Accounting for weather and time-of-day parameters when analysing count data from monitoring programs

Problems induced by heterogeneity in species and individuals detectability are now well recognized when analysing count data. Yet, most recent techniques developed to handle this problem are still hardly applicable to many monitoring schemes, and do not provide abundance estimates at the point count scale. Here, we show how using simple weather variables can be a useful surrogate to detect variability in species detectability. We further look for a potential bias or loss in statistical power based on count data while ignoring weather and time-of-day variables. We first used the French Breeding Bird Survey to test how each of the counts of the 97 most common breeding species was influenced by weather and time-of-day variables. We assessed how the estimation of each species response to fragmentation could be influenced by correcting counts with such variables. Among 97 species, 75 were affected by at least one of the five weather and time-of-day variables considered. Despite these strong influences, the relationship between species abundance and fragmentation was not biased when not controlling counts for weather and time-of-day variables and further found no improvement in statistical power when accounting for these variables. Our results show that simple variables can be very powerful to assess how species detectability is influenced by weather conditions but they are inconsistent with any specific bias due to heterogeneous detectability. We suggest that raw count data can be used without any correction in case the sources of variation in detectability could be considered independent to the factor of interest.     

Species richness estimation and determinants of species detectability in butterfly monitoring programmes

Abstract 1. Species richness is the most widely used biodiversity index, but can be hard to measure. Many species remain undetected, hence raw species counts will often underestimate true species richness. In contrast, capture–recapture methods estimate true species richness and correct for imperfect and varying detectability. 2. Detectability is a crucial quantity that provides the link between a species count and true species richness. For insects, it has hardly ever been estimated, although this is required for the interpretation of species counts. 3. In the Swiss butterfly monitoring programme about 100 transect routes are surveyed seven times a year using a highly standardised protocol. In July 2003, control observers made two additional surveys on 38 transects. Data from these 38 quadrats were analysed to see whether currently available capture–recapture models can provide quadrat‐specific estimates of species richness, and to estimate species detectability in relation to transect, observer, survey, region, and abundance. 4. Species richness over the entire season cannot be estimated using current capture–recapture methods. The species pool was open, preventing use of closed population models, and detectability varied by species, preventing use of current open population models. Assuming a closed species pool during two mid‐season (July) surveys, a Jackknife capture–recapture method was used that accounts for heterogeneity to estimate mean detectability and species richness. 5. In every case, more species were present than were counted. Mean species detectability was 0.61 (SE 0.01) with significant differences between observers (range 0.37–0.83). Species‐specific detection at time t+ 1 was then modelled for those species seen at t for three mid‐season surveys. Detectability averaged 0.50 (range 0.17–0.81) for individual species and 0.65, 0.44, and 0.42 for surveys. Abundant species were detected more easily, although this relationship explained only 5% of variation in species detectability. 6. These are important, although not entirely unexpected, results for species richness estimation of short‐lived animals. Raw counts of species may be misleading species richness indicators unless many surveys are conducted. Monitoring programmes should be calibrated, i.e. the assumption of constant detectability over dimensions of interest needs to be tested. The development of capture–recapture or similar models that can cope with both open populations and heterogeneous species detectability to estimate species richness should be a research priority.     

Using time‐of‐detection to evaluate detectability assumptions in temporally replicated aural count indices: an example with Ring‐necked Pheasants

ABSTRACT The validity of treating counts as indices to abundance is based on the assumption that the expected detection probability, E(p), is constant over time or comparison groups or, more realistically, that variation in p is small relative to variation in population size that investigators seek to detect. Unfortunately, reliable estimates of E(p) and var(p) are lacking for most index methods. As a case study, we applied the time‐of‐detection method to temporally replicated (within season) aural counts of crowing male Ring‐necked Pheasants (Phasianus colchicus) at 18 sites in southern Minnesota in 2007 to evaluate the detectability assumptions. More specifically, we used the time‐of‐detection method to estimate E(p) and var(p), and then used these estimates in a Monte Carlo simulation to evaluate bias‐variance tradeoffs associated with adjusting count indices for imperfect detection. The estimated mean detection probability in our case study was 0.533 (SE = 0.030) and estimated spatial variation in E(p) was 0.081 (95% CI: 0.057–0.126). On average, both adjusted (for) and unadjusted counts of crowing males qualitatively described the simulated relationship between pheasant abundance and grassland abundance, but the bias‐variance tradeoff was smaller for adjusted counts (MSE = 0.003 vs. 0.045, respectively). Our case study supports the general recommendation to use, whenever feasible, formal population‐estimation procedures (e.g., mark‐recapture, distance sampling, double sampling) to account for imperfect detection. However, we caution that interpreting estimates of absolute abundance can be complicated, even if formal estimation methods are used. For example, the time‐of‐detection method was useful for evaluating detectability assumptions in our case study and the method could be used to adjust aural count indices for imperfect detection. Conversely, using the time‐of‐detection method to estimate absolute abundances in our case study was problematic because the biological populations and sampling coverage could not be clearly delineated. These estimation and inference challenges may also be important in other avian surveys that involve mobile species (whose home ranges may overlap several sampling sites), temporally replicated counts, and inexact sampling coverage.     

