sGD: software for estimating spatially explicit indices of genetic diversity
sGD: software for estimating spatially explicit indices of genetic diversity
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sGD：用于估计遗传多样性的空间明确指数的软件
DOI：
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发表时间：
2011
影响因子：
7.7
通讯作者：
S. Cushman
中科院分区：
文献类型：
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作者：
A. Shirk;S. Cushman
人为的景观变化大大减少了许多陆生物种的种群规模、范围和迁移速度。残余种群的局部有效种群规模较小，有利于遗传多样性的丧失，导致适应度和适应潜力降低，最终导致更大的灭绝风险。因此，准确量化遗传多样性对于评估小种群的生存能力至关重要。多样性指数通常是根据在离散定义的生境斑块或更大的区域范围内取样的所有个体的多位点基因型计算的。重要的是，离散种群方法不能捕获因距离或景观抗性而遗传隔离的种群的临床性质。在这里，我们引入了空间遗传多样性（sGD），这是一种新的空间明确工具，用于估计遗传多样性，该工具基于将个体分组到与种群结构相匹配的潜在重叠遗传邻域，无论是离散的还是临床的。我们比较了在模拟种群和经验种群上使用斑块或区域采样和sGD的遗传多样性估计值和模式。当种群不满足孤岛模型的假设时，我们发现斑块和区域抽样普遍高估了局部杂合度、近交和等位基因多样性。此外，sGD还揭示了遗传多样性的精细尺度空间异质性，这在斑块或区域抽样中并不明显。这些优势应提供一种更有力的手段来评估遗传因素影响临床种群生存能力的潜力，并指导适当的保护计划。
Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine‐scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans.