地模型，物种丰度和丰富度数据不可靠; （3）映射的物种丰富度数据可能固有地对“按比例放大”或“按比例缩小”具有抵抗力; （4）基于映射的物种丰富度模式的决策可能对来自不可靠数据和模型的错误敏感，从而导致次优保护决策。我们建议一种通过人口统计学模型，多尺度抽样和决策理论将映射数据链接到管理的方法。我们使用一个系统的数字表示形式，假设该系统中的植被数据被假定为已知且无错误地进行了映射，一个简单的模型将栖息地与预测的物种持久性相关联，并使用了统计决策理论来说明在保护性决策中所使用的映射数据及其影响决策结果的数据或模型的不确定性。 [参考：47]

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