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257 results for “Insect Diversity”

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zenodo44/100

Data and code from: Insect biomass decline scaled to species diversity: General patterns derived from a hoverfly community

To study changes in flying insect communities, and hoverflies in particular, malaise trap samples from a German site were compared between two years (Hallmann et al. 2020). The data files deposited here contain data obtained from six malaise traps in the Wahnbachtal (North Rhine-Westphalia, Germany, 50.851944N, 7.320833E) that were deployed in 1989 and again in 2014, at the exact same locations. Traps were situated in wet meadows as well as tall perennial meadows, in close proximity to shrub corridors, to forest–grassland borders, and to the Wahnbach River and surrounded by agricultural land, essentially a rather heterogeneous habitat. The Wahnbach River and the greater part of the valley are protected for watershed purposes and are subject to nature conservation management by the Wahnbach Talperrenverband. Hence, several restrictions apply to safeguard against water contamination. Total insect biomass collected with these traps was already included in Hallmann et al. (2017), but here we focus on additional information: the abundance and richness of hoverflies (Syrphidae) in each of the collected samples (pots). Methodologies of collection are described in Sorg (1990), Schwan et al. (1993), Sorg et al. (2013), Hallmann et al. (2017), and Ssymank et al. (2018).  In brief, malaise traps were deployed throughout the growing season and operated continuously (day and night). Malaise trap construction (e.g., size, material, colouring, and ground sealing) and placing (e.g., positioning, orientation, and slope of the locations) were standardised in all aspects. Insect samples were preserved in 80% ethanol solution. Catches of the six traps investigated in the present study were emptied regularly: On average exposure intervals were 7.0 d (SD = 0.5) in 1989 and 16.7 d (SD = 5.6) in 2014. Across the six traps in 2014 the total exposure time (in number of days) was 42% higher compared to 1989. All collected samples (n = 196) were used in the present analysis with in total 19,604 individual hoverflies counted, distributed over 162 species and 59 genera. To assess how environmental conditions have changed over the 25 year, several additional datasets were assembled. Climatic data were obtained from 169 climatic stations and were used to interpolate daily weather variables to each trap location, using spatiotemporal kriging. These steps are described in detail in Hallmann et al. (2017). Our analysis (see R code) consists of three components. First, we considered total abundance, species richness, and species diversity, at two temporal scales: pooled per year, i.e., across the sampling season, and seasonally (i.e., per day), and we compared these metrics between 1989 and 2014. Second, we examined how total flying biomass (i.e., the weight of all trapped insects, of which hoverflies are only a small proportion) related to total abundance as well as species richness of hoverflies. Third, we derived persistence probabilities and population growth rate trends per species, to examine interspecific variation in these parameters. Descriptions of the deposited files: Groups.csv MF_NR = identifier of each of the six malaise trap locations yrf = year of sampling pot = sample identifier dt = number of sampling days from.dnr = day-of-the-year on which a pot was attached to a malaise trap to.dnr = day-of-the-year on which a pot was collected from a malaise trap mean.daynr = mean day-of-the-year of the sampling period Nspec = number of different hoverfly species found in a pot Nind = number of hoverfly individuals found in a pot Counts.csv A matrix of counts of individual hoverflies per pot per species. The 196 rows represent the pots in the same order as in the file 'Groups.csv'. The columns represent the 162 different hoverfly species found. The scientific species names are indicated in the column headers. PairedData.csv pot = sample identifier JAHR = year of sampling MF_NR = identifier of each of the six malaise trap locations dt = number of sampling days from.dnr = day-of-the-year on which a pot was attached to a malaise trap to.dnr = day-of-the-year on which a pot was collected from a malaise trap NI = number of hoverfly individuals found in a potbiomass.daily NSP = number of different hoverfly species found in a pot biomass.daily = daily fresh weight [gram] of flying insects: total fresh weight in a pot divided by the number of sampling days. ModelFrame.csv MF_NR = identifier of each of the six malaise trap locations yrf = year of sampling pot = sample identifier dt = number of sampling days from.dnr = day-of-the-year on which a pot was attached to a malaise trap to.dnr = day-of-the-year on which a pot was collected from a malaise trap mean.daynr = mean day-of-the-year of the sampling period plot = identifier of each of the six malaise trap locations date = date for which the weather variables are interpolated daynr = day-of-the-year for which the weather variables are interpolated altitude = altitude [m] of the malaise trap locations year = year of sampling temperature = interpolated temperature [degrees Celsius] precipitation = interpolated precipitation [mm per day] wind.speed = interpolated wind speed [m/s] Data_Rcode.pdf This pdf provides the R-code behind the analysis of the Hoverfly data. Three datasets are provided along with this R-code document, namely "Counts.csv", "Groups.csv", "PairedData.csv" and "ModelFrame.csv". Additionally, the BUGS-code ""syrphidModel.jag" is required for running the daily-activity model in JAGS. syrphidModel.jag This BUGS-code is required for running the daily-activity model in JAGS.

