Air bells of water spiders are an extended phenotype modified in response to gas composition

The water spider Argyroneta aquatica (Clerck) is the only spider that spends its whole life under water. Water spiders keep an air bubble around their body for breathing and build under-water air bells, which they use for shelter and raising offspring, digesting and consuming prey, moulting, depositing eggs and sperm, and copulating. It is unclear whether these bells are an important oxygen reservoir for breathing under water, or whether they serve mainly to create water-free space for feeding and reproduction. In this study, we manipulated the composition of the gas inside the bell of female water spiders to test whether they monitor the quality of this gas, and replenish oxygen if required. We exchanged the entire gas in the bell either with pure O(2), pure CO(2), or with ambient air as control, and monitored behavioural responses. The test spiders surfaced and replenished air more often in the CO(2) treatment than in the O(2) treatment, and they increased bell building behaviour. In addition to active oxygen regulation, they monitored and adjusted the bells by adding silk. These results show that water spiders use the air bell as an oxygen reservoir, and that it functions as an external lung, which renders it essential for living under water permanently. A. aquatica is the only animal that collects, transports, and stores air, and monitors its property for breathing, which is an adaptive response of a terrestrial animal to the colonization of an aquatic habitat. J. Exp. Zool. 307A:549-555, 2007. (c) 2007 Wiley-Liss, Inc.

The role of landuse and natural determinants for grassland vegetation composition in the Swiss Alps

The Alps provide a high habitat diversity for plant species, structured by broad- and fine-scale abiotic site conditions. In man-made grasslands, vegetation composition is additionally affected by the type of landuse. We recorded vegetation composition in 216 parcels of grassland in 12 municipalities representing an area of 170 x 70 km in the south-eastern part of the Swiss Alps. Each parcel was characterized by a combination of altitudinal level (valley, intermediate, alp). traditional landuse (mown. grazed), current management (mown, grazed, abandoned). and Fertilization (unfertilized, fertilized). For each parcel we also assessed the abiotic factors aspect, slope, pH value, and geographic coordinates, and for each municipality annual precipitation and its cultural tradition. We analysed vegetation composition using (i) variation partitioning in RDA. (ii) cover of graminoids. non-legume forbs, and legumes, and (iii) dominance and frequency of species. Species composition was determined by, in decreasing order of variation explained. landuse, broad-scale abiotic factors, fine-scale abiotic factors. and cultural tradition. Current socio-economically motivated landuse changes, such as grazing of unfertilized former meadows or their abandonment, strongly affect vegetation composition. In our study, the frequency of characteristic meadow species was significantly smaller in grazed and even smaller in abandoned parcels than in still mown ones, suggesting less severe consequences of grazing for vegetation composition than of abandonment. Therefore. low-intensity grazing and mowing every few years should be considered valuable conservation alternatives to abandonment. Furthermore. because each landuse type was characterized by different species. a high variety of landuse types should be promoted to preserve plant species diversity in Alpine grasslands. (C) 2007 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.