Nonparametric Estimators Of Species Richness Research Articles

Species diversity and spatial distribution of mosquitoes (Diptera: Culicidae) from La Isla Amazon Park, Napo Province, Ecuador

Introduction: Vector-borne diseases are prevalent in the Amazon and Coastal regions of Ecuador. However, there is a scarcity of mosquito ecology studies in these areas. The most recent list of species reported for the country comprises 8 tribes, 22 genera, and 200 species. Objectives: To document the Culicidae species found in La Isla Amazon Park, Napo, Ecuador, including those with epidemiological significance; and to analyze their composition, abundance, and diversity, focusing on larval habitats during the dry and rainy periods. Methods: We evaluated different larval habitats, considering collection duration as the primary criterion. We used CDC and Shannon traps to collect adult mosquitoes during both rainy and dry periods. To assess sampling effort, we used accumulation curves and non-parametric estimators of species richness, while we employed Hill numbers to determine diversity. Additionally, we used the Berger-Parker and Pielou indices to evaluate species dominance and evenness. We conducted cluster analysis and ANOSIM tests to assess the similarity between habitats and the differences in taxonomic composition between periods. Results: We collected a total of 802 individuals from 15 species and 4 taxonomic units, 5 genera, and 4 tribes. Notably, this may be the first records of Wyeomyia felicia Dyar & Núñez Tovar and Culex derivator Dyar & Knab from Ecuador. Additionally, the presence of Culex dunni Dyar and Psorophora ferox von Humboldt (both recognized as vectors) was correlated with increased rainfall. Conclusions: The abundance of mosquitoes, including potential vector species, increased during the rainy season, indicating a higher risk of pathogen transmission. However, the relationship between rainfall amount and diversity patterns is not well-defined.

Uneven species occurrence and richness of lowland snakes (Serpentes, Squamata) in Terengganu, Peninsular Malaysia, with new locality records.

This study documents information on the composition, diversity, richness, and temporal occurrence of snakes at Sekayu's lowland forest (SLF), Terengganu, Peninsular Malaysia for the first time. The snakes recorded within the SLF were sampled opportunistically from 2013 to 2019, employing the Visual Encounter Survey method (VES) and L-shape pitfall traps with drift fences. Forty-six snake species from 37 genera belonging to the nine families were recorded, of which 11 were new records to Terengganu. Individual-based rarefaction and extrapolation curves were not reaching asymptote, indicating that additional species can be recorded at the study area. Non-parametric species richness estimators estimated and produced a range between 51 and 57 species. ACE was the best estimator based on the quantitative evaluation. All species showed some variations of occurrence patterns across months. Fourteen species were only encountered once across the sampling years, and interestingly 11 of them were only detected during the rainy season (late October to January). In general, the number of species richness, abundance, and rare species were high during this season. Species richness of snakes is high at SLF but sampling effort should be intensified, especially during these rainy months, to obtain a robust estimated snake species richness in SLF. Terengganu harbor considerably high species richness of snakes with a total of 71 species to date (excluding marine snakes), but snake diversity is still underestimated as only a few localities were surveyed in the past years, primarily at the northern part. Future surveys should be commenced at the central and southern parts of Terengganu to complement the current investigation.

Estimating total species richness: Fitting rarefaction by asymptotic approximation

AbstractEstimating the number of species in a community is important for assessments of biodiversity. Previous species richness estimators are mainly based on nonparametric approaches. Although parametric asymptotic models have been applied, they received limited attention due to specific limitations. Here, we introduce parametric models fitting the probability‐based rarefied species richness curve that allow us to estimate the “Total Expected Species” (TES) in a community based on species' abundance data. We develop two approaches to calculate TES (termed “TESa” and “TESb”), based on two slightly different mathematical assumptions regarding Expected Species (ES) models. We provide R functions to calculate both these estimation approaches and their standard deviation. The function also enables users to visualize the estimation. We test the performance of TESa, TESb, and their average (TESab) across simulated and empirical data, and compare their bias, precision, and accuracy with other commonly used, nonparametric species richness estimators: the bias‐corrected (bc‐)Chao1 and the abundance‐based coverage estimator (ACE). Simulation reveals that in small samples TESa shows a tendency to overestimate and TESb to underestimate overall species richness. TESab performs well in bias, precision, and accuracy when compared with (bc‐)Chao1 and ACE estimators. Results from empirical data show that the variance generated from TES estimates is comparable with that for (bc‐)Chao1 and ACE. Our study demonstrates that rarefaction theory in combination with parametric approximation models provides a valuable new approach to estimate the species richness of incompletely sampled communities. Robust estimates are likely to be obtained where the observed number of species is greater than half of the TES estimation. When the ratio of TESa to the observed richness is ≫2, we suggest the use of TESb or TESab. Although more comprehensive comparisons with other estimators are suggested, we encourage researchers to consider the TES approach in their biodiversity studies as a complement to current existing estimators.

