John T. Longino

Bio: John T. Longino is an academic researcher from University of Utah. The author has contributed to research in topics: Species richness & Biodiversity. The author has an hindex of 34, co-authored 99 publications receiving 7033 citations. Previous affiliations of John T. Longino include The Evergreen State College & University of California, Santa Barbara.

Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages

Abstract: Aims In ecology and conservation biology, the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected. Moreover, comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled. For individual-based data, we treat a single, empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models: estimating the expected number of species (and its unconditional variance) in a random sample of (i) a smaller number of individuals (multinomial model) or a smaller area sampled (Poisson model) and (ii) a larger number of individuals or a larger area sampled. For sample-based incidence (presence–absence) data, under a Bernoulli product model, we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units. Methods The first objective is a problem in interpolation that we address with classical rarefaction (multinomial model) and Coleman rarefaction (Poisson model) for individual-based data and with sample-based rarefaction (Bernoulli product model) for incidence frequencies. The second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample (multinomial model), a larger area (Poisson model) or a larger number of sampling units (Bernoulli product model), based on an estimate of asymptotic species richness. Although published methods exist for many of these objectives, we bring them together here with some new estimators under a unified statistical and notational framework. This novel integration of mathematically distinct approaches allowed us to link interpolated (rarefaction) curves and extrapolated curves to plot a unified species accumulation curve for empirical examples. We provide new, unconditional variance estimators for classical, individual-based rarefaction and for Coleman rarefaction, long missing from the toolkit of biodiversity measurement. We illustrate these methods with datasets for tropical beetles, tropical trees and tropical ants.

Global Warming, Elevational Range Shifts, and Lowland Biotic Attrition in the Wet Tropics

Abstract: Many studies suggest that global warming is driving species ranges poleward and toward higher elevations at temperate latitudes, but evidence for range shifts is scarce for the tropics, where the shallow latitudinal temperature gradient makes upslope shifts more likely than poleward shifts. Based on new data for plants and insects on an elevational transect in Costa Rica, we assess the potential for lowland biotic attrition, range-shift gaps, and mountaintop extinctions under projected warming. We conclude that tropical lowland biotas may face a level of net lowland biotic attrition without parallel at higher latitudes (where range shifts may be compensated for by species from lower latitudes) and that a high proportion of tropical species soon faces gaps between current and projected elevational ranges.

Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation

Abstract: Physiological thermal-tolerance limits of terrestrial ectotherms often exceed local air temperatures, implying a high degree of thermal safety (an excess of warm or cold thermal tolerance). However, air temperatures can be very different from the equilibrium body temperature of an individual ectotherm. Here, we compile thermal-tolerance limits of ectotherms across a wide range of latitudes and elevations and compare these thermal limits both to air and to operative body temperatures (theoretically equilibrated body temperatures) of small ectothermic animals during the warmest and coldest times of the year. We show that extreme operative body temperatures in exposed habitats match or exceed the physiological thermal limits of most ectotherms. Therefore, contrary to previous findings using air temperatures, most ectotherms do not have a physiological thermal-safety margin. They must therefore rely on behavior to avoid overheating during the warmest times, especially in the lowland tropics. Likewise, species living at temperate latitudes and in alpine habitats must retreat to avoid lethal cold exposure. Behavioral plasticity of habitat use and the energetic consequences of thermal retreats are therefore critical aspects of species’ vulnerability to climate warming and extreme events.

The ant fauna of a tropical rain forest: estimating species richness three different ways

