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Food Webs and Biodiversity develops a fresh, comprehensive perspective on food webs. Mechanistic explanations for several known macroecological patterns are derived from a few fundamental concepts, which are quantitatively linked to field-observables. An argument is developed that food webs will often be the key to understanding patterns of biodiversity at community level.

With global warming and other pressures on ecosystems rising, understanding and protecting biodiversity is a cause of international concern. This highly topical book will be of interest to a wide ranging audience, including not only graduate students and practitioners in community and conservation ecology but also the complex-systems research community as well as mathematicians and physicists interested in the theory of networks. It is testable in many ways and the author finds remarkable agreements between predictions and reality.

This handbook provides a comprehensive survey of the cultural, social and policy contexts of environmental change across East Asia. The team of international experts critically examine a wide range of environmental problems related to energy, climate change, air, land, water, fisheries, forests and wildlife. The editors conclude that, with nearly half of the human population of the planet, and several rapidly growing economies, most notably China, Asian societies will determine much of the future of human impacts on the regional and global environments.

As climate change-related threats to society increase, the book strongly argues for increased environmental consciousness and action in Asian societies. This handbook is a very valuable companion for students, scholars, policy makers and researchers working on environmental issues in Asia. Account Options Sign in. Top charts. New arrivals. Luo Yiqi May 16, The most recent volume of this series, Advances in Ecological Research , demonstrates a captivating knowledge of recent advances in the analysis of food webs.

A food web describes the network of predator-prey interactions within a community. The simplest description of a food web specifies only who eats whom a connectance web , with no indication of how much or how often. Chapters in this book begin with a discussion of the most detailed connectance webs ever compiled, and advance to incorporate information on the body size and numerical abundance of the species. The results yield new ways of describing food webs and powerful new models for estimating patterns of energy flow in ecosystems. Provides fresh ways of describing food webs and applies previous observations in a new context Ranked as the 1 publication in the Institute for Scientific Information in the Ecology section of Powerful new theory AND application to some of the best food web data in the world Many mathematical models for food web structure and function Integrates previously unconnected perspectives on the description of ecological communities.

Reviews Review Policy. Published on. Flowing text, Original pages. Best For. Web, Tablet, Phone, eReader. Content Protection. Read Aloud. Learn More. Flag as inappropriate. It syncs automatically with your account and allows you to read online or offline wherever you are. Please follow the detailed Help center instructions to transfer the files to supported eReaders. Continue the series. See more. Floods in an Arid Continent. Book Nowhere are floods more paradoxical than in the generally arid Australian continent.

Floods in an Arid Continent brings together experts in meteorology, hydrology, limnology, ornithology, landscape ecology, veterinary and medical sciences, economics, anthropology and sociology to synthesize current knowledge on floods, their occurrence, and their consequences for the environment and societies in the Australian context. Offers detailed trends of effects on global climatic changeProvides an understanding of past and future floods in AustraliaDiscusses disturbances on landscapeIncludes effects on aquatic birds, infectious diseases, and economy.

This volume covers the function of Arctic ecosystems based on the most comprehensive long-term data set in the world from a well-defined Arctic ecosystem. Editors offer a comprehensive and authoritative analysis of how climate variability is influencing an Arctic ecosystem and how the Arctic ecosystems have inherent feedback mechanisms interacting with climate variability or change. The latest research on the functioning of Arctic ecosystemsSupplements current books on arctic climate impact assessment as a case study for ecological specialistsDiscusses the complex perpetuating effects on EarthVital information on modeling ecosystem responses to understand future climates.

Advances in Ecological Research: Volume Ecological Networks. This thematic volume represents an important and exciting benchmark in the study of food webs and other ecological networks, synthesizing and showcasing current research and highlighting future directions for the development of the field. Updates and informs the reader on the latest research findingsWritten by leading experts in the fieldHighlights areas for future investigation.

Integrative Ecology: From Molecules to Ecosystems. This thematic volume represents an important and exciting benchmark in the study of integrative ecology, synthesizing and showcasing current research and highlighting future directions for the development of the field.

More related to ecology. Costa Rican Ecosystems. In the more than thirty years since the publication of Daniel H. And from the lowland dry forests of Guanacaste to the montane cloud forests of Monteverde, from the seasonal forests of the Central Valley to the coastal species assemblages of Tortuguero, Costa Rica has proven to be as richly diverse in ecosystems as it is in species.