Taxonomic uncertainty and the challenge of estimating global species richness

Taxonomic uncertainty and the challenge of estimating global species richness

A Universal Key to Rationally Select Which, Among Nonparametric Species Richness Estimators, Performs Best According to Each Particular Incomplete Sampling

Since most samplings of local species communities are bound to remain substantially incomplete for practical reasons, a wide variety of nonparametric estimators of the number of unrecorded species have been proposed over the past fifty years. Unfortunately, the distinct formulations of each of these estimators naturally lead to substantially divergent estimates. The will to try to select, in each case, the estimator expected to be the more accurate has long been carried out only on a purely empirical, even arbitrary, basis (as is evident from the extensive consultation of much of the past literature on estimating species richness of incompletely sampled communities). So that extrapolating the true species richness of a community from its incomplete survey has long remained quite unsatisfactory. Indeed, the definition of a truly rational procedure for selecting the most accurate (least-biased) estimator actually requires a solidly established theoretical framework, involving to conform, as best as possible, to the general mathematical characteristics of the Species Accumulation Function. Accordingly, unveiling, first of all, these mathematical characteristics of the Species Accumulation Function was a decisive step forward in this perspective. Thereby making it now possible to propose an objective key to rationally select the one, within the series of various estimators, which, depending on each particular sampling, happens to be the least biased in this particular case, thus providing the most accurate estimate of the number of still unrecorded species. And, consequently, making it possible, now, to deliver the best estimate of the true species richness of a local community, despite its being incompletely surveyed.

Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation

Abstract Estimates of the number of successfully breeding adults (NS) in a population can predict levels of recruitment. However, assessments of NS are often difficult to obtain because encounters with adults are limited due to life‐history characteristics, low abundance or other constraints associated with access to critical habitats. Alternatively, efforts to sample individuals at earlier ontogenetic stages can be more tractable, resulting in more comprehensive samples. To estimate NS, we describe, evaluate and apply two nonparametric species richness estimators to information associated with genetic pedigree reconstruction. Simulations compared bias and precision associated with Chao and Jackknife methods when estimating NS. We also evaluated NS estimation sensitivity to two sources of variation associated with species reproductive ecology (variance in reproductive success and sex ratio skew) and genetic pedigree assignment error. Finally, the application of our novel method was demonstrated in two different species and systems (Chinook Salmon in Oregon, USA and Lake Sturgeon in Michigan, USA). We found unbiased NS estimates were generated across a broad range of offspring sample sizes using the Chao method. Empirical results corroborated simulation‐based expectations and highlighted applications where parents and offspring are sampled, and when only offspring are sampled. When offspring sample sizes are adequate and pedigree reconstruction errors are low, the combination of established methods from community ecology and genetic pedigree reconstruction provides an accurate alternative method to estimate NS that can facilitate population assessments.

Cost-effective sampling for estimating species richness of ground beetles (Coleoptera: Carabidae) using pitfall traps: efficiency of non-parametric species richness estimators

Because it is extremely time-consuming and costly to evaluate species richness of highly diverse taxa such as insects, cost-effective sampling strategies to estimate species richness are needed, especially when long-term monitoring is conducted. We found a sampling method that reduced the number of traps per site when estimating species richness of ground beetles (Coleoptera: Carabidae) in six forest sites in Sorachi, Hokkaido, northern Japan. We set 40 pitfall traps per site and collected ground beetles for 1-week periods in June, July, and August 2013. We evaluated the performance of three non-parametric species richness estimators [Jackknife2, Chao1, and the abundance-based coverage estimator (ACE)] to estimate species richness. Rarefaction curves showed that ACE was the only valid estimator to estimate species richness for all sites. Using ACE, we can reduce the number of traps to 30 or 20 from 40 traps per site if we allow a bias of 5 or 10%, respectively. This study suggests that non-parametric species richness estimators are useful in estimating species richness of ground beetles with reduced sample size.

