Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play.

Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer-algae chemostats; alewife-zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife-zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.

Emergence: a paradigm for robust and scalable distributed applications

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

Quality-of-context driven autonomicity

Optimisation in wireless sensor networks is necessary due to the resource constraints of individual devices, bandwidth limits of the communication channel, relatively high probably of sensor failure, and the requirement constraints of the deployed applications in potently highly volatile environments. This paper presents BioANS, a protocol designed to optimise a wireless sensor network for resource efficiency as well as to meet a requirement common to a whole class of WSN applications - namely that the sensor nodes are dynamically selected on some qualitative basis, for example the quality by which they can provide the required context information. The design of BioANS has been inspired by the communication mechanisms that have evolved in natural systems. The protocol tolerates randomness in its environment, including random message loss, and incorporates a non-deterministic ’delayed-bids’ mechanism. A simulation model is used to explore the protocol’s performance in a wide range of WSN configurations. Characteristics evaluated include tolerance to sensor node density and message loss, communication efficiency, and negotiation latency .

Data rescue and re-use: Recycling old information to address new policy concerns

Information on past trends is essential to inform future predictions and underpin attribution needed to drive policy responses. It has long been recognised that sustained observations are essential for disentangling climate-driven change from other regional and local-scale anthropogenic impacts and environmental fluctuations or cycles in natural systems. This paper highlights how data rescue and re-use have contributed to the debate on climate change responses of marine biodiversity and ecosystems. It also illustrates via two case studies the re-use of old data to address new policy concerns. The case studies focus on (1) plankton, fish and benthos from the Western English Channel and (2) broad-scale and long-term studies of intertidal species around the British Isles. Case study 1 using the Marine Biological Association of the UK's English Channel data has shown the influence of climatic fluctuations on phenology (migration and breeding patterns) and has also helped to disentangle responses to fishing pressure from those driven by climate, and provided insights into ecosystem-level change in the English Channel. Case study 2 has shown recent range extensions, increases of abundance and changes in phenology (breeding patterns) of southern, warm-water intertidal species in relation to recent rapid climate change and fluctuations in northern and southern barnacle species, enabling modelling and prediction of future states. The case is made for continuing targeted sustained observations and their importance for marine management and policy development.

Unanticipated biological changes and global warming

Evidence of global warming is now unequivocal, and studies suggest that it has started to influence natural systems of the planet, including the oceans. However, in the marine environment, it is well-known that species and ecosystems can also be influenced by natural sources of large-scale hydro-climatological variability. The North Atlantic Oscillation (NAO) was negatively correlated with the mean abundance of one of the subarctic key species Calanus finmarchicus in the North Sea. This correlation was thought to have broken down in 1996, however, the timing has never been tested statistically. The present study revisits this unanticipated change and reveals that the correlation did not break down in 1996 as originally proposed but earlier, at the time of an abrupt ecosystem shift in the North Sea in the 1980s. Furthermore, the analyses demonstrate that the correlation between the NAO and C. finmarchicus abundance is modulated by the thermal regime of the North Sea, which in turn covaries positively with global temperature anomalies. This study thereby provides evidence that global climate change is likely to alter some empirical relationships found in the past between species abundance or the ecosystem state and large-scale natural sources of hydro-climatological variability. A theory is proposed to explain how this might happen. These unanticipated changes, also called ‘surprises’ in climatic research, are a direct consequence of the complexity of both climatic and biological systems. In this period of rapid climate change, it is therefore hazardous to integrate meteo-oceanic indices such as the NAO in models used in the management of living resources, as it has been sometimes attempted in the past.

Relationships between North Atlantic salmon, plankton and hydroclimatic change in the Northeast Atlantic

The abundance of wild salmon (Salmo salar) in the North Atlantic has declined markedly since the late 1980s as a result of increased marine mortality that coincided with a marked rise in sea temperature in oceanic foraging areas. There is substantial evidence to show that temperature governs the growth, survival, and maturation of salmon during their marine migrations through either direct or indirect effects. In an earlier study (2003), long-term changes in three trophic levels (salmon, zooplankton, and phytoplankton) were shown to be correlated significantly with sea surface temperature (SST) and northern hemisphere temperature (NHT). A sequence of trophic changes ending with a stepwise decline in the total nominal catch of North Atlantic salmon (regime shift in ∼1986/1987) was superimposed on a trend to a warmer dynamic regime. Here, the earlier study is updated with catch and abundance data to 2010, confirming earlier results and detecting a new abrupt shift in ∼1996/1997. Although correlations between changes in salmon, plankton, and temperature are reinforced, the significance of the correlations is reduced because the temporal autocorrelation of time-series substantially increased due to a monotonic trend in the time-series, probably related to global warming. This effect may complicate future detection of effects of climate change on natural systems.

Lake restoration in terms of ecological resilience: a numerical study of biomanipulations under bistable conditions

An abstract version of the comprehensive aquatic simulation model (CASM) is found to exhibit bistability under intermediate loading of nutrient input, supporting the alternative-stable-states theory and field observations for shallow lakes. Our simulations of biomanipulations under the bistable conditions reveal that a reduction in the abundance of zooplanktivorous fish cannot switch the system from a turbid to a clear state. Rather, a direct reduction of phytoplankton and detritus was found to be most effective to make this switch in the present model. These results imply that multiple manipulations may be effective for practical restorations of lakes. We discuss the present results of biomanipulations in terms of ecological resilience in multivariable systems or natural systems.

