Estimating species richness and catch per unit effort from boat electro‐fishing in a lowland river in temperate Australia

Abstract Biodiversity estimates are typically a function of sampling effort and in this regard it is important to develop an understanding of taxon‐specific sampling requirements. Northern hemisphere studies have shown that estimates of riverine fish diversity are related to sampling effort, but such studies are lacking in the southern hemisphere. We used a dataset obtained from boat electro‐fishing the fish community along an essentially continuous 13‐km reach of the Murrumbidgee River, Australia, to investigate sampling effort effects on fish diversity estimates. This represents the first attempt to investigate relationships between sampling effort and the detection of fish species in a large lowland river in Australia. Seven species were recorded. Species‐specific patterns in catch per unit effort were evident and are discussed in terms of solitary and gregarious species, recreational fishing and the monitoring of rare and threatened species. There was a requirement to sample substantial lengths of river to describe total species richness of the fish community in this river reach. To this end, randomly allocated sampling effort and use of species richness estimators produced accurate estimates of species richness without the requirement for excessive levels of effort. Twenty operations were required to estimate species richness at this site, highlighting the need for comparable studies of river fish communities in lowland rivers elsewhere in Australia and the southern hemisphere.     

Optimising sampling methods for small mammal communities in Neotropical rainforests

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Stable baselines of temporal turnover underlie high beta diversity in tropical arthropod communities

While the high species diversity of tropical arthropod communities has often been linked to marked spatial heterogeneity, their temporal dynamics have received little attention. This study addresses this gap by examining spatio‐temporal variation in the arthropod communities of a tropical montane forest in Honduras. By employing DNA barcode analysis and Malaise trap sampling across 4 years and five sites, 51,596 specimens were assigned to 8,193 presumptive species. High beta diversity was linked more strongly to elevation than geographic distance, decreasing by 12% when only the dominant species were considered. When sampling effort was increased by deploying more traps at a site, beta diversity only decreased by 2%, but extending sampling across years decreased beta diversity by 27%. Species inconsistently detected among years, likely transients from other settings, drove the low similarity in species composition among traps only a few metres apart. The dominant, temporally persistent species substantially influenced the cyclic pattern of change in community composition among years. This pattern likely results from divergence–convergence dynamics, suggesting a stable baseline of temporal turnover in each community. The overall results establish that large sample sizes are necessary to reveal species richness, but are not essential for quantifying beta diversity. This study further highlights the need for standardized methods of sampling and species identification to generate the comparative data required to evaluate biodiversity change in space and time.     

The challenge of accurately documenting bee species richness in agroecosystems: bee diversity in eastern apple orchards

Bees are important pollinators of agricultural crops, and bee diversity has been shown to be closely associated with pollination, a valuable ecosystem service. Higher functional diversity and species richness of bees have been shown to lead to higher crop yield. Bees simultaneously represent a mega‐diverse taxon that is extremely challenging to sample thoroughly and an important group to understand because of pollination services. We sampled bees visiting apple blossoms in 28 orchards over 6 years. We used species rarefaction analyses to test for the completeness of sampling and the relationship between species richness and sampling effort, orchard size, and percent agriculture in the surrounding landscape. We performed more than 190 h of sampling, collecting 11,219 specimens representing 104 species. Despite the sampling intensity, we captured <75% of expected species richness at more than half of the sites. For most of these, the variation in bee community composition between years was greater than among sites. Species richness was influenced by percent agriculture, orchard size, and sampling effort, but we found no factors explaining the difference between observed and expected species richness. Competition between honeybees and wild bees did not appear to be a factor, as we found no correlation between honeybee and wild bee abundance. Our study shows that the pollinator fauna of agroecosystems can be diverse and challenging to thoroughly sample. We demonstrate that there is high temporal variation in community composition and that sites vary widely in the sampling effort required to fully describe their diversity. In order to maximize pollination services provided by wild bee species, we must first accurately estimate species richness. For researchers interested in providing this estimate, we recommend multiyear studies and rarefaction analyses to quantify the gap between observed and expected species richness.     

Are there pitfalls to pitfalls? Dung beetle sampling in French Guiana

Dung beetles have widely been accepted as cost-effective indicator taxa for biodiversity assessment; thus, standard protocols have been created to examine their species richness and diversity in many habitats. However, the vast majority of studies adopt short-term sampling protocols; few studies have quantified sampling efficiency at longer time scales or tested the efficacy of species richness estimates. Here we present long- and short-term sampling data from two regions of French Guiana: the Nouragues Tropical Forest Research Station and Kaw Mountain. We examine species richness and diversity, and use these data to make suggestions for future biodiversity assessments of dung beetles using dung baited pitfall transects. Species richness estimates based on short-term samples strongly underestimate the actual species richness by approximately 40?%. Duration of trapping was found to be more important than the number of traps and length of transects; by setting a second transect (4-day sample period) in the same habitat of Nouragues, thereby increasing the sample duration, the number of species increased by 14?%.     