opencc-by-4.0Nov 2020View details →

dryad40/100

Crop heterogeneity is positively associated with beneficial insect diversity in subtropical farmlands

Increasing crop configurational heterogeneity – smaller crop fields with more field margins – has been repeatedly found to support farmland biodiversity. But research on compositional crop heterogeneity – the number and evenness of crop types – has usually shown only weak effects. However, much of this research has been conducted in large-scale temperate agroecosystems. We examined smallholder subtropical agroecosystems in southern China to assess the effects of crop heterogeneity on beneficial insect biodiversity. In addition to pollinators (bees, apoid and vespid wasps, butterflies), we studied dung beetles and dragonflies/damselflies, which are not usually considered in cropland heterogeneity studies, but are abundant in these multi-functional agroecosystems. We sampled these taxa in 468 transects placed inside 52 farms across three seasons (summer, spring, winter), collecting data on 27,245 insects belonging to 160 species. We found a strong positive effect of crop compositional heterogeneity (measured by Shannon-Wiener index) on dung beetle and dragonfly/damselfly diversity. Bees/wasps and butterflies, conversely, were positively affected by crop configurational heterogeneity (measured by cumulative field margin length). Field margin type, categorized by the structure of the dominant crop types, was consistently an important explanatory variable, with weedy margins having high insect diversity. The presence of a vegetable crop on one side of the field margin, compared to non-vegetable monocultures on both sides, increased diversity in 3/4 taxon-season comparisons made for rice, and 6/9 comparisons made for sugarcane or corn. Synthesis and applications. We demonstrate that crop compositional heterogeneity can support insects that respond to differences among crop types, including taxa that play a key role in nutrient cycling (dung beetles) and natural pest control (dragonflies/damselflies). Incorporating structurally diverse crops into monoculture Asian agroecosystems can reduce the adverse effects these intensive systems have on beneficial insects, and increase crucial ecosystem services.

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Data and code from: Insect biomass decline scaled to species diversity: General patterns derived from a hoverfly community

Crop heterogeneity is positively associated with beneficial insect diversity in subtropical farmlands

Figure 3 in Diversity of cellulolytic and xylanolytic fungi associated with the digestive tract of aquatic insect larvae in streams of the Amazon Forest and Cerrado in Brazil

Figure 2 in Diversity of cellulolytic and xylanolytic fungi associated with the digestive tract of aquatic insect larvae in streams of the Amazon Forest and Cerrado in Brazil

Figure 1 in Diversity of cellulolytic and xylanolytic fungi associated with the digestive tract of aquatic insect larvae in streams of the Amazon Forest and Cerrado in Brazil

Figure 2 in Diversity and enzymatic capabilities of fungi associated with the digestive tract of larval stages of a shredder insect in Cerrado and Amazon Forest, Brazil

Data & Analysis Script for: Phylogenetic relatedness to native congeners drives insect abundance and diversity hosted by non-native trees

Figure 2 in Diversity of Orthopteran insects and their role in Tea Agro-Ecosystem of West Bengal

Figure 1 in A comparative study of the aquatic insect diversity of two ponds located in Cachar District, Assam, India

Linked collectors and determiners for: Aquatic Insects from the Caatinga: checklists and diversity assessments of Ubajara (Ceará State) and Sete Cidades (Piauí State) National Parks, Northeastern Brazil.

Linked collectors and determiners for: Holopothrips diversity-a Neotropical genus of gall-inducing insects (Thysanoptera, Phlaeothripidae).

Linked collectors and determiners for: Insect Diversity and Diagnostics.

Linked collectors and determiners for: FBIP: Genetic diversity of olive insect pests and their natural enemies in the Western Cape.

Figure 1 in Challenging the Wallacean shortfall: A total assessment of insect diversity on Guadeloupe (French West Indies), a checklist and bibliography

FIGURE 25 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

FIGURE 21 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

FIGURE 23 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

FIGURE 20 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

FIGURE 19 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

FIGURE 18 in Diverse new scale insects (Hemiptera: Coccoidea) in amber from the Cretaceous and Eocene with a phylogenetic framework for fossil Coccoidea

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