Dietary switching of collembola in grassland soil food webs

Soil food webs are characterised by complex direct and indirect effects among the organisms. Consumption of microorganisms by soil animals is considered as an important factor that contributes to the stability of communities, though cascading effects within the food web can be difficult to detect. In a greenhouse experiment, an addition of a high number the fungal feeding collembola Folsomia quadrioculata was applied to grassland soil food webs in monocultures of three plant species: Plantago lanceolato (forb), Lotus corniculatus (legume) and Holcus lanatus (grass). The abundance of microorganisms, determined as the abundances of phospholipid fatty acids (PLFAs) and the abundances of resident invertebrates, nematodes and collembolans, did not change due to the addition of E quadrioculata. Trophic positions of collembolans were determined by analyses of natural abundances of N-15 stable isotopes. The use of food resources by microorganisms and collembolans was determined by C-13 analysis of microbial PLFAs and solid samples of collembolans. delta C-13 values of the resident collembola Folsomia fimetaria were lower in the presence of E quadrioculata than in the control food webs indicating a use of more depleted C-13 food resources by E fimetaria. The delta N-15 values of E fimetaria did not change at the addition of E quadrioculata thus no change of trophic levels was detected. The switch of E fimetaria to a different food resource could be due to indirect interactions in the food web as the two collembolan species were positioned on different trophic positions, according to different delta N-15 values. (c) 2008 Elsevier Ltd. All rights reserved.

Compositional divergence and convergence in arbuscular mycorrhizal fungal communities

In spite of the controversy that they have generated, neutral models provide ecologists with powerful tools for creating dynamic predictions about beta-diversity in ecological communities. Ecologists can achieve an understanding of the assembly rules operating in nature by noting when and how these predictions are met or not met. This is particularly valuable for those groups of organisms that are challenging to study under natural conditions (e.g., bacteria and fungi). Here, we focused on arbuscular mycorrhizal fungal (AMF) communities and performed an extensive literature search that allowed us to synthesize the information in 19 data sets with the minimal requisites for creating a null hypothesis in terms of community dissimilarity expected under neutral dynamics. In order to achieve this task, we calculated the first estimates of neutral parameters for several AMF communities from different ecosystems. Communities were shown either to be consistent with neutrality or to diverge or converge with respect to the levels of compositional dissimilarity expected under neutrality. These data support the hypothesis that divergence occurs in systems where the effect of limited dispersal is overwhelmed by anthropogenic disturbance or extreme biological and environmental heterogeneity, whereas communities converge when systems have the potential for niche divergence within a relatively homogeneous set of environmental conditions. Regarding the study cases that were consistent with neutrality, the sampling designs employed may have covered relatively homogeneous environments in which the effects of dispersal limitation overwhelmed minor differences among AMF taxa that would lead to environmental filtering. Using neutral models we showed for the first time for a soil microbial group the conditions under which different assembly processes may determine different patterns of beta-diversity. Our synthesis is an important step showing how the application of general ecological theories to a model microbial taxon has the potential to shed light on the assembly and ecological dynamics of communities.

Predicting critical source areas of sediment in headwater catchments

Mitigation of diffuse nutrient and sediment delivery to streams requires successful identification andmanagement of critical source areas within catchments. Approaches to predicting high risk areas forsediment loss have typically relied on structural drivers of connectivity and risk, with little considera-tion given to process driven water quality responses. To assess the applicability of structural metrics topredict critical source areas, geochemical tracing of land use sources was conducted in three headwateragricultural catchments in Co. Down and Co. Louth, Ireland, within a Monte Carlo framework. Outputswere applied to the inverse optimisation of a connectivity model, based on LiDAR DEM data, to assess theefficacy of land use risk weightings to predict sediment source contributions over the 18 month studyperiod in the Louth Upper, Louth Lower and Down catchments. Results of the study indicated sedimentproportions over the study period varied from 6 to 10%, 84 to 87%, 4%, and 2 to 3% for the Down Catch-ment, 79 to 85%, 9 to 17%, 1 to 3% and 2 to 3% in the Louth Upper and 2 to 3%, 79 to 85%, 10 to 17%and 2 to 3% in the Louth Lower for arable, channel bank, grassland, and woodland sources, respectively.Optimised land use risk weightings for each sampling period showed that at the larger catchment scale,no variation in median land use weightings were required to predict land use contributions. However,for the two smaller study catchments, variation in median risk weightings was considerable, which mayindicate the importance of functional connectivity processes at this spatial scale. In all instances, arableland consistently generated the highest risk of sediment loss across all catchments and sampling times.This study documents some of the first data on sediment provenance in Ireland and indicates the needfor cautious consideration of land use as a tool to predict critical source areas at the headwater scale

Habitat Isolation Reduces the Temporal Stability of Island Ecosystems in the Face of Flood Disturbance

Natural ecosystems are increasingly exposed to multiple anthropogenic stressors, including land-use change, deforestation, agricultural intensification, and urbanisation, all of which have led to widespread habitat fragmentation, which is also likely to be amplified further by predicted climate change. The potential interactive effects of these different stressors cannot be determined by studying each in isolation, although such synergies have been largely ignored in ecological field studies to date. Here, we use a model system of naturally fragmented islands in a braided river network, which is exposed to periodic inundation, to investigate the interactive effects of habitat isolation and flood disturbance. Food web structure was similar across the islands during periods of hydrological stability, but several key properties were altered in the aftermath of flood disturbance, based on distance of the islands from the regional source pool of species: taxon richness and mean food chain length declined with habitat isolation after flooding, while the proportion of basal species increased. Greater species turnover through time reflected the slower process of re-colonisation on the more distant islands following disturbance. Increased variability of several food web properties over a 1-year period highlighted the reduced temporal stability of isolated habitat fragments. Many of these effects reflected the differential successes of predator and prey species at re-colonising the islands: even though larger, more mobile consumers may reach the more distant islands first, they cannot establish populations until the lower trophic levels have successfully reassembled. These results highlight the susceptibility of fragmented ecosystems to environmental perturbations. © 2013 Elsevier Ltd.

