Addressing the Eltonian shortfall with trait‐based interaction models

Caron, Dominique; Maiorano, Luigi; Thuiller, Wilfried; Pollock, Laura J.

doi:10.1111/ele.13966

Cited by 21 publications

(35 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In all cases, the predicted connectance was greater than the observed connectance (Figure 5b). This result is similar to that of a recent study of European vertebrate food webs by Caron et al (2022). They found that local food web connectance was consistently overestimated by a trait‐based model which used diet, nesting habitat, activity time, foraging behavior, and body mass of species.…”

Section: Discussionsupporting

confidence: 93%

Section: Connectance and Missing Linkssupporting

confidence: 92%

“…That is, it cannot predict that a predator will consume prey of sizes 1 and 3 and not prey of size 2. Such patterns can however be predicted if a trait in addition to size which is not perfectly correlated with size, influences foraging parameters (Allesina et al, 2008; Caron et al, 2022; Petchey et al, 2008; Stouffer et al, 2006). Secondly, it is important to note that the observed diets were not contiguous when prey are ordered by their size.…”

Section: Discussionmentioning

confidence: 99%

“…Secondly, it is important to note that the observed diets were not contiguous when prey are ordered by their size. This could be due to some ecological differences in how predator groups choose their prey (Caron et al, 2022). Hence, the estimation process will result in a greater number of predicted links than observed given these features, and the model attempts to maximize the coincidence of predicted and observed link presence and absence (i.e., the TSS).…”

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Simultaneously estimating food web connectance and structure with uncertainty

Gupta

Furrer

Petchey

2022

Ecology and Evolution

View full text Add to dashboard Cite

Food web models explain and predict the trophic interactions in a food web, and they can infer missing interactions among the organisms. The allometric diet breadth model (ADBM) is a food web model based on the foraging theory. In the ADBM, the foraging parameters are allometrically scaled to body sizes of predators and prey. In Petchey et al. (Proceedings of the National Academy of Sciences, 2008; 105: 4191), the parameterization of the ADBM had two limitations: (a) the model parameters were point estimates and (b) food web connectance was not estimated. The novelty of our current approach is: (a) We consider multiple predictions from the ADBM by parameterizing it with approximate Bayesian computation, to estimate parameter distributions and not point estimates. (b) Connectance emerges from the parameterization, by measuring model fit using the true skill statistic, which takes into account prediction of both the presences and absences of links. We fit the ADBM using approximate Bayesian computation to 12 observed food webs from a wide variety of ecosystems. Estimated connectance was consistently greater than previously found. In some of the food webs, considerable variation in estimated parameter distributions occurred and resulted in considerable variation (i.e., uncertainty) in predicted food web structure. These results lend weight to the possibility that the observed food web data is missing some trophic links that do actually occur. It also seems likely that the ADBM likely predicts some links that do not exist. The latter could be addressed by accounting in the ADBM for additional traits other than body size. Further work could also address the significance of uncertainty in parameter estimates for predicted food web responses to environmental change.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Connectance and Missing Linkssupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Simultaneously estimating food web connectance and structure with uncertainty

Gupta

Furrer

Petchey

2022

Ecology and Evolution

View full text Add to dashboard Cite

show abstract

“…When possible, MSC analyses should test the sensitivity of connectivity estimates by comparing models that vary the presence-absence and strength of interactions to better understand the relative impact of these two sources of error. Promising new studies on metawebs, which aim to understand spatial variation in food web structure, find that interactions can be grouped into trophic guilds using functional traits with relatively little error (O'Connor et al, 2020;Caron et al, 2022). Such studies can help bridge the gap between spatial community ecology and landscape ecology, a link that is currently missing in applied connectivity conservation (Pollock et al, 2020).…”

Section: Integrating Species Interactionsmentioning

confidence: 99%

Missing Interactions: The Current State of Multispecies Connectivity Analysis

Wood¹,

Martins²,

Dumais-Lalonde³

et al. 2022

Front. Ecol. Evol.

View full text Add to dashboard Cite

Designing effective habitat and protected area networks, which sustain species-rich communities is a critical conservation challenge. Recent decades have witnessed the emergence of new computational methods for analyzing and prioritizing the connectivity needs of multiple species. We argue that the goal of prioritizing habitat for multispecies connectivity should be focused on long-term persistence of a set of species in a landscape or seascape. Here we present a review of the literature based on 77 papers published between 2010 and 2020, in which we assess the current state and recent advances in multispecies connectivity analysis in terrestrial ecosystems. We summarize the four most employed analytical methods, compare their data requirements, and provide an overview of studies comparing results from multiple methods. We explicitly look at approaches for integrating multiple species considerations into reserve design and identify novel approaches being developed to overcome computational and theoretical challenges posed by multispecies connectivity analyses. There is a lack of common metrics for multispecies connectivity. We suggest the index of metapopulation capacity as one metric by which to assess and compare the effectiveness of proposed network designs. We conclude that, while advances have been made over the past decade, the field remains nascent by its ability to integrate multiple species interactions into analytical approaches to connectivity. Furthermore, the field is hampered its ability to provide robust connectivity assessments for lack of a clear definition and goal for multispecies connectivity conservation.

show abstract