Abstract: Species richness is an important characteristic of ecological communities, but it is difficult to quantify. We report here a thorough inventory of a tropical rain forest ant fauna and use it to evaluate species richness estimators. The study was carried out in ;1500 ha of lowland rain forest at La Selva Biological Station, Costa Rica. Diverse methods were used, including canopy fogging, Malaise traps, Berlese samples, Winkler samples, baiting, and manual search. Workers of 437 ant species were encountered. The abundance distribution was clearly lognormal, and the distribution emerged from a veil line with each doubling of sampling effort. Three richness estimates were calculated: the area under the fitted lognormal distribution, the asymptote of the Michaelis-Menten equation fit to the species accumulation curve, and the Incidence-based Coverage Estimator (ICE). The per- formance of the estimators was evaluated with sample-based rarefaction plots. The inventory was nearly complete because the species accumulation curve approached an asymptote, the richness estimates were very close to the observed species richness, and the uniques and duplicates curves were both declining. None of the richness estimators was stable in sample- based rarefaction plots, but regions of stability of estimators occurred. The explanation of rarity is one key to understanding why richness estimates fail. Fifty-one species (12% of the total) were still uniques (known from only one sample) at the end of the inventory. The rarity of 20 of these species was explained by ''edge effects'': ''methodological edge species'' (possibly abundant at the site but difficult to sample because of their microhabitat), and ''geographic edge species,'' known to be common in habitats or regions outside of La Selva. Rarity of 31 species remained unexplained. Most of the 51 rare species were known from additional collections outside of La Selva, either in other parts of Costa Rica or in other countries. Only six species were ''global uniques,'' known to date from only one sample on Earth. The study demonstrates that patterns of species occurrence early in an inventory may be inadequate to estimate species richness, but that relatively complete inventories of species-rich arthropod communities are possible if multiple sampling methods and extensive effort are applied.

Biodiversity assessment using structured inventory: capturing the ant fauna of a tropical rain forest

Abstract: The goal of “strict inventory” (as opposed to community characterization) is to obtain species lists for specific sites. Quantitatively structured inventory can improve inventory efficiency (defined as the steepness of species accumulation curves). As part of the Arthropods of La Selva project (ALAS), a structured inventory of the ants of a lowland tropical rain forest was carried out. A novel method of sample processing was developed, in which parataxonomists prepared specimens based on their own sorting of morphospecies within samples (repeating the process for each sample, and thus not attempting to cross-reference morphospecies among samples), and a taxonomic specialist later sorted the resultant pool of prepared specimens. Efficacy of stratifying by sampling method (Berlese samples, Malaise traps, and canopy fogging), habitat, and time was investigated. Novel methods of analysis were used, including (1) curves depicting cost in prepared specimens of adding species to the inventory, as a function of n...

Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

Abstract: Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category‐subcategory ratios (species-to-genus and species-toindividual ratios). Rarefaction methods ‐ both sample-based and individual-based ‐ allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.

Influence of Diet On the Distribtion of Nitrogen Isotopes in Animals

Abstract: The influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition. The isotopic composition of the nitrogen in an animal reflects the nitrogen isotopic composition of its diet. The δ^(15)N values of the whole bodies of animals are usually more positive than those of their diets. Different individuals of a species raised on the same diet can have significantly different δ^(15)N values. The variability of the relationship between the δ^(15)N values of animals and their diets is greater for different species raised on the same diet than for the same species raised on different diets. Different tissues of mice are also enriched in ^(15)N relative to the diet, with the difference between the δ^(15)N values of a tissue and the diet depending on both the kind of tissue and the diet involved. The δ^(15)N values of collagen and chitin, biochemical components that are often preserved in fossil animal remains, are also related to the δ^(15)N value of the diet. The dependence of the δ^(15)N values of whole animals and their tissues and biochemical components on the δ^(15)N value of diet indicates that the isotopic composition of animal nitrogen can be used to obtain information about an animal's diet if its potential food sources had different δ^(15)N values. The nitrogen isotopic method of dietary analysis probably can be used to estimate the relative use of legumes vs non-legumes or of aquatic vs terrestrial organisms as food sources for extant and fossil animals. However, the method probably will not be applicable in those modern ecosystems in which the use of chemical fertilizers has influenced the distribution of nitrogen isotopes in food sources. The isotopic method of dietary analysis was used to reconstruct changes in the diet of the human population that occupied the Tehuacan Valley of Mexico over a 7000 yr span. Variations in the δ^(15)C and δ^(15)N values of bone collagen suggest that C_4 and/or CAM plants (presumably mostly corn) and legumes (presumably mostly beans) were introduced into the diet much earlier than suggested by conventional archaeological analysis.

