Aim To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science‐based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location Denmark, Europe. Methods We used a point process model to estimate the effect of land cover and human infrastructure on the intensity of observations from four different citizen science species recording schemes. We then use these results to predict areas of under‐ and oversampling as well as relative biodiversity ‘hotspots’ and ‘deserts’, accounting for common spatial biases introduced in unstructured sampling designs. Results We demonstrate that the explanatory power of spatial biases such as infrastructure and human population density increased as the complexity of the sampling schemes decreased. Despite a low absolute sampling effort in agricultural landscapes, these areas still appeared oversampled compared to the observed species richness. Conversely, forests and grassland appeared undersampled despite higher absolute sampling efforts. We also present a novel and effective analytical approach to address spatial biases in unstructured sampling schemes and a new way to address such biases, when more structured sampling is not an option. Main conclusions We show that citizen science datasets, which rely on untrained amateurs, are more heavily prone to spatial biases from infrastructure and human population density. Objectives and protocols of mass‐participating projects should thus be designed with this in mind. Our results suggest that, where contextual data is available, modelling the intensity of individual observation can help understand and quantify how spatial biases affect the observed biological patterns.

The response of body size to increasing temperature constitutes a universal response to climate change that could strongly affect terrestrial ectotherms, but the magnitude and direction of such responses remain unknown in most species. The metabolic cost of increased temperature could reduce body size but long growing seasons could also increase body size as was recently shown in an Arctic spider species. Here, we present the longest known time series on body size variation in two High-Arctic butterfly species: Boloria chariclea and Colias hecla. We measured wing length of nearly 4500 individuals collected annually between 1996 and 2013 from Zackenberg, Greenland and found that wing length significantly decreased at a similar rate in both species in response to warmer summers. Body size is strongly related to dispersal capacity and fecundity and our results suggest that these Arctic species could face severe challenges in response to ongoing rapid climate change.

1. Changes in insect biomass, abundance, and diversity are challenging to track at sufficient spatial, temporal, and taxonomic resolution. Camera traps can capture habitus images of ground-dwelling insects. However, currently sampling involves manually detecting and identifying specimens. Here, we test whether a convolutional neural network (CNN) can classify habitus images of ground beetles to species level, and estimate how correct classification relates to body size, number of species inside genera, and species identity.2. We created an image database of 65,841 museum specimens comprising 361 carabid beetle species from the British Isles and fine-tuned the parameters of a pretrained CNN from a training dataset. By summing up class confidence values within genus, tribe, and subfamily and setting a confidence threshold, we trade-off between classification accuracy, precision, and recall and taxonomic resolution.3. The CNN classified 51.9% of 19,164 test images correctly to species level and 74.9% to genus level. Average classification recall on species level was 50.7%.Applying a threshold of 0.5 increased the average classification recall to 74.6% at the expense of taxonomic resolution. Higher top value from the output layer and larger sized species were more often classified correctly, as were images of species in genera with few species. 4. Fine-tuning enabled us to classify images with a high mean recall for the whole test dataset to species or higher taxonomic levels, however, with high variability.This indicates that some species are more difficult to identify because of properties such as their body size or the number of related species.5. Together, species-level image classification of arthropods from museum collections and ecological monitoring can substantially increase the amount of occurrence data that can feasibly be collected. These tools thus provide new opportunities in understanding and predicting ecological responses to environmental change. Jens-Christian Svenninghttps://orcid.

