Mapping of Species Richness for Conservation of Biological Diversity: Conceptual and Methodological Issues
Mapping of Species Richness for Conservation of Biological Diversity: Conceptual and Methodological Issues
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为保护生物多样性绘制物种丰富度图：概念和方法问题
DOI：
10.2307/2269481
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发表时间：
1996
影响因子：
5
通讯作者：
B. Noon
中科院分区：
文献类型：
--
作者：
M. Conroy;B. Noon
生物多样性测绘(例如，差距分析计划[GAP])在粗略的空间尺度上绘制了土地利用的植被特征和类别，已被提议作为土地利用决策(例如，保护区识别、选择和设计)的可靠工具。这隐含地假设，在粗略的时空尺度上收集的物种丰富度数据提供了群落和生态系统代表性和持久性的一级近似值。这一假设可能是错误的，因为(1)物种丰富度分布和物种丰富度不能很好地反映群落/生态系统过程，并且依赖于尺度；(2)物种丰富度和丰富度数据是不可靠的，因为抽样概率不相等和未知，物种栖息地模型的可靠性令人怀疑；(3)绘制的物种丰富度数据可能内在地抵制扩大或缩小规模：(4)基于绘制的物种丰富度格局的决策可能对不可靠的数据和模型的错误敏感，导致次优的保护决策。我们建议一种方法，通过人口统计模型、多尺度抽样和决策理论将地图数据与管理联系起来。我们使用一个系统的数值表示，其中假设植被数据是已知的，并且没有错误地绘制，一个将生境与预测的物种持久性联系起来的简单模型，以及统计决策理论来说明在保护决策中使用绘制的数据以及数据或模型中的不确定性对决策结果的影响。
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 spatio-temporal 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.