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Richness Estimates (richness + estimate)
Selected AbstractsGlobal patterns of plant diversity and floristic knowledgeJOURNAL OF BIOGEOGRAPHY, Issue 7 2005Gerold Kier Abstract Aims, We present the first global map of vascular plant species richness by ecoregion and compare these results with the published literature on global priorities for plant conservation. In so doing, we assess the state of floristic knowledge across ecoregions as described in floras, checklists, and other published documents and pinpoint geographical gaps in our understanding of the global vascular plant flora. Finally, we explore the relationships between plant species richness by ecoregion and our knowledge of the flora, and between plant richness and the human footprint , a spatially explicit measure of the loss and degradation of natural habitats and ecosystems as a result of human activities. Location, Global. Methods, Richness estimates for the 867 terrestrial ecoregions of the world were derived from published richness data of c. 1800 geographical units. We applied one of four methods to assess richness, depending on data quality. These included collation and interpretation of published data, use of species,area curves to extrapolate richness, use of taxon-based data, and estimates derived from other ecoregions within the same biome. Results, The highest estimate of plant species richness is in the Borneo lowlands ecoregion (10,000 species) followed by nine ecoregions located in Central and South America with , 8000 species; all are found within the Tropical and Subtropical Moist Broadleaf Forests biome. Among the 51 ecoregions with , 5000 species, only five are located in temperate regions. For 43% of the 867 ecoregions, data quality was considered good or moderate. Among biomes, adequate data are especially lacking for flooded grasslands and flooded savannas. We found a significant correlation between species richness and data quality for only a few biomes, and, in all of these cases, our results indicated that species-rich ecoregions are better studied than those poor in vascular plants. Similarly, only in a few biomes did we find significant correlations between species richness and the human footprint, all of which were positive. Main conclusions, The work presented here sets the stage for comparisons of degree of concordance of plant species richness with plant endemism and vertebrate species richness: important analyses for a comprehensive global biodiversity strategy. We suggest: (1) that current global plant conservation strategies be reviewed to check if they cover the most outstanding examples of regions from each of the world's major biomes, even if these examples are species-poor compared with other biomes; (2) that flooded grasslands and flooded savannas should become a global priority in collecting and compiling richness data for vascular plants; and (3) that future studies which rely upon species,area calculations do not use a uniform parameter value but instead use values derived separately for subregions. [source] Estimating bird species richness: How should repeat surveys be organized in time?AUSTRAL ECOLOGY, Issue 6 2002Scott A. Field Abstract Estimates of species richness for a given area require that repeat surveys be taken, so that the statistical robustness of the estimate can be assessed. But how should these repeat surveys be organized in time? Here we present a case study of Australian woodland birds, surveyed using the ,active timed area search' method, which has become the standard unit for the Australian Bird Atlas, a continental-scale bird survey. To date, there has been no assessment of how estimates of species richness derived from this method are affected by the temporal organization of the repeat surveys. For instance, can conducting the repeat surveys in sequence on the same day effectively capture richness, or will additional species be obtained by repeating the surveys on different days within a season? If so, does the spacing of the repeat visits throughout the season have an effect? To answer these questions, we surveyed woodland birds in the Mount Lofty Ranges, South Australia, during late spring,summer 1999,2000, and compared the performance of two different temporal configurations of repeat visits to sites: (i) six repeat surveys performed on the same day; and (ii) three repeat surveys on different days. For both, we calculated the average number of species actually sighted and also estimated total species richness. The data supported our hypothesis that the same-day surveys would yield fewer species and underestimate total species richness. The different-day repeats captured significantly more species per unit of survey effort, and yielded a higher richness estimate. However, the timespan over which different-day surveys were conducted within a season did not have a significant influence on species richness estimates, evincing a qualitative advantage to surveying on different days, regardless of the spacing of repeat visits. These results may be of assistance to conservation managers when planning cost-efficient monitoring regimes. [source] Undersampling bias: the null hypothesis for singleton species in tropical arthropod surveysJOURNAL OF ANIMAL ECOLOGY, Issue 3 2009Jonathan A. Coddington Summary 1Frequency of singletons , species represented by single individuals , is anomalously high in most large tropical arthropod surveys (average, 32%). 