Loss of functionally unique species may gradually undermine ecosystems

Functionally unique species contribute to the functional diversity of natural systems, often enhancing ecosystem functioning. An abundance of weakly interacting species increases stability in natural systems, suggesting that loss of weakly linked species may reduce stability. Any link between the functional uniqueness of a species and the strength of its interactions in a food web could therefore have simultaneous effects on ecosystem functioning and stability. Here, we analyse patterns in 213 real food webs and show that highly unique species consistently tend to have the weakest mean interaction strength per unit biomass in the system. This relationship is not a simple consequence of the interdependence of both measures on body size and appears to be driven by the empirical pattern of size structuring in aquatic systems and the trophic position of each species in the web. Food web resolution also has an important effect, with aggregation of species into higher taxonomic groups producing a much weaker relationship. Food webs with fewer unique and less weakly interacting species also show significantly greater variability in their levels of primary production. Thus, the loss of highly unique, weakly interacting species may eventually lead to dramatic state changes and unpredictable levels of ecosystem functioning.

Press perturbations and indirect effects in real food webs

The prediction of the effects of disturbances in natural systems is limited by the general lack of knowledge on the strength of species interactions, i.e., the effect of one species on the population growth rate of another, and by the uncertainty of the effects that may be manifested via indirect pathways within the food web. Here we explored the consequences of changes in species populations for the remaining species within nine exceptionally well-characterized empirical food webs, for which, unlike the vast majority of other published webs, feeding links have been fully quantied. Using the inverse of the Jacobian matrix, we found that perturbations to species with few connections have larger net effects (considering both direct and indirect pathways between two species) on the rest of the food web than do disturbances to species that are highly connected. For 40% of predator-prey links, predators had positive net effects on prey populations, due to the predominance of indirect interactions. Our results highlight the fundamental, but often counterintuitive, role of indirect effects for the maintenance of food web complexity and biodiversity.

Energy sustainability indicators for urban environments

Sustainable development comprises of three dimensions. The three dimensions are the environment, the social and the economic. There have been many indicators used to measure the three dimensions of sustainability. For example air pollution, consumption of natural resources, quality of open space, noise, equity and opportunities and economic benefits from transport and land use. Urban areas constitute the most crucial factor in the sustainability. Urban systems affect and are affected by natural systems beyond their physical boundaries and in general the interdependence between the urban system and the regional and global environment is not reflected in urban decision making. The use of energy in the urban system constitutes the major element in the construction and function of urban areas. Energy impacts across the boundaries of the three dimensions of sustainability. The objective of this research is to apply energy-use-indicators to the urban system as a measure of sustainability. This methodology is applied to a case study in the United Kingdom.

Prey field switching based on preferential behaviour can induce Lévy flights

Using the foraging movements of an insectivorous bat, Myotis mystacinus, we describe temporal switching of foraging behaviour in response to resource availability. These observations conform to predictions of optimized search under the Lévy flight paradigm. However, we suggest that this occurs as a result of a preference behaviour and knowledge of resource distribution. Preferential behaviour and knowledge of a familiar area generate distinct movement patterns as resource availability changes on short temporal scales. The behavioural response of predators to changes in prey fields can elicit different functional responses, which are considered to be central in the development of stable predator-prey communities. Recognizing how the foraging movements of an animal relate to environmental conditions also elucidates the evolution of optimized search and the prevalence of discrete strategies in natural systems. Applying techniques that use changes in the frequency distribution of movements facilitates exploration of the processes that underpin behavioural changes. © 2012 The Author(s) Published by the Royal Society. All rights reserved.

Choosing and using diversity indices: Insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Growth enhancement of micro algae, Chaetoceros calcitrans and Nannochloropsis oculata, using selected bacterial strains

In natural systems phytoplankton interact with planktonic (free living) and attached epiphytic bacteria both synergistically and antagonistically. The specificity of the association with micro algae and bacteria differs in terms of adhesion mechanisms and metabolic cooperation. Present research was carried out to study the effect of bacterial isolates namely Bacillus sp. and Pseudomonas sp. from algal culture systems on the growth of micro algae such as Chaetoceros calcitrans and Nannochloropsis oculata. C. calcitrans (F= 15.34; P<0.05) and N. oculata (F=12.52; P<0.05) showed significantly higher growth, in treatments with Bacillus sp. and Pseudomonas sp when compared to control.

Biochemical effects of cadmium, salinity and temperature on the catabolism of proteins and purines in oreochromis mossambicus (Peters)

In the present investigation, three important stressors: cadmium ion (Cd++), salinity and temperature were selected to study their effects on protein and purine catabolism of O. mossambicus. Cadmium (Cd) is a biologically nonessential metal that can be toxic to aquatic animals. Cadmium is a trace element which is a common constituent of industrial effluents. It is a non-nutrient metal and toxic to fish even at low concentrations. Cadmium ions accumulate in sensitive organs like gills, liver, and kidney of fish in an unregulated manner . Thus; the toxic effects of cadmium are related to changes in natural physiological and biochemical processes in organism. The mechanics of osmoregulation (i.e. total solute and water regulation) are reasonably well understood (Evans, 1984, 1993), and most researchers agree that salinities that differ from the internal osmotic concentration of the fish must impose energetic regulatory costs for active ion transport. There is limited information on protein and purine catabolism of euryhaline fish during salinity adaptation. Within a range of non-lethal temperatures, fishes are generally able to cope with gradual temperature changes that are common in natural systems. However, rapid increases or decreases in ambient temperature may result in sub lethal physiological and behavioral responses. The catabolic pathways of proteins and purines are important biochemical processes. The results obtained signifies that O. mossambicus when exposed to different levels of cadmium ion, salinity and temperature show great variation in the catabolism of proteins and purines. The organism is trying to attain homeostasis in the presence of stressors by increasing or decreasing the activity of certain enzymes. The present study revealed that the protein and purine catabolism in O. mossambicus is sensitive to environmental stressors.