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.     

Early tetrapodomorph biogeography: Controlling for fossil record bias in macroevolutionary analyses

The fossil record provides direct empirical data for understanding macroevolutionary patterns and processes. Inherent biases in the fossil record are well known to confound analyses of this data. Sampling bias proxies have been used as covariates in regression models to test for such biases. Proxies, such as formation count, are associated with paleobiodiversity, but are insufficient for explaining species dispersal owing to a lack of geographic context. Here, we develop a sampling bias proxy that incorporates geographic information and test it with a case study on early tetrapodomorph biogeography. We use recently-developed Bayesian phylogeographic models and a new supertree of early tetrapodomorphs to estimate dispersal rates and ancestral habitat locations. We find strong evidence that geographic sampling bias explains supposed radiations in dispersal rate (potential adaptive radiations). Our study highlights the necessity of accounting for geographic sampling bias in macroevolutionary and phylogenetic analyses and provides an approach to test for its effect.     

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.     

The spatial and temporal distribution of predatory and phytophagous mites in field-grown strawberry in the UK

Extensive sampling of strawberry plants in everbearing and June-bearing strawberry plantations and on potted plants showed that different species of mites were spatially separated. Of the two phytophagous species recorded, Tetranychus urticae was most abundant on old leaves and Phytonemus pallidus on folded leaves and flower/fruit clusters. Predatory phytoseiid mites were found on all plant parts but different species were spatially separated; Neoseiulus cucumeris and N. aurescens were found mostly on folded leaves and clusters, and N. californicus and Phytoseiulus persimilis on old and medium aged leaves. No Typhlodromus pyri were found in the field plantations. These patterns of distribution did not change over sampling dates in summer and early autumn. An understanding of this within-plant zonation of mite species is important when studying predator–prey interactions and when designing sampling strategies for strawberry. A programme to sample the entire mite system on strawberry should be stratified to include all the above mentioned parts of the plant. Different sampling protocols, as appropriate, are required for sampling different pest species and their associated predators.     

Sampling strategies for biotope definition: minimal sampling area for selected groups of macroinvertebrates in the rocky subtidal of São Miguel, Azores

Azorean rocky shores are mainly characterized by patchy algae-based communities with variable associated macrofauna. Characterization studies should therefore include quantitative information for both algae and macroinvertebrates. Unlike for the algae, minimal sampling areas are undefined for macroinvertebrates in the Azores. The present study defines the minimal area to be used for the assessment of the abundance of conspicuous benthic macroinvertebrate abundance. This study proposes methodologies to be used for a selected group of invertebrates when simultaneously undertaking quantifications of macroalgae.     

Scale‐dependent variation in visual estimates of grassland plant cover

Abstract. Plant cover was visually estimated by five observers, independent of each other, in a species‐rich grassland in the Bílé Karpaty Mts., southeastern Czech Republic, in seven plots ranging from 0.001 to 4 m². Variation of total plant cover among the observers was high at small scales: 0.001–0.016 m²; coefficient of variation, CV = 35 to 45%, but much lower at larger scales: 0.06–4 m²; CV = 7 to 15%. Differences between visual estimates of plant cover of individual species made by different observers were affected by plot size, total cover and morphology of particular plants. CV of the cover of individual species ranged from 0 to 225% and decreased with increasing plot size. For abundant plants the CV attained ca. 50%, independent of plot size. In spite of a very high number of sterile plants with similar leaf morphology and colour, the observed variation in cover estimates in the studied grassland was comparable with results reported from other vegetation types. Differences between estimates by individual observers were often larger than usual year to year changes in undisturbed grasslands. Therefore, I suggest that to avoid difficulties in the interpretation of results based on plant cover data obtained from visual estimates, several observers should always work together, adjusting their extreme estimates.