Horn, Robert O. Pringle, and Eduardo Carrillo J. Featuring a foreword and introductory remarks by two renowned leaders in biodiversity science and ecological conservation, Thomas E. Fundamentals of Ecosystem Science. The modified PageRank also consistently delivered the highest potential outcome after the optimal approach. Extinction risk with management is zero. Standard competition ranking is used and ten is the best ranking. The patterns in relative management performance of different food-web indices described above are robust to variability in the assumed interaction strength between species, food web structure, and total management budget.

Supplementary Figures 3 and 4 show that the relative performance pattern remains consistent even if we vary the cost of managing species in the network, reduce the assumed effectiveness of management interventions or decrease the likelihood of high extinction probabilities. However, as management effectiveness decreases or we assume a different Beta distribution where species are more likely to have a lower chance of extinction, then the difference between optimal management and management using the other indices also decreases.

Although the superiority of the optimal and greedy approaches is robust to the assumed interaction strength between species, by looking in detail at a single food web, in this case the Alaskan food web, we observe that the species prioritized for management change substantially depending on the strength of interactions between species Fig. Figure 3c—f also illustrates how, for the Alaskan food web, even when interaction strengths are held constant, the different social network, food web and conservation indices prioritize the management of markedly different suites of species.

A detailed investigation of the species selected for management of the Alaskan food web highlights further how the species prioritized for management differ between indices Supplementary Fig. The majority of indices we investigate are deterministic and therefore select the same species to manage irrespective of interaction strengths illustrated by the solid and white tones in Supplementary Fig. The optimal and greedy approaches are able to incorporate information about interaction strengths and management, and adjust the species selected to manage accordingly illustrated by the shaded tones in Supplementary Fig.

Optimal A a , Return-On-Investment c , Betweenness Centrality d , Keystone Index e , and Cascading Extinction f show the prioritization under each of these approaches for the same assignments of species extinction risk and strength of interaction between species. Prioritization rank is indicated by node radius; larger radius equals higher priority. Across the six real food webs explored here, there was no discernible pattern in the trophic level targeted for management by the optimal and greedy approaches Fig.

Inset shows the structure of the real food web and illustrates the number of trophic levels and species per trophic level, note some links have been removed from larger webs for visual clarity.


We discovered that common indices of species importance in food webs do not reveal the best species to manage to conserve the maximum number of species in those webs. The failure of management guided by food-web indices to save as many species as possible can be explained by the difference between accounting for the probabilistic impact of management on the food web, versus propagating the effects of Jenga-style removal of species.

Species are neither secure with management, nor doomed without it. Instead, investing in management of a species affects the probability of that species' extinction, which in turn impacts the chance of extinction for other species in the network. The net effects on overall species persistence from not managing a species are not well approximated through the removal of that species from a food web. We demonstrate that a straightforward greedy heuristic is an excellent approximation of optimal food-web management, providing a computationally efficient way of identifying the important species to manage in large food webs.

As such, the greedy approach used here represents an important addition to the indices used to evaluate food webs, and networks with probabilistic characteristics more generally. The importance of understanding the network consequences of managing species is underscored by our finding that a single species return-on-investment approach for example, ref. This indicates that the improvement in species survival as a result of considering which species would benefit most from management, are substantially outweighed by missed opportunities to manage the entire food web in a more holistic manner.

In general, prioritization indices that neglect food-web structure perform relatively poorly, and their performance is also less robust to uncertainty in web structure and interaction strength Supplementary Fig. It has been proposed that mesoscale approaches, those that incorporate the interactions across the entire network but reduce their importance with distance from a species, could provide a useful tool for conservation 7 , Although in our results a mesoscale measure Keystone Index performs well for webs with relatively low connectance, index performance did not seem to relate to a global, meso, or local taxonomy in a consistent manner.

Node Degree, a local centrality measure, also performed relatively well for low connectance webs, while the PageRank approach, akin to a global centrality measure, had the highest median performance across real and hypothetical food webs. In our work, no single conventional food-web index provided a reliable guide to the optimal management of all food webs.

From a management decision perspective, what is perhaps more interesting than the relative optimality of the median performance of the indices, is how badly an index might do in terms of species protection given the underlying uncertainty in food web parameters. As such, the PageRank approach could offer decision-makers a way of avoiding the worst outcome when an optimal approach cannot be used.

They show that many of the secondary extinctions in dynamic food-web models are captured by the BBN. No previous study has investigated optimal management in food webs, a mathematically and computationally challenging task. Our approach evaluates all possible permutations of species to manage. For a node food web where half the species could be managed this equates to over million management alternatives.