Does microhabitat influence the testate amoebae communities in the Nameri National Park, northeastern India? A tropical forest perspective

The community structure of testate amoebae inhabiting different microhabitats (soil and tree-moss) within a tropical forest biome in Nameri National Park, northeastern India, was investigated. A total of 33 testate amoebae species belonging to 13 genera were identified. Species belonging to the class Lobosea constituted 73% of total testate amoebae density in the soil habitat, whereas the class Filosea constituted the most dominant forms (58%) in the moist tree-moss habitat. The relative abundance of species was higher in the tree-moss habitat compared to the soil habitats of the forest. Although multivariate analysis suggested a significant difference in assemblage patterns between the habitats, the turnover in species (i.e., beta diversity) was insignificant. Species accumulation curves (SAC) constructed using both parametric and non-parametric species richness estimators revealed that the asymptote of species richness was achieved by a low number of sample replicates in both habitats. The temperature and pH of the substratum on testate amoebae distribution patterns suggest the importance of additional background factors on testate amoebae community structure. Further studies involving more biotopes, seasons, and trophic interactions are recommended to document a complete record of testate amoebae diversity and their interactions with environmental gradients in the tropical forest biomes of northeastern India.

Variation in mammal species richness and relative abundance in the Karoo

Understanding how climate change and land transformation may impact the distribution and diversity of wildlife species requires landscape-level foundational biodiversity surveys. The Karoo BioGaps Project aims to provide such data and to support the scientific assessment for shale gas development projects in the Karoo basin. In this paper we present the findings of the BioGaps mammal survey, which recorded medium and large mammals across twenty-five 1 km × 1 km sampling sites within the proposed fracking footprint using camera trapping techniques. We use sample rarefaction curves, non-parametric species richness estimators and non-metric multidimensional scaling plots to explore both species richness and community structure. We also used a generalised linear model to investigate how species diversity varies with both site-specific and landscape-level predictors. A total of 38 species were recorded at the majority of sites. Longitude (z = 4.018, p = 0.0005) emerged as the best predictor of species diversity across the study area, which we suggest is linked to the clear east–west aridity gradient. Together these results reveal the cosmopolitan distribution of the mammal taxa in the Karoo and could be used to inform decision-making linked to mining activities in the area.

Coral assemblages are structured along a turbidity gradient on the Southwestern Gulf of Mexico, Veracruz

Corals on the reef corridor of the southwestern Gulf of Mexico have evolved on a terrigenous shallow continental shelf under the influence of several natural river systems. As a result, water turbidity on these reefs can be high, with visibility as low as <1m, depending on reef location and season. Using a presence-absence species database from field surveys, literature search, and satellite data on sea surface temperature, turbidity and chlorophyll-a, the coral species composition and environmental variables were analyzed for the three main reef systems of the reef corridor of the southwestern Gulf of Mexico. Completeness of the data set was assessed using species accumulation curves and non-parametric estimators of species richness. Differences in coral assemblages’ composition between the reef systems were investigated using univariate (ANOVA) and multivariate (nMDS, ANOSIM, SIMPER) analyses and the relationship between the assemblages and environmental data was assessed using a forward selection process in canonical correspondence analysis (CCA) to eliminate non-significant environmental variables. The northern and central Veracruz reef systems share a similar number of coral species (p=0.78 mult. comp.) and both showed higher species richness than the southern system (p<0.001 mult. comp.). In terms of the assemblages’ structure, significant differences were found (ANOSIM R=0.3, p=0.001) with larger average dissimilitude between north-south (75.4% SIMPER) and central-south (74.2%) than north-central (27%) comparisons. Only environmental variables related to water turbidity and productivity were significant on the final CCA configuration, which showed a gradient of increasing turbidity from north to south. Reef geomorphology and the effect of turbidity help explain differences in coral assemblages’ composition. More studies are necessary to establish if turbidity could function as a refuge for future environmental stress. Each Veracruz reef system is at the same time unique and shares a pool of coral species. To protect these ecosystems it is necessary to effectively manage water quality and consider coral diversity on the reef corridor of the southwestern Gulf of Mexico.