Estimating Terrestrial Biodiversity through Extrapolation

Abstract: Both the magnitude and the urgency of the task of assessing global biodiversity require that we make the most of what we know through the use of estimation and extrapolation. Likewise, future biodiversity inventories need to be designed around the use of effective sampling and estimation procedures, especially for 'hyperdiverse' groups of terrestrial organisms, such as arthropods, nematodes, fungi, and microorganisms. The challenge of estimating patterns of species richness from samples can be separated into (i) the problem of estimating local species richness, and (ii) the problem of estimating the distinctness, or complementarity, of species assemblages. These concepts apply on a wide range of spatial, temporal, and functional scales. Local richness can be estimated by extrapolating species accumulation curves, fitting parametric distributions of relative abundance, or using non-parametric techniques based on the distribution of individuals among species or of species among samples. We present several of these methods and examine their effectiveness for an example data set. We present a simple measure of complementarity, with some biogeographic examples, and outline the difficult problem of estimating complementarity from samples. Finally, we discuss the importance of using 'reference' sites (or sub-sites) to assess the true richness and composition of species assemblages, to measure ecologically significant ratios between unrelated taxa, to measure taxon/sub-taxon (hierarchical) ratios, and to 'calibrate' standardized sampling methods. This information can then be applied to the rapid, approximate assessment of species richness and faunal or floral composition at 'comparative' sites.

Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies

Abstract: Quantifying and assessing changes in biological diversity are central aspects of many ecological studies, yet accurate methods of estimating biological diversity from sampling data have been elusive. Hill numbers, or the effective number of species, are increasingly used to characterize the taxonomic, phylogenetic, or functional diversity of an assemblage. However, empirical estimates of Hill numbers, including species richness, tend to be an increasing function of sampling effort and, thus, tend to increase with sample completeness. Integrated curves based on sampling theory that smoothly link rarefaction (interpolation) and prediction (extrapolation) standardize samples on the basis of sample size or sample completeness and facilitate the comparison of biodiversity data. Here we extended previous rarefaction and extrapolation models for species richness (Hill number q D, where q ¼ 0) to measures of taxon diversity incorporating relative abundance (i.e., for any Hill number q D, q . 0) and present a unified approach for both individual-based (abundance) data and sample- based (incidence) data. Using this unified sampling framework, we derive both theoretical formulas and analytic estimators for seamless rarefaction and extrapolation based on Hill numbers. Detailed examples are provided for the first three Hill numbers: q ¼ 0 (species richness), q ¼ 1 (the exponential of Shannon's entropy index), and q ¼ 2 (the inverse of Simpson's concentration index). We developed a bootstrap method for constructing confidence intervals around Hill numbers, facilitating the comparison of multiple assemblages of both rarefied and extrapolated samples. The proposed estimators are accurate for both rarefaction and short-range extrapolation. For long-range extrapolation, the performance of the estimators depends on both the value of q and on the extrapolation range. We tested our methods on simulated data generated from species abundance models and on data from large species inventories. We also illustrate the formulas and estimators using empirical data sets from biodiversity surveys of temperate forest spiders and tropical ants.

iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers)

Abstract: Summary Hill numbers (or the effective number of species) have been increasingly used to quantify the species/taxonomic diversity of an assemblage. The sample-size- and coverage-based integrations of rarefaction (interpolation) and extrapolation (prediction) of Hill numbers represent a unified standardization method for quantifying and comparing species diversity across multiple assemblages. We briefly review the conceptual background of Hill numbers along with two approaches to standardization. We present an R package iNEXT (iNterpolation/EXTrapolation) which provides simple functions to compute and plot the seamless rarefaction and extrapolation sampling curves for the three most widely used members of the Hill number family (species richness, Shannon diversity and Simpson diversity). Two types of biodiversity data are allowed: individual-based abundance data and sampling-unit-based incidence data. Several applications of the iNEXT packages are reviewed: (i) Non-asymptotic analysis: comparison of diversity estimates for equally large or equally complete samples. (ii) Asymptotic analysis: comparison of estimated asymptotic or true diversities. (iii) Assessment of sample completeness (sample coverage) across multiple samples. (iv) Comparison of estimated point diversities for a specified sample size or a specified level of sample coverage. Two examples are demonstrated, using the data (one for abundance data and the other for incidence data) included in the package, to illustrate all R functions and graphical displays.