While the size of the generated food webs we investigate are in the range of many recent dynamic studies, for example, 20 to 60 nodes 8 , 22 , 23 , many empirical webs are much larger, for example, ref. However, the application of our approach to real management will rarely involve search across all possible combinations because there are unlikely to be identified management actions for each species in a large web. Our framework is a step towards decision support for optimally managing food webs. In building this approach, however, we have made a number of assumptions that should be evaluated in future work.

In assigning initial values for interaction strengths within the food webs we analysed that we aimed for generality and derived initial probability of persistence from a Beta distribution and prey dependence from a lognormal distribution, see ref. Determining long-term conditional survival probabilities and prey dependence will always be a challenge, however, classical methods of learning BBN conditional probabilities from data on species occurrence or expert knowledge could be applied The strength of interactions between species based on energy flows have been shown to have an important impact on secondary extinctions in food webs, for example, ref.

While our work does not incorporate energy flows as biomass, an approach in doing so might consider the probability of persistence of a species proportional to the total incoming energy flow from prey species. This is similar to the approach taken by Bellingeri and Bodini 29 who translate an energy requirement threshold into an extinction threshold and showed that the higher this threshold the less robust the ecosystem to species removal.

The Intertidal and Shallow Subtidal Food Web at Marion Island

Importantly, some indices may be more or less robust to misspecification of network properties when predicting species of importance 31 and exploration of this with a focus on protection could greatly inform management in the face of this uncertainty. Food webs and the theory behind them can be a powerful guide to conservation and management of ecosystems, but we have discovered that the most common measures of species importance in food webs do not lead to the best management decisions.

We developed a heuristic approach that provides a benchmark by which to assess the performance of food web and network indices, and a robust way to optimally prioritize management of multiple interacting species to maximize species survival for small to medium-sized food webs. The utility of this approach to managing food webs could easily be modified to address other objectives such as the preservation of food web structure 14 or the management of ecosystem services We use BBN's to model food webs where the nodes represent species and the directed edges coincide with predation links.

Here an interspecies interaction represents the conditional probability of a species i persisting given the set of species j on which it feeds F i all persist p i persistence F i. The survival probabilities of basal species, which have no prey, were independent of the number of prey remaining and were hence drawn directly from the Beta distribution. We assume that each species can be managed, or not, which will modify its year conditional probability of persistence.

The conditional persistence probabilities of unmanaged species are unchanged. Good management decisions also depend on the budget available to management agencies. The total cost of a management strategy, c a , must be less than or equal to the budget available for management B :.

To derive an optimal management strategy for a food web we define a utility based on the subset of species extant in the long term.

Food Chains Compilation: Crash Course Kids

More precisely, each extant species i is assigned a positive utility U i , and the global utility of a group of extant species is assumed to be additive:. The expected value of management strategy a , V a , is the expected value of the communities that persist after the implementation of management:. Technically, q x a is the joint probability distribution of the BBN representing the food-web trophic interactions. V a can be computed from the marginal probabilities q i x i a of the joint distribution q x a :. See ref. Overall, computing an optimal strategy requires computing the marginal probabilities of as many BBNs as there are affordable management strategies.

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For larger problems, we must turn to heuristic methods. We tested 13 heuristic methods for food-web management that incorporate varying degrees of food-web complexity, including the presence, direction and strength of interactions between species see Table 1 for summary. We test two approaches that are naive to the interactions between species, a Random approach and a Return-on-Investment approach calculated as the benefit of management in terms of the change in initial probability of persistence relative to the cost of managing that species 25 :.

With equal management costs and effectiveness this reduces to an allocation based on the species with the highest initial probability of extinction. We tested four indices from social network theory, Node Degree the number of predators and prey a species has , Betweenness Centrality how frequently a species is part of the shortest path between two species , and Closeness Centrality the inverse of the sum of the lengths of the shortest paths from a species to all other species.

Each index incorporates the presence of links only and is calculated based on ref. We also investigate a weighted version of Betweenness Centrality and Closeness Centrality 35 , where the weights are based on the measure of prey dependence, w ij and represent interaction strengths. Further, we tested three food-web-specific indices. First, the Keystone Index that assesses the importance of trophic interactions between species in the food web and the species they directly depend on, see ref.

Second, a modified Google PageRank index that aims to classify species as important in the food web that support, directly or indirectly, other important species in the food web, see ref. Third, an index based on a Dominator Tree that represents the pathways essential for energy delivery throughout the food web and each species contribution to this energy deliver These approaches incorporate the presence of interactions and the trophic structure but not interaction strengths.