Calculation of collated indices of abundance of butterflies based on monitored sites

Abstract.

• 1 The Butterfly Monitoring Scheme uses regular transect counts on fixed sites to establish annual indices of abundance of butterfly species in the United Kingdom. The annual change in collated index for each species has hitherto been calculated as a simple ratio between total counts summed over all participating sites.
• 2 A revised method for calculation of collated indices is proposed, which applies a logarithmic transformation to site values so as to downweight the influence on the index of the sites with greatest numbers of a species. Zero counts are handled comparably with non-zero values. An alternative method using geometric mean ratios is also examined.
• 3 Indices calculated using the logarithmic transformation are compared with those calculated using the traditional method. Two internal tests of dependency of collated indices on the sites with highest abundance are made. Another evaluation uses regression analysis for the effects of temperature and rainfall on collated indices of butterfly abundance.
• 4 The first internal test shows that logarithmic transformation reduces the dependence of the collated index on the sites of highest abundance for twenty-five out of twenty-seven species examined; while a second test shows a reduction for twenty-six out of forty-two species, and an increase for one species. The number of significant regressions on temperature variables increases with the use of the logarithmic transformation from 11% to 13% of tests made, and on rainfall from 10% to 11%.
• 5 The geometric mean ratio method introduces considerable biases in its treatment of zero values, for which a remedy is not available.
• 6 Although the revised collated indices calculated using logarithmic transformation are broadly comparable with traditionally calculated values, the reductions in dependency on sites with the most abundant populations render the revised indices less subject to perturbation due to local ‘noise’, and so more suitable for research on factors influencing butterfly abundance.

     

Monitoring butterfly abundance: beyond pollard walks

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability.     

Modelling variation in calling rates to develop a reliable monitoring method for the Australasian Bittern Botaurus poiciloptilus

Monitoring the abundance of cryptic species inevitably relies on the use of index methods. Unfortunately, detectability is often confounded by unidentified covariates. One such species is the critically endangered Australasian Bittern Botaurus poiciloptilus. Current monitoring relies upon the ability to count males based on the conspicuous breeding calls of males. However, as in many vocal species, calling rates vary spatially and temporally, making it necessary to account for this when using call counts to index abundance. We undertook 461 15‐min call counts of Australasian Bitterns, in a range of conditions, during two breeding seasons at Whangamarino wetland, New Zealand. We fitted a range of generalized linear mixed models to these data to determine which factors were the best predictors of calling rate per individual Bittern (CRPI), allowing us to make recommendations regarding the optimum time and conditions for monitoring. Bittern CRPI was predictable in terms of time of day, month, cloud cover, rainfall and certain moon parameters, but some spatial and temporal variation remained unexplained. Results showed that the best time to detect Australasian Bitterns was 1 h before sunrise, in September (austral spring), on a moonlit night with no cloud or rain. Such models are useful for identifying times and conditions when counts are the highest and least variable, and could be applied to any species or cue count monitoring method where detection depends on counting calling individuals. Results can be used to standardize index counts, or sensibly to adjust and compare counts from different times. Standardizing monitoring in this way can lead to the development of monitoring methods that have a greater power to show population changes across shorter time periods. Moreover, the use of modelling processes to estimate effect sizes creates potential for such methods to be applied in circumstances where monitoring conditions are rarely optimum and standardization creates logistical trade‐offs, something that is particularly common in studies of cryptic species.     