2We sampled 5965 adult spiders of 352 species (29% singletons) from 1 ha of lowland tropical moist forest in Guyana. 3Four common hypotheses (small body size, male-biased sex ratio, cryptic habits, clumped distributions) failed to explain singleton frequency. Singletons are larger than other species, not gender-biased, share no particular lifestyle, and are not clumped at 0·25,1 ha scales. 4Monte Carlo simulation of the best-fit lognormal community shows that the observed data fit a random sample from a community of ~700 species and 1,2 million individuals, implying approximately 4% true singleton frequency. 5Undersampling causes systematic negative bias of species richness, and should be the default null hypothesis for singleton frequencies. 6Drastically greater sampling intensity in tropical arthropod inventory studies is required to yield realistic species richness estimates. 7The lognormal distribution deserves greater consideration as a richness estimator when undersampling bias is severe. [source] Effects of sampling teams and estimation methods on the assessment of plant coverJOURNAL OF VEGETATION SCIENCE, Issue 6 2003Suzanne M. Kercher Abstract. We evaluated variability in cover estimation data obtained by (1) two sampling teams who double sampled plots and (2) one team that used two methods (line intercepts and visual estimation of cover classes) to characterize vegetation of herbaceous wetlands. Species richness and cover estimates were similar among teams and among methods, but one sampling team scored cover higher than the other. The line intercept technique yielded higher cover estimates but lower species richness estimates than the cover class method. Cluster analyses of plots revealed that 36% and 11% of plots sampled consecutively by two teams or using two methods, respectively, were similar enough in species composition and abundance to be paired together in the resulting clustering tree. Simplifying cover estimate data to presence/absence increased the similarity among both teams and methods at the plot scale. Teams were very similar in their overall characterization of sites when cover estimation data were used, as assessed by cluster analysis, but methods agreed best on their overall characterization of sites when only presence/absence data were considered. Differences in abundance estimates as well as pseudoturnover contribute to variability. For double sampled plots, pseudoturnover was 19.1%, but 57.7% of pseudo-turnover cases involved taxa with , 0.5% cover while only 3.4% involved taxa with > 8% cover. We suggest that vegetation scientists incorporate quality control, calibrate observers and publish their results. [source] Estimating bird species richness: How should repeat surveys be organized in time?AUSTRAL ECOLOGY, Issue 6 2002Scott A. Field Abstract Estimates of species richness for a given area require that repeat surveys be taken, so that the statistical robustness of the estimate can be assessed. But how should these repeat surveys be organized in time? Here we present a case study of Australian woodland birds, surveyed using the ,active timed area search' method, which has become the standard unit for the Australian Bird Atlas, a continental-scale bird survey. To date, there has been no assessment of how estimates of species richness derived from this method are affected by the temporal organization of the repeat surveys. For instance, can conducting the repeat surveys in sequence on the same day effectively capture richness, or will additional species be obtained by repeating the surveys on different days within a season? If so, does the spacing of the repeat visits throughout the season have an effect? To answer these questions, we surveyed woodland birds in the Mount Lofty Ranges, South Australia, during late spring,summer 1999,2000, and compared the performance of two different temporal configurations of repeat visits to sites: (i) six repeat surveys performed on the same day; and (ii) three repeat surveys on different days. For both, we calculated the average number of species actually sighted and also estimated total species richness. The data supported our hypothesis that the same-day surveys would yield fewer species and underestimate total species richness. The different-day repeats captured significantly more species per unit of survey effort, and yielded a higher richness estimate. However, the timespan over which different-day surveys were conducted within a season did not have a significant influence on species richness estimates, evincing a qualitative advantage to surveying on different days, regardless of the spacing of repeat visits. These results may be of assistance to conservation managers when planning cost-efficient monitoring regimes. [source] | ||||||||||