Exploring the Interplay Between Local and Regional Drivers of Distribution of a Subterranean Organism

Caves are excellent model systems to study the effects of abiotic factors on species distributions due to their selective conditions. Different ecological factors have been shown to affect species distribution depending on the scale of analysis, whether regional or local. The interplay between local and regional factors in explaining the spatial distribution of cave-dwelling organisms is poorly understood. Using the troglophilic subterranean spider Artema nephilit (Araneae: Pholcidae) as a model organism, we investigated whether similar environmental predictors drive the species distribution at these two spatial scales. At the local scale, we monitored the abundance of the spiders and measured relevant environmental features in 33 caves along the Jordan Rift Valley. We then extended the analysis to a regional scale, investigating the drivers of the distribution using species distribution models. We found that similar ecological factors determined the distribution at both local and regional scales for A. nephilit. At a local scale, the species was found to preferentially occupy the outermost, illuminated, and warmer sectors of caves. Similarly, mean annual temperature, annual temperature range, and solar radiation were the most important drivers of its regional distribution. By investigating these two spatial scales simultaneously, we showed that it was possible to achieve an in-depth understanding of the environmental conditions that governs subterranean species distribution.Peer reviewe

Fine-scale substrate heterogeneity does not affect arthropod communities on green roofs

Green roofs, which are roofs with growing substrate and vegetation, can provide habitat for arthropods in cities. Maintaining a diversity of arthropods in an urban environment can enhance the functions they fill, such as pest control and soil development. Theory suggests that the creation of a heterogeneous environment on green roofs would enhance arthropod diversity. Several studies have examined how arthropod diversity can be enhanced on green roofs, and particularly whether substrate properties affect the arthropod community, but a gap remains in identifying the effect of substrate heterogeneity within a green roof on the arthropod community. In this paper, it is hypothesized that creating heterogeneity in the substrate would directly affect the diversity and abundance of some arthropod taxa, and indirectly increase arthropod diversity through increased plant diversity. These hypotheses were tested using green roof plots in four treatments of substrate heterogeneity: (1) homogeneous dispersion; (2) mineral heterogeneity—with increased tuff concentration in subplots; (3) organic heterogeneity—with decreased compost concentrations in subplots; (4) both mineral and organic heterogeneity. Each of the four treatments was replicated twice on each of three roofs (six replicates per treatment) in a Mediterranean region. There was no effect of substrate heterogeneity on arthropod diversity, abundance, or community composition, but there were differences in arthropod communities among roofs. This suggests that the location of a green roof, which can differ in local climatic conditions, can have a strong effect on the composition of the arthropod community. Thus, arthropod diversity may be promoted by building green roofs in a variety of locations throughout a city, even if the roof construction is similar on all roofs

SchussenAktivplus: reduction of micropollutants and of potentially pathogenic bacteria for further water quality improvement of the river Schussen, a tributary of Lake Constance, Germany

The project focuses on the efficiency of combined technologies to reduce the release of micropollutants and bacteria into surface waters via sewage treatment plants of different size and via stormwater overflow basins of different types. As a model river in a highly populated catchment area, the river Schussen and, as a control, the river Argen, two tributaries of Lake Constance, Southern Germany, are under investigation in this project. The efficiency of the different cleaning technologies is monitored by a wide range of exposure and effect analyses including chemical and microbiological techniques as well as effect studies ranging from molecules to communities

Coefficients for best pollinator visit models

Model coefficients and SE for the selected best model for each of the plant species. The models were selected by forward selection process out of the GLMM of all combinations of the model explanatory factors

Data from: Effects of plant and pollinator traits on the maintenance of a food deceptive species within a plant community

Model-mimic plant systems are well known. However, the conditions promoting the existence of such systems are still an enigma. We suggest that by focusing on floral similarity between model and mimic, reward levels offered by models, and pollinators' ability to adjust foraging accordingly, the conditions can be better understood. Using spatially-explicit modelling, we examined trait combinations that lead to the survival of deceptive species under a large range of mimic strategies, from Batesian mimicry to general food deception. Unlike previous models studying such systems, we examined model-mimic interactions in the presence of a third, dissimilar species, thus generating a more realistic scenario where pollinators may avoid the model-mimic system altogether. Results showed that overall survival and abundance of species in food deceptive systems depend on the relative reward provided by the participating species and the potential alternatives available. Specifically, the success of a mimic in a Batesian mimicry system depends on high levels of reward provided by its model species relative to potential alternatives in the flower community. On the other hand, the success of a mimic in a general food deception system was higher when the reward offered was lower. Our study suggests that the ability of pollinators to utilize their experience as part of decision-making is highly relevant in promoting mimic survival, thus shedding light on the conditions under which food deception is expected

Coefficients for best survival model

Coeeficients and SE for the selected survival model for each of the plant species. The models were selected by forward selection process out of the set of Cox proportional hazard regressions constructed of all combinations of the model explanatory factors

Coefficients for best pollinator choice model

Model coefficients and SE for best pollinator choice model. The models were selected by forward selection process out of the GLM of all combinations of the model explanatory factors

Beyond the Competition-Colonization Trade-Off: Linking Multiple Trait Response to Disturbance Characteristics

Disturbances' role in shaping communities is well documented but highly disputed. We suggest replacing the overused two-trait trade-off approach with a functional group scheme, constructed from combinations of four key traits that represent four classes of species' responses to disturbances. Using model results and field observations from sites affected by two highly different disturbances, we demonstrated that popular dichotomous trade-offs are not sufficient to explain community dynamics, even if some emerge under certain conditions. Without disturbances, competition was only sufficient to predict species survival but not relative success, which required some escape mechanism (e.g., long-term dormancy). With highly predictable and large-scale disturbances, successful species showed a combination of high individual tolerance to disturbance and, more surprisingly, high competitive ability. When disturbances were less predictable, high individual tolerance and long-term seed dormancy were favored, due to higher environmental uncertainty. Our study demonstrates that theories relying on a small number of predefined trade-offs among traits (e.g., competition-colonization trade-off) may lead to unrealistic results. We suggest that the understanding of disturbance-community relationships can be significantly improved by employing sets of relevant trait assemblies instead of the currently common approach in which trade-offs are assumed in advance