What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder

Erratum to: What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder

Late Quaternary chironomid community structure shaped by rate and magnitude of climate change

Much is known about how climate change impacts ecosystem richness and turnover, but we have less understanding of its influence on ecosystem structures. Here, we use ecological metrics (beta diversity, compositional disorder and network skewness) to quantify the community structural responses of temperature-sensitive chironomids (Diptera: Chironomidae) during the Late Glacial (14 700–11 700 cal a bp) and Holocene (11 700 cal a bp to present). Analyses demonstrate high turnover (beta diversity) of chironomid composition across both epochs; however, structural metrics stayed relatively intact. Compositional disorder and skewness show greatest structural change in the Younger Dryas, following the rapid, high-magnitude climate change at the Bølling–Allerød to Younger Dryas transition. There were fewer climate-related structural changes across the early to mid–late Holocene, where climate change was more gradual and lower in magnitude. The reduced impact on structural metrics could be due to greater functional resilience provided by the wider chironomid community, or to the replacement of same functional-type taxa in the network structure. These results provide insight into how future rapid climate change may alter chironomid communities and could suggest that while turnover may remain high under a rapidly warming climate, community structural dynamics retain some resilience

Broad-scale patterns of geographic avoidance between species emerge in the absence of fine-scale mechanisms of coexistence

This is the final version. Available on open access from Wiley via the DOI in this recordAim: The need to forecast range shifts under future climate change has motivated an increasing interest in better understanding the role of biotic interactions in driving diversity patterns. The contribution of biotic interactions to shaping broad-scale species distributions is however, still debated, partlydue to the difficulty of detecting their effects. We aim to test whether spatial exclusion between potentially competing species can be detected at the species range scale, and whether this pattern relates to fine-scale mechanisms of coexistence. Location: Western Palearctic. Time period: Anthropocene. Taxa: bats (Chiroptera). Methods: We develop and evaluate a measure of geographic avoidance that uses outputs of species distribution models to quantify geographic exclusion patterns expected if interspecific competition affects broad-scale distributions. We apply the measure to 10 Palearctic bat species belonging to four morphologically similar cryptic groups in which competition is likely to occur. We compare outputs to null models based onpairs of virtual species and to expectations based on ecological similarity and fine-scale coexistence mechanisms. We project changes in range suitability under climate change taking into account effects of geographic avoidance. Results: Values of geographic avoidance were above null expectations for two cryptic species pairs, suggesting that interspecific competition could have contributed to shaping their broad-scale distributions. These two pairs showed highest levels of ecological similarity and no trophic or habitat partitioning. Considering the role of competition modified predictions of future range suitability. Conclusions: Our results support the role of interspecific competition in limiting the geographic ranges of morphologically similar species in the absence of fine-scale mechanisms of coexistence. This study highlights the importance of incorporating biotic interactions into predictive models of range shifts under climate change, and the need for further integration of community ecology with species distribution models to understand the role of competition in ecology and biogeography.Natural Environment Research Council (NERC

Life path analysis: scaling indicates priming effects of social and habitat factors on dispersal distances

1. Movements of many animals along a life-path can be separated into repetitive ones within home ranges and transitions between home ranges. We sought relationships of social and environmental factors with initiation and distance of transition movements in 114 buzzards Buteo buteo that were marked as nestlings with long-life radio tags. 2. Ex-natal dispersal movements of 51 buzzards in autumn were longer than for 30 later in their first year and than 35 extra-natal movements between home ranges after leaving nest areas. In the second and third springs, distances moved from winter focal points by birds that paired were the same or less than for unpaired birds. No post-nuptial movement exceeded 2 km. 3. Initiation of early ex-natal dispersal was enhanced by presence of many sibs, but also by lack of worm-rich loam soils. Distances travelled were greatest for birds from small broods and with relatively little short grass-feeding habitat near the nest. Later movements were generally enhanced by the absence of loam soils and short grassland, especially with abundance of other buzzards and probable poor feeding habitats (heathland, long grass). 4. Buzzards tended to persist in their first autumn where arable land was abundant, but subsequently showed a strong tendency to move from this habitat. 5. Factors that acted most strongly in ½-km buffers round nests, or round subsequent focal points, usually promoted movement compared with factors acting at a larger scale. Strong relationships between movement distances and environmental characteristics in ½-km buffers, especially during early ex-natal dispersal, suggested that buzzards became primed by these factors to travel far. 6. Movements were also farthest for buzzards that had already moved far from their natal nests, perhaps reflecting genetic predisposition, long-term priming or poor habitat beyond the study area

What determines territory configurations of badgers?