We also tested a topological approach to investigating the importance of species within a food web using a Cascading Extinction approach, for example, ref. Subsequent to removing one species, all species with no prey remaining were removed and this process was repeated until no more species were without resources.

Species were then ranked based on the total number of species extant in the food web after these secondary extinctions ceased. No interactions strengths were considered in this approach. Investigation of the optimal management of medium-sized food-web motifs see Supplementary Fig. We investigated an approach that prioritized following these rules, and is based around the notion that species depend first and foremost on the presence of their food resources Bottom—up Prioritization.

Again no interactions strengths are considered. Computing the optimal strategy becomes infeasible as the budget and network size increase, since the number of feasible management strategies becomes too large for these to be exhaustively searched. We investigate a Greedy heuristic that instead of using exhaustive search only evaluates a small subset of possible strategies by:.

The greedy process of adding single species to the already selected subset, without removing previously selected species, continues until the full budget B is expended. Both the Greedy and optimal approaches incorporate all three levels of complexity we consider. Food webs range in size from 9 species to 34 species, and in complexity with connectance value between 0.

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Data for all food webs except for the Alaskan food web see ref. We constructed networks representative of ecological communities, based on the food web-niche model 39 , adjusted to prevent closed loops and cannibalism as in ref. The niche model is considered the leading static food-web model as it explains the topology of a large number of empirical food webs, for example, refs 6 , 10 , 40 , 41 and is the base model used to generate the initial structure of food webs in many studies of dynamic food webs, for example, refs 22 , 23 , We generated 20 hypothetical food webs consisting of 30 species with a connectance value of 0.

This range of connectance is within the range observed for empirical food webs and is a common interval used in the study of food webs, for example, refs 4 , 6 , Each management heuristic was used to make management decisions on each empirical food web and generated food web. Species in each food web were ranked based on each heuristic. This ranked list was then used to prioritize species to manage based on each heuristic.

Species were managed in order until the budget, B , was expended. If a species was too expensive to manage given the remaining budget, then this species was skipped and the highest-ranked affordable species in the list of species was considered. For a summary of the steps we followed to assess the performance see the Supplementary Information. Management performance of each heuristic approach was tested on each real food web with iterations of initial probability of extinction and also iterations with variable cost of management and initial probability of extinction.

Management performance was also tested for 20 hypothetical webs of 30 nodes with 10 iterations of initial probability of extinction. First, notional costs of management were all set to one unit. The performance of each heuristic was explored under variable management costs that were drawn uniformly across non-negative integers between zero and five, that is some species cost up to five times more to manage than the cheapest species to manage.

We compared the management performance of each heuristic approach and the optimal strategy based on the expected number of species present after management, calculated as the average performance across all iterations. To investigate the consistency of performance of each heuristic across all iterations we ranked their performance in comparison with all other approaches. Ranking is based on standard competition ranking where outcomes of the same value are given an equal ranking, for example, if two heuristics both were the best ranked they would both be given a ranking of ten for example, 10,10,9,8 and so on.

To search for rules of thumb that mimic the optimal or greedy management approaches we investigated whether there was consistency in the trophic level being targeted by these approaches.

Food Webs: From Connectivity to Energetics - Google Libros

The average investment in managing species in each trophic level, that is the sum of the times a species was managed across all iterations relative to the total number of species in that trophic level and normalized across all trophic levels, was used as a measure of the relative importance of the trophic level for optimal management.

How to cite this article : McDonald-Madden, E. Using food-web theory to conserve ecosystems. We thank W. Probert for help generating network plots, E. Probert, N.

Food webs : from connectivity to energetics

Peyrard, L. Dee and M. Bode for comments on this manuscript. Author contributions E. All authors designed the study, discussed the analysis and results, and edited the manuscript text, and gave final approval for publication. National Center for Biotechnology Information , U. Nat Commun. Published online Jan McDonald-Madden , a, 1 R.

Sabbadin , 2 E. Game , 3 P. Possingham 6, 7. Author information Article notes Copyright and License information Disclaimer. Received May 21; Accepted Nov All Rights Reserved. This work is licensed under a Creative Commons Attribution 4. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material.

This article has been cited by other articles in PMC. Abstract Food-web theory can be a powerful guide to the management of complex ecosystems. Results A greedy heuristic for optimal management For all real and hypothetical food webs tested here, managing species on the basis of common food web indices results in more extinctions than using an optimal multispecies management strategy Fig. Open in a separate window. Figure 1. Comparison of management metrics to optimal performance Across the food web indices tested here, the maximum potential departure from the optimal management performance ranged from 8.