An integrated modeling approach to estimating Gunnison sage‐grouse population dynamics: combining index and demographic data

Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large‐scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short‐term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage‐grouse (Centrocercus minimus). The long‐term population index data available for Gunnison sage‐grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage‐grouse to be variable and slightly declining over the past 16 years.     

The line transect method for estimating densities of large mammals in a tropical deciduous forest: An evaluation of models and field experiments

We have evaluated techniques of estimating animal density through direct counts using line transects during 1988–92 in the tropical deciduous forests of Mudumalui Sanctuary in southern India for four species of large herbivorous mammals, namely, chital (Axis axis). sambar (Cervus unicolor). Asian elephant (Elephas maximus) and gaur (Bos gaurus) Density estimates derived from the Fourier Series and the Half-Normal models consistently had the lowest coefficient of variation. These two models also generated similar mean density estimates. For the Fourier Series estimator, appropriate cut-off widths for analyzing line transect data for the four species are suggested. Grouping data into various distance classes did not produce any appreciable differences in estimates of mean density or their variances, although model fit is generally better when data arc placed in fewer groups. The sampling effort needed to achieve a desired precision (coefficient of variation) in the density estimate is derived. A sampling effort of 800 km of transects returned a 10% coefficient of variation on estimate for ehital; for the other species a higher effort was needed to achieve this level of precision. There was no statistically significant relationship between detectability of a group and the size of the group for any species. Density estimates along roads were generally significantly different from those in the interior of the forest, indicating that road-side counts many not be appropriate for most species.     

Mammal indicator species for protected areas and managed forests in a landscape conservation area of northern India

There is a realization that managed forests and other natural areas in the landscape matrix can and must make significant contributions to biodiversity conservation. Often, however, there are no consistent baseline vegetation or wildlife data for assessing the status of biodiversity elements across protected and managed areas for conservation planning, nor is there a rapid and efficient means to acquire those data. We used a unified vegetation classification and simple animal sampling design to describe the patterns of abundance of selected mammals as indicator, or characteristic, species in different vegetation types and protected areas vs. managed forest units in the Terai Conservation Area (TCA) in northern Uttar Pradesh state, India. We quantified the relative abundance of 15 mammals of conservation concern from dung counts in vegetation sampling plots within 122 sample patches in 13 vegetation types and 4 management units. Assemblages of species differed both among vegetation types and among management units. Species assemblages in the two protected areas differed strongly from those in two managed forests. Grasslands in protected areas were the most species diverse among vegetation types and had several indicator species. Protected forests were dominated by chital (Axis axis) and nilgai (Boselaphus tragocamelus) in a second species group. A third species group in open grasslands and savannas in managed forests was characterized by cattle (Bos taurus) and Indian hare (Lepus nigricollis). Protected areas clearly are the core conservation area of the TCA for their relatively high habitat value and species diversity, and their protected status minimizes human disturbance. Impacts of human use are high in managed forests, indicating their compromised value for biodiversity conservation. Our simple assessment methodology gives managers a simple way to assess the status of important mammals across landscape conservation units.     

The ecology of a diatom community in a thermal stream

From 1964 to 1967 the annual variations in the relative abundance of diatoms in a thermal stream draining a hot spring were examined for changes in species diversity (H) and redundancy (R). Despite large seasonal changes in abundance and shifts in the species composition, the values in general did not deviate significantly from the calculated mean diversity value. This relative constancy of H was interpreted as an indication of diatom community stability. The species exhibited a characteristic pattern of seasonal abundance that is thought be to partially attributable to a light adaptation phenomenon. Three cores were obtained from the soft sediment of the spring and were analysed for diatom remains. The cores were dated by a pumice layer of known age and interpretations relative to the ontogeny of the diatom community added a significant time dimension to the yearly diatom analysis.     

Robustness and uncertainty in estimates of butterfly abundance from transect counts

Many butterfly populations are monitored by counting the number of butterflies observed while walking transects during the butterfly’s flight season. Methods for estimating population abundance from these transect counts are appealing because they allow rare populations to be monitored without capture–recapture studies that could harm fragile individuals. An increasingly popular method for estimating abundance from transect counts relies on strong assumptions about the counting process and the processes that govern butterfly population dynamics. Here, we study the statistical performance of this method when underlying model assumptions are violated. We find that estimates of population size are robust to departures from underlying model assumptions, but that the uncertainty in these estimates (i.e., confidence intervals) is substantially underestimated. Alternative bootstrap and Bayesian methods provide better measures of the uncertainty in estimated population size, but are conditional upon knowledge of butterfly detectability. Because of these requirements, a mixed approach that combines data from small capture–recapture studies with transect counts strikes the best balance between accurate monitoring and minimal injury to individuals. Our study is motivated by monitoring studies for St. Francis satyr (Neonympha mitchelli francisci), a rare and relatively immobile butterfly occurring only in the sandhills region of south-central North Carolina, USA.     