Blackwell and Macdonald (2000) have re-analysed models by Doncaster and Woodroffe (1993) for badger territory configurations, and drawn opposite conclusions in suggesting that sett locations are not the crucial factor in determining territory shapes and sizes. Doncaster and Woodroffe had constructed Dirichlet tessellations around badger main setts and compared their borders with the locations of actual border latrines. A close correspondence at some sites provided direct evidence that territory size and configuration could be determined solely from the locations of main setts. In contrast, Blackwell and Macdonald use the latrine locations to define Dirichlet tessellations, in order to compare the centres of these modelled territories to actual sett locations. Their method employs statistical techniques that avoid some complications in the way the original model was compared to alternatives. However, because their analysis pre-determines the size and shape of territories from latrine sites, it cannot test hypotheses about factors regulating size and shape. In this respect their conclusions overinterpret the analysis, which can only test the hypothesis that Dirichlet centres associate with sett locations. Here I describe two consequences of this limitation. Firstly, any test of an exact coincidence between Dirichlet centres and setts is necessarily sensitive to underlying structure in the mosaic of habitats across which border latrines are situated, and to missing data on latrine sites. These influences can explain the observed displacement of centres from setts reported by Blackwell and Macdonald. Secondly, alternative tests of non-random association between centres and setts can provide indirect evidence for a role interritory configuration of some single point feature at least in the vicinity of the sett, if not the sett itself. A simple test of this sort indeed confirms a strong pairing of centres with setts at two out of three study sites

Effects of simulated human exploitation of a key grazer, Patella vulgata, on rocky shore assemblages

Exploitation of key consumers can have major consequences for community and ecosystem functioning. Limpets are key grazers exploited in regions such as Macaronesia, southern Africa, Chile and California. Here we describe a field experiment designed to simulate human exploitation of British limpets that are unexploited and used as model populations. Our aim was to evaluate the effects of size-selective harvesting on the composition of the rocky shore community of non-target species. Limpet populations were subjected to simulated exploitation of large size classes for 18 mo at 2 locations in the southwest of England, by systematic removal at 2 different intensities: low and high exploitation compared with unexploited plots. The exploitation of limpets led to establishment of Fucus spp. to differing degrees at each location, but while variation in percentage cover of Fucus spp. decreased over the course of the experiment in unmanipulated control plots, it increased in plots with either low or high exploitation. Multivariate analyses showed that communities at the 2 locations responded differently to the same intensity of exploitation: unmanipulated controls were similar to low-exploitation treatments at Constantine, while at Trevone low-exploitation treatments were similar to high-exploitation treatments. This was mainly due to increases in percentage cover of F. vesiculosus var. evesiculosus with exploitation, indicating that site-specific differences in assemblage structure and the size structure of the harvested populations will determine its assemblage-level responses. Therefore, reductions in density of grazers may have divergent consequences for different rocky shore communities

A spatially explicit agent-based model of the interactions between jaguar populations and their habitats

Agent-based models can predict system-level properties of populations from stochastic simulation of fine-scale movements. One important application to conservation lies in their ability to consider the impact of individual variation in movement and decision-making on populations under future landscape changes. Here, we present a spatially explicit agent-based simulation of a population of jaguars (Panthera onca) in a mixed forest and farmland landscape in Central America that demonstrates an application of least-cost modelling, a description of the way that agents move through their environment, to equilibrium population dynamics. We detail the construction and application of the model, and the processes of calibration, sensitivity analysis and validation with empirical field data. Simulated jaguars underwent feeding, reproduction, and mortality events typical of natural populations, resulting in realistic population dynamics and home range sizes. Jaguar agents located inside protected forest reserves exhibited higher fitness (fecundity, energy reserves, age and age of mortality) as well as lower energy- and habitat-related mortality than jaguar agents located outside these reserves. Changes in fecundity directly affected the dynamics of simulated populations to a larger degree than either mortality or agent–agent interactions. Model validation showed similar patterns to camera traps in the field, in terms of landscape utilisation and the spatial distribution of individuals. The model showed less sensitivity to socially motivated and fine-scale movements, apart from those directed towards feeding and reproduction, but reflected the interactions and movement of naturally occurring populations in this region. Applications of the model will include testing impacts on population dynamics of likely future changes in landscape structure and connectivity

Abundance of hedgehogs (Erinaceus europaeus) in relation to the density and distribution of badgers (Meles meles)

Badgers Meles meles are intraguild predators of hedgehogs Erinaceus europaeus and have been shown to have a major effect on their abundance and behaviour at a localized scale. Previous studies have predicted the exclusion of hedgehogs from rural habitats in areas where badgers are abundant. The two species coexist at the landscape scale, however, as hedgehogs use suburban habitats, which are thought to provide a refuge from the effects of badger predation. We carried out surveys of hedgehog abundance and studied the use of spatial refugia by hedgehogs in relation to badger density and distribution in 10 study sites in the Midlands and south-west regions of England. Surveys confirmed that hedgehogs were almost absent from pasture fields in rural habitats, with their distribution concentrated in amenity grassland fields in suburban areas. However, although suburban habitats are less frequently used by badgers than rural areas, and therefore represented spatial refugia for hedgehogs, the probability of occurrence and abundance of hedgehogs varied in relation to the density of badger setts in the surrounding area. As sett density increased, both the probability of occurrence of hedgehogs and their abundance decreased. A generalized linear model predicted that the probability of hedgehog occurrence in suburban habitats declined towards zero in areas of high badger density. The most probable explanation is the negative effect of high badger abundance on the ability of hedgehogs to move between patches of suburban habitat. The present study concords with results from previous surveys and experimental studies, which found a strong negative spatial relationship between hedgehogs and badgers. It also provides correlative evidence that intraguild predation can exclude intraguild prey from productive habitats