Use of sonar transects to improve efficiency and reduce potential bias in visual surveys of reef fishes

A sonar transect method has been found to be a useful alternative to traditional tape-transect methods in quantification of the species richness and abundance of reef fish. No significant difference was found between species richness measured by the methods, and high Jaccard’s similarity coefficients were calculated for each site using the two methods, indicating a similar response to fish of both the sonar and tape transects. Abundance estimates of one species only (Chaetodon tricinctus) were greater when the transect tape method was used, probably because fish were being attracted to the divers who deployed the transect tape. Substantial time saving was also noted for the sonar transects, indicating overall that estimating distance using sonar rather than transect tape may enable increased efficiency and accuracy in␣underwater visual surveys for both ecological␣and management-related research on reef fishes.     

Sample size and sampling error in geometric morphometric studies of size and shape

Geometric morphometric studies are increasingly becoming common in systematics and palaeontology. The samples in such studies are often small, due to the paucity of material available for analysis. However, very few studies have tried to assess the impact of sampling error on analytical results. Here, this issue is addressed empirically using repeated randomized selection experiments to build progressively smaller samples from an original dataset of ∼400 vervet monkey (Cercopithecus aethiops) skulls. Size and shape parameters (including mean size and shape, size and shape variances, angles of allometric trajectories) that are commonly used in geometric morphometric studies, are estimated first in the original sample and then in the random subsamples. Estimates are then compared to give an indication of what is the minimum desirable sample size for each parameter. Mean size, standard deviation of size and variance of shape are found to be fairly accurate even in relatively small samples. In contrast, mean shapes and angles between static allometric trajectories are strongly affected by sampling error. If confirmed in other groups, our findings may have substantial implications for studies of morphological variation in present and fossil species. By performing rarefaction analyses like those presented in our study, morphometricians can be easily provided with important clues on how a simple but crucial factor like sample size can alter results of their studies.     

Median estimation of chemical constituents for sampling on two occasions under a log‐normal model

Sampling from a finite population on multiple occasions introduces dependencies between the successive samples when overlap is designed. Such sampling designs lead to efficient statistical estimates, while they allow estimating changes over time for the targeted outcomes. This makes them very popular in real‐world statistical practice. Sampling with partial replacement can also be very efficient in biological and environmental studies where estimation of toxicants and its trends over time is the main interest. Sampling with partial replacement is designed here on two occasions in order to estimate the median concentration of chemical constituents quantified by means of liquid chromatography coupled with tandem mass spectrometry. Such data represent relative peak areas resulting from the chromatographic analysis. They are therefore positive‐valued and skewed data, and are commonly fitted very well by the log‐normal model. A log‐normal model is assumed here for chemical constituents quantified in mainstream cigarette smoke in a real case study. Combining design‐based and model‐based approaches for statistical inference, we seek for the median estimation of chemical constituents by sampling with partial replacement on two time occasions. We also discuss the limitations of extending the proposed approach to other skewed population models. The latter is investigated by means of a Monte Carlo simulation study.     

Biological variables as soil quality indicators: Effect of sampling time and ability to classify soils by their suitability

Soil biological variables are considered good soil quality indicators due to their high sensitivity and ability to reflect soil management effects. However, they frequently show high temporal variability. Our objectives were: (a) to analyze temporal stability and seasonal effect on biological variables, (b) to choose between autumn and spring to sample for soil biological variables, and (c) to determine biological variables able to discriminate among selected soil subgroups. Areas with minimal human disturbance were sampled in three soil orders (Mollisol, Vertisol and Alfisol) during two and a half years, each autumn and spring. Microbial biomass C and N (MBC, MBN), basal respiration (Resp), metabolic quotient (qCO₂), potential of N mineralization (PNM-AI), soil organic C (TOC) and total soil N (TON) were measured in three composite soil samples collected from homogeneous areas at 0–15 cm depth. For the studied soils, selected soil biological variables presented different levels depending on the time of sampling, spring or autumn. Hence, the importance of pointing out the time of sampling to report results of these variables in this kind of studies is remarked. In general, biological variables presented higher stability when we sampled soils in autumn compared to spring. Because of this, we used autumn soil samples to determine the best soil biological variables to discriminate among selected subgroups of soils. The separation of soil subgroups by means of discriminant analysis using just TOC and TON was scrutinized, considering that these soil variables are routinely measured in soil test laboratories. Nonetheless they were not able to discriminate properly among soil subgroups because they showed high error rates classifying the samples in the correct subgroups. In contrast, the variables PMN-AI, MBC, and MBN adequately discriminated the five soil subgroups. From the biological variables, PMN-AI and MBC were the best ones to characterize (discriminate) among the five soil subgroups. Particularly, PMN-AI was able to separate soils by their suitability for agricultural purposes.     

捕获-再捕获抽样中的多元组合估计量

首先介绍了捕获-再捕获抽样的思想方法以及Peterson估计量与性质,然后指出了Peterson估计量存在的问题,在此基础上给出了多元组合估计量并研究了它的性质.     