Optimizing performance of nonparametric species richness estimators under constrained sampling.

Understanding the functional relationship between the sample size and the performance of species richness estimators is necessary to optimize limited sampling resources against estimation error. Nonparametric estimators such as Chao and Jackknife demonstrate strong performances, but consensus is lacking as to which estimator performs better under constrained sampling. We explore a method to improve the estimators under such scenario. The method we propose involves randomly splitting species‐abundance data from a single sample into two equally sized samples, and using an appropriate incidence‐based estimator to estimate richness. To test this method, we assume a lognormal species‐abundance distribution (SAD) with varying coefficients of variation (CV), generate samples using MCMC simulations, and use the expected mean‐squared error as the performance criterion of the estimators. We test this method for Chao, Jackknife, ICE, and ACE estimators. Between abundance‐based estimators with the single sample, and incidence‐based estimators with the split‐in‐two samples, Chao2 performed the best when CV < 0.65, and incidence‐based Jackknife performed the best when CV > 0.65, given that the ratio of sample size to observed species richness is greater than a critical value given by a power function of CV with respect to abundance of the sampled population. The proposed method increases the performance of the estimators substantially and is more effective when more rare species are in an assemblage. We also show that the splitting method works qualitatively similarly well when the SADs are log series, geometric series, and negative binomial. We demonstrate an application of the proposed method by estimating richness of zooplankton communities in samples of ballast water. The proposed splitting method is an alternative to sampling a large number of individuals to increase the accuracy of richness estimations; therefore, it is appropriate for a wide range of resource‐limited sampling scenarios in ecology.

Insights for selecting the most suitable nonparametric species-richness estimators for subtropical Brazilian Atlantic Forests

In large-scale biodiversity surveys, the observed species-richness inevitably underestimates the real species richness of a certain geographic region. Nonparametric estimators may be feasible tools for predicting the potential tree/shrub species richness using data from large-scale forest surveys that gather reliable information. In light of the many nonparametric estimators available in the literature, we evaluated their statistical performance (bias and precision) in estimating the γ-diversity of different forest types by comparing their estimates with theoretical total richness values. In addition, we investigated their behaviors on simulated data regarding the spatial distribution of species among sample plots (patchiness). To accomplish these tasks, we used data from a wide-ranging systematic forest survey conducted at 418 sample plots on three subtropical forest types located in a Brazilian hotspot. We established theoretical real tree/shrub species-richness values for each forest type from a vast and carefully revised database for the neotropics. Due to the considerable amount of species with restricted geographic distribution, the incidence-based estimators were shown to be more suitable than the abundance-based estimators for estimating γ-diversity, presenting the smaller overall combination of performance metrics. The abundance-based estimators (Chao1 and ACE) were notedly sensitive to different degrees of patchiness, especially to patchy species distributions. On the other hand, Jackknife1 and the sample-based extrapolation were less influenced by patchiness. Regardless of the differences in species composition and structures among forest types, the Jackknife2 estimator presented the best overall performance and quite accurate estimates for all the cases.

One hundred and seventy-five new species of Graphidaceae: closing the gap or a drop in the bucket?

Recent studies of the global diversity of the lichenized fungal family Graphidaceae suggest that there are a large number of species remaining to be discovered. No less than 640 species have been described since 2002, including 175 new species introduced in a collaborative global effort in a single issue in this journal. These findings suggest that the largest family of tropical crustose lichens may have an even higher number of species than Parmeliaceae. To estimate whether the discovery of 175 new species is a significant step forward in cataloguing extant diversity in this family, we employed a parametric method to predict global species richness of Graphidaceae using a GIS-based grid map approach. The model employs linear regression between observed species richness and sample score and vegetation composition per grid to predict individual grid species richness, and interpolation of species grid distributions to predict global species richness. We also applied a non-parametric species-area curve approach and non-parametric species richness estimators (Chao, Jackknife, Bootstrap) to compare the results from the different methods. Our approach resulted in a prediction of 4,330 species of Graphidaceae, including approximately 3,500 (sub-)tropical species in the core subfamilies Fissurinoideae, Graphidoideae, Redonographoideae, plus 125 species restricted to extratropical regions (outside the zone between 30° northern and 30° southern latitude) and 700 species in subfamily Gomphilloideae. Currently, nearly 2,500 species are known in the family, including species not yet formally described. Thus, our model suggests that even after describing 175 species in this issue and with another approximately 140 awaiting publication, the number of species still to be discovered and described is more than 1,800, and much work remains to be done to close this substantial gap. Based on our approach, we predict that most of this undiscovered diversity is to be found in Mexico, the northern Andean region, the eastern Amazon and central and southern Brazil, tropical West Africa, continental Southeast Asia, Indonesia, and Papua New Guinea.