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

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-to-individual 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.     

Mite (Acari; Arachnida) diversity of two native plants in fragments of a semideciduous seasonal forest in Brazil

Studies to determine mite species richness in natural environments are still scarce, and have been conducted mainly in tropical ecosystems. The aim of this study was to determine the species richness of mites on two common native plants in fragments of the semideciduous seasonal forest in the Northwest of São Paulo State, Brazil. In each of eight fragments, 10 specimens of Actinostemon communis (Euphorbiaceae) and 10 of Trichilia casaretti (Meliaceae) were selected and marked. In total, 124 species of mites belonging to 21 families were found on the two plants. Tarsonemidae had the highest diversity (34 species), followed by Phytoseiidae (31), Tetranychidae (9) and Tenuipalpidae (8). Species accumulation curves for the two sampled plants did not reach an asymptote, even with the large sampling effort. Hence, it is estimated that a greater sampling effort may lead to an increase in species richness compared with what was found in this study. The richness of this mite fauna suggests that preservation of these plant species is important to maintain the mite diversity in these forest fragments.     

Evaluating outcomes of restoration ecology projects on limited budgets: assessment of variation in sampling intensity and sampling frequency for four habitat types

While best practices for evaluating restoration ecology projects are emerging rapidly, budget constraints often limit postrestoration monitoring, which emphasizes the need for practical and efficient monitoring strategies. We examined the postrestoration outcome for an ENGO (Nature Conservancy of Canada) project, to assess retroactively how variation in intensity and frequency of sampling would have affected estimates of plant species composition, diversity, and richness over time. The project restored four habitat types (mesic forest, oak woodland, wet meadow, and sand barren) using sculptured seeding of tallgrass prairie and woody species. Species‐level plant cover was monitored annually for 10 years in 168 2 × 2–m quadrats. We performed randomization tests to examine estimates of species diversity and richness as a function of the number of quadrats sampled, and assessed the necessity of annual sampling for describing changes in species composition and successional trajectories. The randomization tests revealed that sampling 10–17 quadrats, depending on habitat type, was sufficient to obtain estimates of species diversity that were at least 95% of values obtained from the whole dataset. Species richness as a function of number of quadrats sampled did not plateau, which suggests that rather than increasing the number of sampling quadrats, richness could be estimated more efficiently using nonquadrat based sampling techniques. Nonmetric multidimensional scaling analysis revealed that plant species composition largely stabilized by 3–5 years postrestoration depending on habitat type. By that time, native, seeded species dominated the restoration, and the benefits of annual sampling for tracking changes in species composition diminished.     

Body size and measurement of species diversity in large grazing mammals

Species are by definition different from each other. This fact favours ranking rather than additive indices. However, ecologists have measured species diversity in terms of species richness, or by combining species richness with the relative abundance of species within an area. Both methods raise problems: species richness treats all species equally, while relative abundance is not a fixed property of species but varies widely temporally and spatially, and requires a massive sampling effort. The functional aspect of species diversity measurement may be strengthened by incorporating differences between species such as body size as a component of diversity. An index of diversity derived from a measure of variation in body size among species is proposed for large grazing mammals. The proposed diversity index related positively to species abundance, indicating that the use of body size as a surrogate for diversity is adequate. Because the proposed index is based on presence or absence data, the expensive and time consuming counting of individuals per species in each sampling unit is not necessary.     

Seasonal Change of Species Diversity Patterns of Non‐volant Small Mammals along Three Subtropical Elevational Gradients

Our understanding of geographic patterns of species diversity and the underlying mechanisms is increasing rapidly, whereas the temporal variation in these patterns remains poorly understood. We examined the seasonal species richness and species turnover patterns of non‐volant small mammals along three subtropical elevational gradients in southwest China. Small mammal diversity was surveyed in two seasons (early wet season and late wet season) using a standardized sampling protocol. The comparison of species richness patterns between two seasons indicated a temporal component in magnitude and shape, with species richness at high elevations clearly increased during the late wet season. Species richness demonstrated weak correlations with modelled temperature and precipitation. The elevational pattern of species turnover measured by Chao‐Sørenson similarity index also changed seasonally, even though the temporal pattern varied with scale. Species turnover between neighboring elevations at high elevations was slower in the late wet season. Meanwhile, there was an acceleration of species turnover along the whole range of the gradient. The seasonal change in species diversity patterns may be due to population‐level increases in abundance and elevational migration, whereas seasonal variation in factors other than temperature and precipitation may play a greater role in driving seasonal diversity patterns. Our study strongly supports the seasonality in elevational patterns of small mammal diversity in subtropical montane forests. Thus it is recommended that subsequent field surveys consider temporal sampling replicate for elevational diversity studies.     