Scale specific determinants of tree diversity in an old growth temperate forest in China

The major processes generating pattern in plant community composition depend upon the spatial scale and resolution of observation, therefore understanding the role played by spatial scale on species patterns is of major concern. In this study, we investigate how well environmental (topography and soil variables) and spatial variables explain variation in species composition in a 25-ha temperate forest in northeastern China. We used new variation partitioning approaches to discover the spatial scale (using multi-scale spatial PCNM variables) at which environmental heterogeneity and other spatially structured processes influence tree community composition. We also test the effect of changing grain of the study (i.e. quadrat size) on the variation partitioning results. Our results indicate that (1) species composition in the Changbai mixed broadleaf-conifer forest was controlled mainly by spatially structured soil variation at broad scales, while at finer scales most of the explained variation was of a spatial nature, pointing to the importance of biotic processes. (2) These results held at all sampling grains. However, reducing quadrat size progressively reduced both spatially and environmentally explained variance. This probably partly reflects increasing stochasticity in species abundances, and the smaller proportion of quadrats occupied by each species, when quadrat size is reduced. The results suggest that environmental heterogeneity (i.e. niche processes) and other biotic processes such as dispersal work together, but at different spatial scales, to build up diversity patterns.     

Toward an optimal sampling protocol for Hemiptera on understorey plants

There are no standardised sampling protocols for inventorying Hemiptera from understorey or canopy plants. This paper proposes an optimal protocol for the understorey, after evaluating the efficiency of seven methods to maximise the richness of Hemiptera collected from plants with minimal field and laboratory time. The methods evaluated were beating, chemical knockdown, sweeping, branch clipping, hand collecting, vacuum sampling and sticky trapping. These techniques were tested at two spatial scales: 1 ha sites and individual plants. In addition, because efficiency may differ with vegetation structure, sampling of sites was conducted in three disparate understorey habitats, and sampling of individual plants was conducted across 33 plant species. No single method sampled the majority of hemipteran species in the understorey. Chemical knockdown, vacuum sampling and beating yielded speciose samples (61, 61 and 30 species, respectively, representing 53, 53 and 26% of total species collected). The four remaining methods provided species-poor samples (<18 species or <16% of total species collected). These methods also had biases towards particular taxa (e.g., branch clipping and hand collecting targeted sessile Hemiptera, and sticky trapping were dominated by five species of Psyllidae). The most time-efficient methods were beating, sweeping and hand collecting (200 minutes of field and laboratory time yielded >7 species for each technique). By comparison, vacuum sampling, sticky trapping, branch clipping and chemical knockdown yielded <5 species for the same period. Chemical knockdown had further disadvantages; high financial cost and potential spray drift. The most effective methods for a standardised sampling protocol to inventory Hemiptera from the understorey are beating and vacuum sampling. If used in combination, these methods optimise the catch of understorey hemipteran species, as their samples have high complementarity.     

Distribution-abundance relationship for passerines breeding in Tunisian oases: test of the sampling hypothesis

The positive relationship between local abundance and distribution of species is a widely recognized pattern in community ecology. However, it has been suggested that this relationship can simply be an artefact of sampling because locally rare species are less detectable then locally abundant ones, and hence their distribution can easily be underestimated. Here, we use count data to investigate the relationship between distribution and abundance of passerines breeding in a sample of oases from southern Tunisia, and we provide a test of the sampling artefact hypothesis. In particular, we checked for a difference in detection probability between localized and widespread species, and we tested if increasing the sampling effort affects the significance of the relationship. A significant positive relationship between the average local abundance of passerine species and the proportion of occupied oases was found. The use of a capture-recapture approach allowed us to estimate and to compare the detection probabilities of localized and widespread species subsets. We found that localized species were locally less detectable than widespread species, which is consistent with the main assumption of the sampling artefact hypothesis. However, increasing the detection probability of species by conducting more counts did not affect the significance of the relationship, which did not give support to the sampling artefact hypothesis. Our work implies that sampling contributed to the distribution-abundance relationship we found, but that it is unlikely that such a relationship could entirely be explained by an artefact of sampling. It also underlines the insight that can be gained by using probabilistic approaches of estimating species number and detection probability when attempting to disentangle sampling from ecological effects in community ecology studies.     

Aquatic hyphomycete diversity and identity affect leaf litter decomposition in microcosms

We conducted a microcosm experiment with monocultures and all possible combinations of four aquatic hyphomycete species, Articulospora tetracladia, Flagellospora curta, Geniculospora grandis and Heliscus submersus, to examine the potential effects of species richness on three functional aspects: leaf litter decomposition (leaf mass loss), fungal production (ergosterol buildup) and reproductive effort (released spores). Both species richness and identity significantly affected fungal biomass and conidial production (number and biomass of released spores), whereas only species identity had a significant effect on leaf mass loss. In mixed cultures, all measures of fungal functions were greater than expected from the weighted performances of participating species in monoculture. Mixed cultures outperformed the most active monoculture for biomass accumulation but not for leaf mass loss and conidial production. The three examined aspects of aquatic hyphomycete activity tended to increase with species richness, and a complementary effect was unequivocally demonstrated for fungal biomass. Our results also suggest that specific traits of certain species may have a greater influence on ecosystem functioning than species number.