Species richness of Cladocera (Crustacea: Branchiopoda) in the Western Ghats of Maharashtra and Goa (India), with biogeographical comments

We assessed the species richness of Cladocera of the Western Ghats and surrounding areas of Maharashtra and Goa. Data of 230 samples from about 80 localities collected between 2009 and 2013 revealed 51 species in six families. Non-parametric estimators of species richness, Chao 2 and Jackknife 2, estimated the real total at 58 and 63 species, suggesting a coverage of 80% of the total species of the area. This fauna was compared with that of other countries from the Oriental region and found to be relatively species-poor, which is not in line with the biodiversity rich area status of the Western Ghats. Reasons for this are unclear. Complementarity among the cladoceran faunas of different countries belonging to the Oriental region increased with latitude and altitude. Along with the complementarity index, a comparison of family and generic occurrences of Cladocera revealed that family-level representation was similar between countries but species occurrences (like Daphnia species) varied. The subgenus Daphnia was reported only from Nepal while Ctenodaphnia was common in all countries of the Indian region. Biogeographically, the fauna was mainly composed of wide-ranging tropical species, mixed with some rare Palaearctic elements. Only two species were endemic to India. Of another one, the closest relative lives in Y ucatan, Mexico, and thus has a tropical Amphi-Pacific distribution.

The water mites (Acari: Hydrachnidia) of the standing waters of Corsica, Sardinia and Sicily: review and new data

A compilation of our present knowledge of the water mites (Acari: Hydrachnidia) adapted to life in standing waters on the three large islands in the western Mediterranean (Corsica, Sardinia and Sicily) is provided. In addition to published data, this study deals with a rich volume of new material from recent field work, mostly deriving from intermittent ponds and pools, an extremely poorly investigated yet peculiar habitat type in the Mediterranean area. Species richness of water mites reported for the standing waters of the three islands amounts to 91 species. Out of the 47 species for which we present new distributional data, Hydrachna incisa Halbert, 1903, Hydrachna leegei Koenike, 1895, Piersigia limophila Protz, 1896, Hydryphantes crassipalpis Koenike, 1914 and Piona laminata (Thor, 1900) have not been recorded previously from the Mediterranean area. Most of these species were believed to have typical North European distributions. In addition to these, a further 13 species are recorded for the first time from the area covered. In total, 11 species are new for Italy, seven more are new for Sicily, three for Sardinia and seven for Corsica. Redescriptions are given of Axonopsis complanata (Müller, 1776) (A. graeca, nov. syn), Brachypoda baderi (reported for the first time after the original description from Abruzzo, Italy, synonymization with B. mutila rejected) and B. mutila (recorded for the first time outside Algeria with certainty). For each species, information is given on habitat preference and geographical distribution; the significance of the data is discussed under perspectives of zoogeography and nature protection. The completeness of our knowledge for the three investigated island is assessed using rarefaction curves and non-parametric estimators of species richness; while Sicily can be considered fairly well known, Corsica and Sardinia require further sampling to assess their water mite diversity.