Effects of precipitation on parasite burden along a natural climatic gradient in southern Africa – implications for possible shifts in infestation patterns due to global changes

As a consequence of environmental change, it is expected that shifts in temperature and precipitation patterns will influence parasite communities and their hosts with unpredictable impact. Parasites play a vital role in ecosystems but there is only limited quantitative data which describe the effects of environmental parameters under natural conditions. We investigated the influence of rainfall, relative humidity and temperature on the prevalence, abundance and infection intensity of nematodes in southern Africa by studying the gastro‐intestinal helminth community of the striped mouse Rhabdomys pumilio. Along a precipitation gradient from the Cape of South Africa to northern Namibia we trapped 470 mice over a geographical distance of about 1400 km. Faecal egg counts of 439 sampled individuals and dissections of 161 gastro‐intestinal tracts revealed 15 different helminth species. The most abundant nematode species harboured in 62.6% of all infected mice were the oxyurid Syphacia obvelata followed jointly by two species (Heligmonina spira and Neoheligmonella capensis) of the subfamily Nippostrongylinae (43.7%). We found a significant positive correlation between mean annual precipitation (rainfall and relative humidity) and nematode infestation rates of animals and a negative correlation with temperature. In addition, we found associations between precipitation and different qualitative measurements of parasite burden (mean nematode species richness, mean number of nematode worms and infection intensity per individual host). The similarity in nematode species composition decreased with distance between all study sites. Our study indicates for the first time an association between climatic variables and parasite prevalence and abundance along a continuous natural climatic gradient in a small mammal. These results might be incorporated in the development of models which can predict possible threats for the balance of ecosystems and shifts in infestation patterns due to global changes.     

Sequencing our way to more accurate community abundance

Over the last two decades, there has been a huge increase in our understanding of microbial diversity, structure and composition enabled by high-throughput sequencing technologies. Yet, it is unclear how the number of sequences translates to the number of cells or species within the community. In some cases, additional observational data may be required to ensure relative abundance patterns from sequence reads are biologically meaningful. The goal of DNA-based methods for biodiversity assessments is to obtain robust community abundance data, simultaneously, from environmental samples. In this issue of Molecular Ecology Resources, Pierella Karlusich et al. (2022) describe a new method for quantifying phytoplankton cell abundance. Using Tara Oceans data sets, the authors propose the photosynthetic gene psbO for reporting accurate relative abundance of the entire phytoplankton community from metagenomic data. The authors demonstrate higher correlations with traditional optical methods (including microscopy and flow cytometry), using their new method, improving upon molecular abundance assessments using multicopy marker genes. Furthermore, to facilitate application of their approach, the authors curated a psbO gene database for accessible taxonomic queries. This is an important step towards improving species abundance estimates from molecular data and eventually reporting of absolute species abundance, enhancing our understanding of community dynamics.     

Timed surveys and transect walks as comparable methods for monitoring butterflies in small plots

Butterflies are widely used in biodiversity surveys, and several methods of relative abundance counts have been developed. The most frequently used linear transects are praised for a good replicability, but recently have been criticised for poor species detecting ability, especially for poorly visible or extremely sedentary species. As an alternative, timed surveys, based on zigzagging study sites and flexibly checking transient butterfly resources, have been proposed by some authors. We tested the utility of the two methods while studying the effect of restoration practices on butterfly assemblages in limestone quarries in the Czech Republic. Numbers of species and individuals detected per 10 min transect walk were compared with numbers of species and individuals detected during 10 min timed survey. Mobile and imperceptible species were compared in separate analyses as a measure of detection efficiency. More species and individuals per visit were recorded by timed surveys. No difference in detectability of mobile and imperceptible species between both methods used was observed. Whereas linear transects will probably remain the method of choice for long-term monitoring programs employing armies of recorders, timed surveys appear more appropriate for studies in which it is important to obtain the most comprehensive check-list of species occurring at study sites, which is often the case in conservation inventories in species rich regions with limited number of experienced researchers.     