Environmental Challenges and Physiological Solutions: Comparative Energetic Daily Rhythms of Field Mice Populations from Different Ecosystems

Daily and seasonal variations in physiological characteristics of mammals can be considered adaptations to temporal habitat variables. Across different ecosystems, physiological adjustments are expected to be sensitive to different environmental signals such as changes in photoperiod, temperature or water and food availability; the relative importance of a particular signal being dependent on the ecosystem in question. Energy intake, oxygen consumption (VO) and body temperature (T) daily rhythms were compared between two populations of the broad-toothed field mouse Apodemus mystacinus, one from a Mediterranean and another from a sub-Alpine ecosystem. Mice were acclimated to short-day (SD) 'winter' and long-day (LD) 'summer' photoperiods under different levels of salinity simulating osmotic challenges. Mediterranean mice had higher VO values than sub-Alpine mice. In addition, mice exposed to short days had higher VO values when given water with a high salinity compared with mice exposed to long days. By comparison, across both populations, increasing salinity resulted in a decreased T in SD- but not in LD-mice. Thus, SD-mice may conserve energy by decreasing T during ('winter') conditions which are expected to be cool, whereas LD-mice might do the opposite and maintain a higher T during ('summer') conditions which are expected to be warm. LD-mice behaved to reduce energy expenditure, which might be considered a useful trait during 'summer' conditions. Overall, increasing salinity was a clear signal for Mediterranean-mice with resultant effects on VO and T daily rhythms but had less of an effect on sub-Alpine mice, which were more responsive to changes in photoperiod. Results provide an insight into how different populations respond physiologically to various environmental challenges.

Determinants of root-associated fungal communities within Asteraceae in a semi-arid grassland

Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

Plant community assembly at small scales: spatial versus environmental factors in a central European grassland

Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15x15, 12x12 and 12x12 meters in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

Knowledge Transfer in Quadruple Helix Ecosystems: An Absorptive Capacity Perspective

Increased understanding of knowledge transfer (KT) from universities to the wider regional knowledge ecosystem offers opportunities for increased regional innovation and commercialisation. The aim of this article is to improve the understanding of the KT phenomena in an open innovation context where multiple diverse quadruple helix stakeholders are interacting. An absorptive capacity-based conceptual framework is proposed, using a priori constructs which portrays the multidimensional process of KT between universities and its constituent stakeholders in pursuit of open innovation and commercialisation. Given the lack of overarching theory in the field, an exploratory, inductive theory building methodology was adopted using semi-structured interviews, document analysis and longitudinal observation data over a three-year period. The findings identify five factors, namely human centric factors, organisational factors, knowledge characteristics, power relationships and network characteristics, which mediate both the ability of stakeholders to engage in KT and the effectiveness of knowledge acquisition, assimilation, transformation and exploitation. This research has implications for policy makers and practitioners by identifying the need to implement interventions to overcome the barriers to KT effectiveness between regional quadruple helix stakeholders within an open innovation ecosystem.

Metabolism of mineral-sorbed organic matter depends upon microbial lifestyle in fluvial ecosystems

In fluvial ecosystems mineral erosion, carbon (C) and nitrogen (N) fluxes are linked via organo-mineral complexation, where dissolved organic molecules bind to mineral surfaces. Biofilms and suspended aggregates represent major aquatic microbial lifestyles whose relative importance changes predictably through fluvial networks. We tested how organo-mineral sorption affects aquatic microbial metabolism, using organo-mineral particles containing a mix of ¹³C, ¹⁵N-labelled amino acids. We traced ¹³C and ¹⁵N retention within biofilm and suspended aggregate biomass and its mineralisation. Organo-mineral complexation restricted C and N retention within biofilms and aggregates and also their mineralisation. This reduced the efficiency with which biofilms mineralise C and N by 30 % and 6 %. By contrast, organo-minerals reduced the C and N mineralisation efficiency of suspended aggregates by 41 % and 93 %. Our findings show how organo-mineral complexation affects microbial C:N stoichiometry, potentially altering the biogeochemical fate of C and N within fluvial ecosystems.

Aquatic noise pollution: implications for individuals, populations, and ecosystems

Anthropogenically driven environmental changes affect our planet at an unprecedented scale, and are considered to be a key threat to biodiversity. According to the World Health Organisation, anthropogenic noise is one of the most hazardous forms of anthropogenically driven environmental change and is recognised as a major global pollutant. However, crucial advances in the rapidly emerging research on noise pollution focus exclusively on single aspects of noise pollution, e.g. on behaviour, physiology, terrestrial ecosystems or by focusing on certain taxa. Given that more than two thirds of our planet is covered with water, there is a pressing need to get a holistic understanding of the effects of anthropogenic noise in aquatic ecosystems. We found experimental evidence for negative effects of anthropogenic noise on an individual’s development, physiology, and/or behaviour in both invertebrates and vertebrates. We also found that species differ in their response to noise, and highlight the potential underlying mechanisms for these differences. Finally, we point out challenges in the study of aquatic noise pollution and provide directions for future research, which will enhance our understanding of this globally present pollutant.