Performance of species richness estimators across assemblage types and survey parameters

AbstractAimA raw count of the species encountered across surveys usually underestimates species richness. Statistical estimators are often less biased. Nonparametric estimators of species richness are widely considered the least biased, but no particular estimator has consistently performed best. This is partly a function of estimators responding differently to assemblage‐level factors and survey design parameters. Our objective was to evaluate the performance of raw counts and nonparametric estimators of species richness across various assemblages and with different survey designs.LocationWe used both simulated and published field data.MethodsWe evaluated the bias, precision and accuracy of raw counts and 13 nonparametric estimators using simulations that systematically varied assemblage characteristics (number of species, species abundance distribution, total number of individuals, spatial configuration of individuals and species detection probability), sampling effort and survey design. Results informed the development of an estimator selection framework that we evaluated with field data.ResultsWhen averaged across assemblages, most nonparametric estimators were less negatively biased than a raw count. Estimators based on the similarity of repeated subsets of surveys were most accurate and their accumulation curves appeared to reach asymptotes fastest. Number of species, species abundance distribution and effort had the largest effects on performance, ultimately by affecting the proportion of the species pool contained in a sample. Our estimator selection framework showed promising results when applied to field data.Main conclusionsA raw count of the number of species in an area is far from the best estimate of true species richness. Nonparametric estimators are less biased. Newer largely unused, estimators perform better than more well known and longer established counterparts under certain conditions. Given that there is generally a trade‐off between bias and precision, we believe that estimator variance, which is often not reported when presenting species richness estimates, should always be included.

Patterns of species richness and diversity of insects associated with cucurbit fruits in the southern part of Cameroon.

Patterns of species diversity and community structure of insects associated with fruits of domesticated cucurbits were investigated from January 2009 to 2011 in three localities from two agroecological zones in the southern part of Cameroon. Rarefaction curves combined with nonparametric estimators of species richness were used to extrapolate species richness beyond our own data. Sampling efforts of over 92% were reached in each of the three study localities. Data collected revealed a total of 66 insect morphospecies belonging to 37 families and five orders, identified from a set of 57,510 insects. The orders Diptera (especially Tephritidae and Lonchaeidae) and Hymenoptera (mainly Braconidae and Eulophidae) were the most important, in terms of both abundance and species richness on the one hand, and effects on agronomic performance on the other. Values for both the species diversity (Shannon and Simpson) and the species richness indices (Margalef and Berger–Parker) calculated showed that the insect communities were species-rich but dominated, all to a similar extent, by five main species (including four fruit fly species and one parasitoid). Species abundance distributions in these communities ranged from the Zipf–Mandelbrot to Mandelbrot models. The communities are structured as tritrophic networks, including cucurbit fruits, fruit-feeding species (fruit flies) and carnivorous species (parasitoids). Within the guild of the parasitoids, about 30% of species, despite their low abundance, may potentially be of use in biological control of important pests. Our field data contribute in important ways to basic knowledge of biodiversity patterns in agrosystems and constitute baseline data for the planned implementation of biological control in Integrated Pest Management.

Biodiversity analysis of true bug assemblages (Hemiptera, Heteroptera) in four habitats in the Garraf Natural Park (Barcelona, Spain).

With the aim of gaining insight into true bugs assemblages, and of giving tools to enhance environmental manager tasks, an analysis was made of the alpha and beta diversity of true bug assemblages in the NE Iberian Peninsula. The study took place during the years 1999, 2000, and 2001. The diversity of true bug assemblages among four typical Mediterranean plant communities (dry grassland, calcicolous rosemary scrub, kermes oak scrub, and evergreen oak forest) in a protected natural area was compared. In each plant community, a stratified sampling, taking into account plants with highest coverage percentage, was performed. Collections were performed monthly using direct observation plus beating or sweeping of the entomological net. Objectives were 1) to assess whether true bug assemblages are different in each plant community surveyed, by means of the analysis of their alpha and beta diversity, 2) to assess if any of the four true bug assemblages may be prioritized according to the biodiversity parameters studied. In total, 3,071 specimens, belonging to 12 families and 77 species were identified. Fifty percent of specimens collected belonged to only three species, and ∼33% of species was represented by only one or two individuals. In each Heteroptera assemblage, the distribution pattern of species frequency classes followed a lognormal model. Thirty-five percent of species represented by three or more specimens were found in only one plant community. Abundance, species richness, and diversity were found to be different for each true bug assemblage and along the year. Abundance was highest in the evergreen oak forest and in spring. Species richness and diversity were highest in the kermes oak scrub and in early summer. Nonparametric species richness estimators showed that completeness of species inventory was >80%. In the study zone, true bug diversity may be considered low medium. Our results show that true bugs assemblages are characteristic of specific plant communities, and thus, true bugs fit as candidate monitoring group in environmental and conservation management.