Linking local ecological knowledge and habitat modelling to predict absolute species abundance on large scales

Assessing the spatial structure of abundance of a species is a basic requirement to carry out adequate conservation strategies. However, existing attempts to predict species abundance, particularly in absolute units and on large scales, are scarce and have led to weak results. In this work we present a scheme to obtain, in an affordable way, a predictive model of absolute animal abundance on large scales based on the modelling of data obtained from local ecological knowledge (LEK) and its calibration. To exemplify this scheme, we build and validate a predictive absolute abundance model of the endangered terrestrial tortoise Testudo graeca in Southeast Iberian Peninsula. For that purpose, we collected distribution and relative abundance data of T. graeca using a low cost methodology, such as LEK, by means of interviewing shepherds. The information from LEK was employed to build a predictive habitat-based model of relative abundance. The relative abundance model was transformed into an absolute abundance model by means of calibration with a classical absolute abundance sampling method such as distance sampling. The obtained absolute abundance model predicted the observed absolute abundances values well in independent locations when compared with other works (R ² = 36%) and thus can offer a cost-effective predictive ability. Our results show that reliable habitat-based predictive maps of absolute species abundance on regional scales can be obtained starting from low cost sampling methods of relative abundance, such as LEK, and its calibration.     

Accounting for differential migration strategies between age groups to monitor raptor population dynamics in the eastern Black Sea flyway

Migration counts can offer a cost-effective method for monitoring the state of migrant raptor populations. However, differential migration strategies between inexperienced juveniles and experienced non-juveniles are rarely accounted for when inferring population trends from raptor migration counts. Since 2011, the Batumi Raptor Count (BRC) monitors the autumn migration of more than 1 million raptors along the eastern Black Sea coast in the Republic of Georgia. We also systematically sampled age information to assess differential migration timing between age groups and estimate age-specific linear trends in abundance between 2011 and 2018 for eight focal species. In so doing we aimed (1) to reassess the global relevance of BRC counts for each species and the potential for monitoring abundance of juveniles and non-juveniles, and (2) to identify demographic changes underlying recent trends in overall abundance. We found that the mean annual passage of non-juveniles at Batumi represents at least 1% of the estimated global breeding population of five study species. As expected, counts of juveniles were more variable than counts of non-juveniles. Yet despite our short monitoring period our models had sufficient statistical power to detect changes in abundance of 10%/year or less for at least one age group in all species except Pallid Harrier Circus macrourus. Our results indicate stable abundance and demography for half of the study species. We also found strong and significant increases in the abundance of Black Kites Milvis migrans and Short-toed Eagles Circaetus gallicus that were primarily due to increasing numbers of non-juveniles. By contrast, juvenile Montagu's Harriers Circus pygargus and Booted Eagles Hieraaetus pennatus significantly decreased in abundance. The first decade of BRC surveys offers an important benchmark for monitoring raptor populations using the eastern African–Palearctic flyway in the 21st century. We discuss possible causes of the observed trends and hope our work will stimulate demographic monitoring at migration count sites.     

Estimating Detection Probabilities of Waterfowl Broods From Ground-Based Surveys

ABSTRACT Brood:pair ratios could provide an economical method for assessing spatial or temporal variation in waterfowl productivity, but such estimators are severely biased by incomplete detection of broods. We conducted 3 sequential counts of 1,357 waterfowl broods in northeastern North Dakota, USA, and used closed-population mark-recapture models to estimate total brood abundance while controlling for variation in detection probabilities (p). Blue-winged teal (Anas discors) broods had the lowest average detection probability (p = 0.305), whereas diving-duck broods had the highest average detectability (p = 0.571). Detection was generally highest in morning or evening, but temporal patterns varied among species and there was no survey window that maximized detection probabilities for all species. Detection probabilities averaged 0.108 (SD = 0.056) higher for an experienced observer versus an inexperienced observer. Detection probabilities were 0.044 higher for roadside versus walk-up surveys and increased with increasing brood size, total brood abundance, survey date, wind speed, temperature, cloud cover, and amount of time spent surveying each wetland. Detection probabilities declined with increasing wetland size and amount of tall peripheral vegetation. Our mark-recapture results indicated that a traditional unreplicated brood survey would have missed 67.5% of estimated broods, summed over all species. Use of closed-population mark-recapture techniques provided an effective method for reducing this bias and identifying and quantifying factors that reduce detection probabilities of waterfowl broods. We recommend that future brood surveys incorporate 2 or 3 temporally segregated replicate counts to allow for formal estimation of detection probabilities.     