Constant tree species richness along an elevational gradient of Mt. Bokor,a table-shaped mountain in southwestern Cambodia

Some previous studies along an elevational gradient on a tropical mountain documented that plant species richness decreases with increasing elevation. However, most of studies did not attempt to standardize the amount of sampling effort. In this paper, we employed a standardized sampling effort to study tree species richness along an elevational gradient on Mt. Bokor, a table-shaped mountain in southwestern Cambodia, and examined relationships between tree species richness and environmental factors. We used two methods to record tree species richness: first, we recorded trees taller than 4 m in 20 uniform plots (5 × 100 m) placed at 266–1048-m elevation; and second, we collected specimens along an elevational gradient from 200 to 1048 m. For both datasets, we applied rarefaction and a Chao1 estimator to standardize the sampling efforts. A generalized linear model (GLM) was used to test the relationship of species richness with elevation. We recorded 308 tree species from 20 plots and 389 tree species from the general collections. Species richness observed in 20 plots had a weak but non-significant correlation with elevation. Species richness estimated by rarefaction or Chao1 from both data sets also showed no significant correlations with elevation. Unlike many previous studies, tree species richness was nearly constant along the elevational gradient of Mt. Bokor where temperature and precipitation are expected to vary. We suggest that the table-shaped landscape of Mt. Bokor, where elevational interval areas do not significantly change between 200 and 900 m, may be a determinant of this constant species richness.     

Subsampling Herbarium Collections to Assess Geographic Diversity Gradients: A Case Study with Endemic Orchidaceae and Rubiaceae in Cameroon

We compiled herbarium specimen data to provide an improved characterization of geographic patterns of diversity using indices of species diversity and floristic similarity based on rarefaction principles. A dataset of 3650 georeferenced plant specimens belonging to Orchidaceae and Rubiaceae endemic to Atlantic Central Africa was assembled to assess species composition per half‐degree or one‐degree grid cells. Local diversity was measured by the expected number of species (S_k) per grid cell found in subsamples of increasing size and compared with raw species richness (S_R). A nearly unbiased estimator of the effective number of species per grid cell was also used, allowing quantification of ratios of ‘true diversity’ between grid cells. Species turnover was measured using a presence/absence‐based similarity index (Sørensen) and an abundance‐based index that corrects for sampling bias (NNESS). Our results confirm that the coastal region of Cameroon is more diverse in endemic species than those more inland. The southern part of this coastal forest is, however, as diverse as the more intensively inventoried northern part, and should also be recognized as an important center of endemism. A strong congruence between Sørensen and NNESS similarity matrices lead to similar delimitations of floristic units. Hence, heterogeneous sampling seems to confer more bias when measuring patterns of local diversity using raw species richness than species turnover using Sørensen index. Overall, we argue that subsampling methods represent a useful way to assess diversity gradients using herbarium specimens while correcting for heterogeneous sampling effort. Abstract in French is available in the online version of this article.     

Community assessment techniques and the implications for rarefaction and extrapolation with Hill numbers

Diversity estimates play a key role in ecological assessments. Species richness and abundance are commonly used to generate complex diversity indices that are dependent on the quality of these estimates. As such, there is a long‐standing interest in the development of monitoring techniques, their ability to adequately assess species diversity, and the implications for generated indices. To determine the ability of substratum community assessment methods to capture species diversity, we evaluated four methods: photo quadrat, point intercept, random subsampling, and full quadrat assessments. Species density, abundance, richness, Shannon diversity, and Simpson diversity were then calculated for each method. We then conducted a method validation at a subset of locations to serve as an indication for how well each method captured the totality of the diversity present. Density, richness, Shannon diversity, and Simpson diversity estimates varied between methods, despite assessments occurring at the same locations, with photo quadrats detecting the lowest estimates and full quadrat assessments the highest. Abundance estimates were consistent among methods. Sample‐based rarefaction and extrapolation curves indicated that differences between Hill numbers (richness, Shannon diversity, and Simpson diversity) were significant in the majority of cases, and coverage‐based rarefaction and extrapolation curves confirmed that these dissimilarities were due to differences between the methods, not the sample completeness. Method validation highlighted the inability of the tested methods to capture the totality of the diversity present, while further supporting the notion of extrapolating abundances. Our results highlight the need for consistency across research methods, the advantages of utilizing multiple diversity indices, and potential concerns and considerations when comparing data from multiple sources.     