Diversidad alfa y beta de los artrópodos en diferentes ambientes del Parque Nacional Los Cardones, Salta (Argentina)

The essential role of the National Parks is to protect nature, in order to prevent the deterioration and loss of the ecosystem under protection. Very few records about the diversity of arthropods are known from Los Cardones National Park, where three eco-regions are protected: Puna and Monte eco-regions and the High Andean Grassland of the Yungas. Here, we aimed to compare the alpha and beta diversity of arthropods in these eco-regions, and to prove if sites from the same ecoregion, show greater similarity between them in their assemblages, than with sites of the other eco-regions. We also identified arthropod orders with higher species richness, and indicated the families that contribute the most to the registered beta diversity. Three sampling sites were established on each eco-region and the arthropods were sampled using pitfall traps and suction samples. We evaluated the obtained inventory through nonparametric estimators of species richness, and compared diversity among eco-regions through "diversity profiles" and "effective number of species". Beta diversity was assessed by different methods such as the Morisita Index, nonmetric multidimentional scaling analysis, a multiple permutation procedure, and a Similarity Percentage analysis. We recorded 469 spp/morphospecies and recognized three arthropod orders (spiders, dipterans and hymenopterans) that are diverse and abundant in the Park. Besides, the diversity in Los Cardones National Park was found to be high, but it was observed higher in the High Andean Grassland of the Yungas, and lower in the Puna. The inventory obtained was good, reached up to the 81% of the species richness estimated by nonparametric estimators. Each eco-region of the park showed a very particular arthropod community that was tested by a multi-response permutation procedure. The species turnover between eco-regions was high, so that the different environments of the protected area are contributing to the maintenance of the regional diversity of arthropods in the park. The assemblages of arthropods belonging to the same eco-region sites showed greater similarity among themselves than with those of more distant sites. This represents the first attempt for biodiversity studies in these areas, but more evaluations are required to detail on the possible climate change and human impacts in the ecosystem.

Detecting change in intertidal species richness on sandy beaches: calibrating across sampling designs

Detecting changes in the biodiversity of biotic communities is fundamental to evaluating ecological responses to anthropogenic and climatic drivers at multiple scales. Species richness, the simplest measure of biodiversity, can be strongly affected by sampling design, making comparisons among results of different studies challenging. We investigated the use of extrapolative species richness estimators to address these issues in comparing species richness results from two sampling designs that differed in area sampled for intertidal macroinvertebrates on exposed sandy beaches. The area sampled by the proportional area sampling design increased with beach width (0.4 m2–3.0 m2) across our sites. The area sampled by the fixed area sampling design (3.5 m2) was independent of intertidal width. To obtain datasets for comparisons, we simultaneously used these sampling designs on nested intertidal grids at seven sandy beaches in central and southern California, USA. Observed species richness differed significantly (p ≤ 0.05) between the two sampling designs and was consistently lower (3–10 species less) for the proportional area design compared to the fixed area design (8–35 vs. 12–38 species, respectively), except at the widest beach where sampling areas were most similar (3 m2 vs. 3.5 m2). All seven non-parametric species richness estimators provided higher estimates of richness for both designs (mean = 5.4 ± 3.8 species), but only four of the richness estimators reduced differences in richness obtained by the two designs to a non-significant level (p ≥ 0.05) across the sites. The ratio of richness values (proportional area/fixed area) obtained by the two designs was strongly correlated with sampling area for observed richness and four of the seven estimators, suggesting these estimators did not uniformly correct for sampling area. When we used an extrapolation of sample-based rarefaction to adjust for sampling area, differences in species richness between sampling designs were reduced (mean difference = 0.9 ± 3.1 species) to within the 95% CI at every site and estimated species richness did not differ significantly among designs. Our results suggest that use of the extrapolative sample-based rarefaction approach could provide a means of calibrating species richness among sampling designs that differ in area sampled. This approach could allow more robust analyses and enable comparisons of species richness data collected across larger temporal and spatial scales. Such comparisons will provide needed opportunities to evaluate the responses of biodiversity to larger scale effects of human impacts and climate change in coastal ecosystems.