Conservation value for birds of traditionally managed isolated trees in an agricultural landscape of Madagascar

Isolated trees have distinctive economic, social and cultural value for the Betsileo people living on the edge of the protected forest corridor between Ranomafana and Andringitra national parks, in South-East Madagascar. Many of these trees are Ficus spp., traditionally protected and respected. At the landscape level, they are isolated features in a heterogeneous mosaic, providing fruit, shade and aesthetic services in open cultivated areas. Within the current management system, isolated trees may also contribute significantly to the provision of ecological services by enhancing bird diversity in open areas outside the forest. We identified practices and values linked to isolated tree uses and management through ethnographic data collection. Bird presence and abundance were sampled by 338 point counts in isolated trees and open areas of the agricultural mosaic. Isolated trees were occupied by 18 out of 32 (56%) bird species in the agricultural mosaic, including 8 (25%) endemic forest species. Endemic forest birds were significantly more numerous in isolated trees than in open habitats, both in species richness and abundance (mean P value < 0.001). Overall bird species richness was significantly higher in open areas containing isolated trees, than in areas without isolated trees. Bird species richness in Ficus spp. was significantly higher than in other isolated tree species, although no differences were detected in abundance or within guilds. Community-based management of isolated trees may thus represent an opportunity for convergence between bird conservation goals outside protected areas and local management values and practices.     

Is pitfall trapping a valuable sampling method for grassland Orthoptera?

Common methods to assess diversity and abundance of Orthoptera are sweep netting, transect counts and box-quadrat sampling. Pitfall trapping, by contrast, is rarely used, and the value of this method is still being questioned. In 2008, we studied Orthoptera species richness and abundance in five vegetation types along a gradient of dune succession on the Baltic Sea island of Hiddensee (NE Germany) by comparing transect-count and pitfall-trapping data. Using transect counts, 12 species were detected in the study area. With pitfall traps, three chorto- and thamnobiont Ensifera species (C. dorsalis, M. roeselii and T. viridissima) were not caught at all, and it was only in low-growing and sparsely-vegetated grey dunes that all present species were detected. With pitfall traps, the proportion of present species recorded strongly declined with increasing height and density of the vegetation type. Assuming that transect counts are a good proxy for relative Orthoptera densities, densities ascertained by pitfall traps are strongly biased by vegetation structure and locomotive behaviour of the species. More than 80% of all individuals were caught in sparsely-vegetated grey dunes. Frequency patterns of the species also differed. Using pitfall traps, especially chortobiont species were significantly underrepresented. Qualitative and quantitative sampling of Orthoptera using pitfall traps seems only reasonable in habitats with low and sparse vegetation and a high proportion of geobiont species.     

Sampling communities of ground-foraging ants: Pitfall catches compared with quadrat counts in an Australian tropical savanna

The relative abundances of ant species captured in pitfall traps was compared with those obtained by direct counts in quadrats at a savanna site in Kakadu National Park, Northern Territory. Two measures of abundance in traps were used, one based on total numbers of ants, the other on species frequency of occurrence. All species commonly recorded in quadrats were collected in traps, and their relative abundances were highly correlated on all occasions. Of the 20 most common species in quadrats, five occurred with a significantly different (in all cases lower) frequency in pitfall traps, but these species represented only 1.8–3.1% of total quadrat counts. Results from quadrats and pitfall traps were particularly similar (r > 0.8) when species-were classified into functional groups. Frequency data from traps may sometimes overestimate the abundance of widespread, solitary foraging species (e.g. ‘Chelaner’ and Tetramorium spp.) and underestimate species with large colony sizes (e.g. Iridomyrmex spp.). Data based on total numbers of ants in traps may be more prone to distortion arising from species differences in locomotor behaviour. Species counts in traps could be scaled to reduce these distortions. The finding that pitfall traps gave results comparable with those from quadrat counts provides support for the use of pitfall traps in studies of Australian ant communities in open habitats.