Abstract
Estimates of spatial patterns of broad-scale species richness are central to major questions in ecology, evolution and conservation. Yet, they are scarce due to incomplete information on species distributions. Often the only germane data derives from museum specimens collected during non-standardized sampling. Rarefaction, a promising approach to estimate broad-scale richness with these data, estimates the expected number of species represented in subsets of n specimens drawn from N specimens collected in a sampling unit. One version of rarefaction, known as individual-based rarefaction, assumes that the N specimens collected in a sampling unit constitute a random sample of individuals in that sampling unit. Another version, known as spatially explicit rarefaction, assumes that the N specimens collected in a sampling unit are spatially aggregated. We examined the working hypothesis that, when applied to museum specimen data, spatially explicit rarefaction is less biased than individual-based rarefaction because it reduces overestimation due to spatially aggregated sampling. We derived five predictions from this working hypothesis and tested them using computer simulation experiments based on a database of 129,782 plant specimens from Nicaragua, and sampling units of 5 x 5, 50 x 50, and 100 x 100 km. One experiment was a negative control, whereby we simulated collection of randomly chosen individuals from each sampling unit. In contrast, three other experiments included spatially aggregated sampling. In all experiments we applied individual-based and spatially explicit rarefaction to estimate richness, with n = 200 and n = 500 specimens. As expected, the experiment designed as a negative control did not support the working hypothesis. The other three experiments supported the working hypothesis in analyses of larger sampling units, but not in 5 x 5 km sampling units. The predictions we derived from the working hypothesis can be used to assess which rarefaction version is best in particular systems.
Highlights
Understanding spatial patterns of broad-scale species richness is a major goal in ecology and evolutionary biology [1,2], with implications for biodiversity conservation [3,4]
Results for prediction 4 showed that estimates from individual-based rarefaction were always significantly closer to accumulation curves than those of spatially explicit rarefaction (Table 2)
There was support for prediction 3. This result was expected, because richness estimates based on individual-based rarefaction ought to be generally higher than those based on spatially explicit rarefaction, given spatial aggregation of species occurrences (Fig 2)
Summary
Understanding spatial patterns of broad-scale species richness is a major goal in ecology and evolutionary biology [1,2], with implications for biodiversity conservation [3,4]. Quantifying broad-scale species richness is often difficult due to uncertainty about the geographic distribution of species This issue, known as the “Wallacean shortfall” [5,6], is most severe for studies focusing on highly diverse taxa, including vascular plants and invertebrates [7,8,9,10]. Often the only germane information available derives from natural history museum specimens collected during non-standardized sampling. Obtaining from these data complete counts of the number of species occurring within relatively large areas is often virtually impossible. It would be invalid to compare the number of species known to occur in two equal-area sampling units that differed in sampling effort (Fig 1)
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