Use of invertebrate traits for the biomonitoring of European large rivers: the effects of sampling effort on genus richness and functional diversity

1. Studies on biodiversity and ecosystem function require considering metrics for accurately describing the functional diversity of communities. The number of taxa (richness) is commonly used to characterise biological diversity. The disadvantage of richness as a measure of biological diversity is that all taxa are taken into account on an equal basis regardless of their abundance, their biological characteristics or their function in the ecosystem. 2. To circumvent this problem, we applied a recently described measure of biological diversity that incorporates dissimilarities among taxa. Dissimilarities were defined from biological traits (e.g. life history, morphology, physiology and behaviour) of stream invertebrate taxa and the resulting biological diversity index was considered as a surrogate for functional diversity. 3. As sampling effort is known to affect the number of taxa collected within a reach, we investigated how change in functional diversity is affected by sampling effort. We used stream invertebrate community data from three large European rivers to model accumulation curves and to assess the number of samples required to estimate (i.e. closeness to the maximal value) functional diversity and genera richness. We further evaluated the precision of estimates (i.e. similarity of temporal or spatial replicates) of the total functional diversity. 4. As expected, richness estimates were strongly dependent on sampling effort, and 10 replicate samples were found to underestimate actual richness. Moreover, richness estimates showed much variation with season and location. In contrast, functional diversity had greater accuracy with less sampling effort and the precision of the estimates was higher than richness both across sampling occasions and sampling reaches. These results are further arguments towards conducting research on the design of a biomonitoring tool based on biological traits.     

Species–area and species–sampling effort relationships: disentangling the effects

Species numbers tend to increase with both the area surveyed (species–area relationship, SAR) and the number of samples taken (species–sampling effort relationship, SSER). These two relationships differ in their nature and underlying mechanisms but are not clearly distinguished in field studies. To discriminate the effects of area (spatial extent) and sampling effort (SE) on species richness, several models explicitly involving both variables were proposed and tested against 13 datasets from marine micro‐, meio‐ and macrobenthos. A combination of power SSER and piecewise power SAR terms was found to have the best fit. The effects of area and SE were both significant, but the former one was noticeably weaker. The SSERs were roughly linear in log‐log space, whereas the SARs demonstrated scale‐dependent behavior with a noticeable threshold (slope breakpoint). Species richness was almost area‐independent below this threshold (the “small area effect”, SAE) but followed typical power‐law SAR beyond the threshold. This effect was similar to the “small island effect” but occurred for arbitrarily delineated areas within continuous habitats. Parameters of the SAR curves depended on organism size. The upper limit of the SAE increased from microorganisms to meiofauna to macrofauna. Also, SAR curves for unicellular groups had significantly lower slopes. SAE is supposed to indicate a spatial range of statistical homogeneity in species composition. Its upper limit corresponds to the characteristic size of a local community (a single habitat occupied by a common species pool). Interpretations of SAR and SSER parameters in terms of α‐ and β‐diversity are proposed. Both SAR and SSER slopes obtained from univariate regressions are overestimated. This upward bias depends on sampling design, decreasing for SAR but increasing for SSER with more unequally spaced samples. Both spatial extent and sampling effort should be taken into account to disentangle properly their effects on diversity.     

Rapid assessment in conservation research: a critique of avifaunal assessment techniques illustrated by Ecuadorian and Madagascan case study data