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A laser flash photolysis-resonance fluorescence technique has been employed to study the kinetics of the reaction of atomic chlorine with pyridine (C(5)H(5)N) as a function of temperature (215-435 K) and pressure (25-250 Torr) in nitrogen bath gas. At T> or = 299 K, measured rate coefficients are pressure independent and a significant H/D kinetic isotope effect is observed, suggesting that hydrogen abstraction is the dominant reaction pathway. The following Arrhenius expression adequately describes all kinetic data at 299-435 K for C(5)H(5)N: k(1a) = (2.08 +/- 0.47) x 10(-11) exp[-(1410 +/- 80)/T] cm(3) molecule(-1) s(-1) (uncertainties are 2sigma, precision only). At 216 K < or =T< or = 270 K, measured rate coefficients are pressure dependent and are much faster than computed from the above Arrhenius expression for the H-abstraction pathway, suggesting that the dominant reaction pathway at low temperature is formation of a stable adduct. Over the ranges of temperature, pressure, and pyridine concentration investigated, the adduct undergoes dissociation on the time scale of our experiments (10(-5)-10(-2) s) and establishes an equilibrium with Cl and pyridine. Equilibrium constants for adduct formation and dissociation are determined from the forward and reverse rate coefficients. Second- and third-law analyses of the equilibrium data lead to the following thermochemical parameters for the addition reaction: Delta(r)H = -47.2 +/- 2.8 kJ mol(-1), Delta(r)H = -46.7 +/- 3.2 kJ mol(-1), and Delta(r)S = -98.7 +/- 6.5 J mol(-1) K(-1). The enthalpy changes derived from our data are in good agreement with ab initio calculations reported in the literature (which suggest that the adduct structure is planar and involves formation of an N-Cl sigma-bond). In conjunction with the well-known heats of formation of atomic chlorine and pyridine, the above Delta(r)H values lead to the following heats of formation for C(5)H(5)N-Cl at 298 K and 0 K: Delta(f)H = 216.0 +/- 4.1 kJ mol(-1), Delta(f)H = 233.4 +/- 4.6 kJ mol(-1). Addition of Cl to pyridine could be an important atmospheric loss process for pyridine if the C(5)H(5)N-Cl product is chemically degraded by processes that do not regenerate pyridine with high yield.

Environmental DNA (eDNA) metabarcoding is increasingly being implemented as a non-invasive and efficient approach for biodiversity research and monitoring across ecosystems. However, accurate detection of species with eDNA requires robust experimental designs as eDNA analysis carries a risk of contamination at every step of the fieldwork and laboratory processes. Several studies focus on rigorous laboratory procedures and processing of sequencing data, but surprisingly, little research investigates the process of background input of DNA in the field. For example, airborne DNA from localities outside the study area could potentially contaminate eDNA samples.Here, we use an experimental setup and eDNA metabarcoding to study the diversity and accumulation of airborne eukaryotic eDNA on exposed surfaces in the field. At two different natural locations, a coastal marine site and a terrestrial grassland site, we placed open containers each filled with 0.5 liters of water, which was then sampled at eight successive time points after exposure to the surroundings. We found an accumulation of detected species richness in the samples, which reached its maximum at the end of the experiment, 24 h after exposure. This result was consistent across both sites and across two markers (COI for eukaryotes and 12S for vertebrates). While many of the detected species were contaminants commonly found in eDNA studies, we also detected several other eukaryotic taxa. Most notable were metazoan species such as birds, fish, and insects, likely originating from airborne transport of eDNA.We also found that increasing the number of PCR cycles tended to have a positive impact on richness for the unfiltered reads but a negative impact on the richness after bioinformatic filtering. Our results add to the sparse evidence that metazoan eDNA can be transported by air, which have wide implications for eDNA research and calls for increased implementation of field control samples.

Insects and other terrestrial invertebrates are declining in species richness and abundance. This includes the invertebrates associated with herbivore dung, which have been negatively affected by grazing abandonment and the progressive loss of large herbivores since the Late Pleistocene. Importantly, traditional monitoring of these invertebrates is time-consuming and requires considerable taxonomic expertise, which is becoming increasingly scarce. In this study, we investigated the potential of environmental DNA (eDNA) metabarcoding of cow dung samples for biomonitoring of dung-associated invertebrates. From eight cowpats we recovered eDNA from 12 orders, 29 families, and at least 54 species of invertebrates (mostly insects), representing several functional groups. Furthermore, species compositions differed between the three sampled habitats of dry grassland, meadow, and forest. These differences were in accordance with the species' ecology; for instance, several species known to be associated with humid conditions or lower temperatures were found only in the forest habitat. We discuss potential caveats of the method, as well as directions for future study and perspectives for implementation in research and monitoring. K E Y W O R D S conservation biology, environmental DNA, insects, invertebratesThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.