The urgency of conservation concerns in the tropics, linked with the limitations imposed on research efforts by the tropical environment has resulted in the development of methods for rapid assessment of biological communities. One such method, the MacKinnon list technique, has been increasingly applied in avifaunal surveys worldwide. Using paired tropical bird data sets from Ecuadorian cloud forest and Madagascan littoral forest, we compare the performance of the MacKinnon list with that of the more standard method of point counts in indicating when a site has been adequately surveyed, estimating the magnitude of species richness, quantifying relative species abundance, and providing an α‐index of diversity. In species‐rich Ecuadorian cloud forest, neither method produced data indicating adequate survey effort, despite extensive sampling, whereas in the relatively species‐poor Madagascan littoral forests, data collected by both methods indicated that the area had been sufficiently surveyed with comparable sampling effort. Species richness estimates generated from MacKinnon list data provided a more accurate estimate of the magnitude of the species richness for the Ecuadorian avifauna, whereas estimates for the Madagascan avifauna stabilised with relatively few samples using either method. Data collected by each method reflected different patterns of relative abundance among the five most abundant species, with MacKinnon list data showing a bias towards solitary and territorial species and against monospecific flocking species relative to the point count data. As a consequence of this bias, MacKinnon list data also fail to reflect accurately the structure of communities as quantified by an index of community evenness. Point counts, on the other hand, failed to capture the full species complement of the species‐rich Ecuadorian study area. As techniques for the rapid assessment of unsurveyed areas, both methods are subject to biases that limit their value, if used alone, in collecting data of scientific and management value. We propose a hybrid rapid assessment methodology that capitalises on the strengths of both techniques while compensating for their weaknesses.     

Quantifying rotifer species richness in temperate lakes

1. Biodiversity assessments of lakes depend on the ability to identify the complement of species present, although the degree of sampling required is often uncertain. We utilise long‐term data to predict rotifer species richness in three habitats in three Polish lakes using rarefaction sampling methods. 2. Richness in littoral and psammon habitats did not saturate, even with up to 130 samples. Highest richness was observed in psammon habitat (119 species) in Lake Mikolajskie, followed by littoral habitat in Lakes ?uknajno (114 species) and Kuc (110 species). Littoral habitats in Lakes ?uknajno (56%) and Kuc (51%) had the most species not shared with other habitats in the same lake. 3. Species richness (Chao2) estimates ranged between 44 for pelagic and 135 for psammon habitat in Lake Mikolajskie, to 100 for psammon and 137 for littoral habitat in Lake Kuc, and 65 for pelagic and 162 for littoral habitat in Lake ?uknajno. Whole lake estimates were 167, 205 and 171 species, respectively, for these lakes, higher than the 150 to 160 species predicted by Dumont and Segers (Hydrobiologia, 1996, 341 , 125). 4. Using standardised sampling, richness was significantly higher in littoral than either pelagic or psammon habitats. Contrasts of standardised rarefaction curves revealed that richness in Lakes Kuc and Mikolajskie was described as well by littoral‐only or psammon‐only samples, respectively, as by those randomly drawn from across all habitats in the lake. 5. Species richness estimates for Lake Mikolajskie were highest in summer, followed by autumn and spring. Interannual estimates differed by up to 427%, nearly an order of magnitude greater than maximal seasonal variation of 70%. 6. Results indicate that much higher sampling intensity is required to establish species richness than is presently carried out in most lakes. Because many species can be detected only with very intensive sampling, conservation programmes must consider sampling intensity when designing studies.     

Cannot see the diversity for all the species: Evaluating inclusion criteria for local species lists when using abundant citizen science data

Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α‐ and β‐diversity estimates to the use raw versus detection‐corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence‐only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α‐ and β‐diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.     

Multi‐scale responses of plant species diversity in semi‐natural buffer strips to agricultural landscapes

Question: How does agricultural land usage affect plant species diversity in semi‐natural buffer strips at multiple scales? Location: Lepsämä River watershed, Nurmijärvi, Southern Finland. Methods: Species diversity indicators included both richness and evenness. Plant communities in buffer strips were surveyed in 29 sampling sites. Using ArcGIS Desktop 9.0 (ArcInfo) and Fragstats 3.3 for GIS analysis, the landscape composition around each sampling site was characterized by seven parameters in square sectors at five scales: 4, 36, 100, 196, and 324ha. For each scale, Principle Component Analysis was used to examine the importance of each structural metric to diversity indicators using multiple regression and other simple analyses. Results: For all but the smallest scales (4 ha), two structural metrics including the diversity of land cover types and percentage of arable land were positively and negatively correlated with species richness, respectively. Both metrics had the highest correlation coefficients for species richness at the second largest scale (196 ha). The density of arable field edges between the fields was the only metric that correlated with species evenness for all scales, which had highest predictive power at the second smallest scale (36 ha). Conclusions: Species richness and evenness of buffer strips had scale‐dependent relationships to land use in agricultural ecosystems. The results of this study indicated that species richness depends on the pattern of arable land use at large scales, which may relate to the regional species pool. Meanwhile, species evenness depended on the level of field edge density at small scales, which relates to how the nearby farmland was divided by the edges (e.g. many small‐scale fields with high edge density or a few big‐scale fields with low edge density). This implies that it is important to manage the biodiversity of buffer strips within a landscape context at multiple scales.