Quantifying invasibility

Pande, Jayant; Yehonatan, None Tsubery,; Shnerb, Nadav M.

doi:10.1101/2021.06.22.449376

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…In brief, one would introduce an invader species to the resident community at low abundance (relative to the abundance of the resident species) and assess whether species composition changes. Recently developed computational tools can also facilitate the inference (Deng et al, 2021;Pande et al, 2021). If we are only interested in bottom-up assembly, then many edges do not need to be mapped to construct the corresponding F I G U R E 5 Explaining the predictability of community assembly using topological features.…”

Section: F Rom T H Eory To T E Sta Ble H Y Pot H E Se Smentioning

confidence: 99%

Untangling the complexity of priority effects in multispecies communities

2021

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The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this framework, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of historydependent community assembly.

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Section: F Rom T H Eory To T E Sta Ble H Y Pot H E Se Smentioning

confidence: 99%

Untangling the complexity of priority effects in multispecies communities

2021

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“…In reality N and so x reach zero eventually, implying global extinction of that species. We therefore approximate the dynamics of x by simple Brownian motion with an absorbing boundary at x = 0 [14].…”

Section: Extinction Risk and Regularisation Of Geometric Mean Abundan...mentioning

confidence: 99%

A metric for tradable biodiversity credits linked to the Living Planet Index and global species conservation

Rossberg¹,

O’Sullivan²,

Terry³

et al. 2021

Preprint

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Difficulties identifying appropriate biodiversity impact metrics remain a major barrier to inclusion of biodiversity considerations in environmentally conscious investment. Here we propose a science-based metric with a simple definition that supports a narrative of biodiversity protection. It links mathematically to a widely used global biodiversity indicator, the Living Planet Index, for which we propose an improved formula to overcome long-standing conceptual issue. We show that, in an ideal market, trade in our metric would lead to near optimal allocation of resources to global biodiversity conservation. Barriers to adoption are low, use of the metric does not require an institutional certification system. We propose its use in biodiversity related financial disclosures and in voluntary or legislated policies of no net biodiversity loss.

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Untangling the complexity of priority effects in multispecies communities

Song

Fukami

Saavedra

2021

Preprint

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Priority effects arise when the history of species arrival influences local species interactions, thereby affecting the composition of ecological communities. The outcome of some priority effects may be more difficult to predict than others, but this possibility remains to be fully investigated. Here, we provide a graph-based, non-parametric, theoretical framework to understand the classification of priority effects and the predictability of multi-species communities. We show that we can classify priority effects by decomposing them into four basic dynamical sources: the number of alternative stable states, the number of alternative transient paths, the length of composition cycles, and the interaction between alternative stable states and composition cycles. Although the number of alternative stable states has received most of the attention, we show that the other three sources can contribute more to the predictability of community assembly, especially in small communities. We discuss how this theoretical framework can guide new experimental studies.

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Quantifying invasibility

Cited by 3 publications

References 41 publications

Untangling the complexity of priority effects in multispecies communities

Untangling the complexity of priority effects in multispecies communities

A metric for tradable biodiversity credits linked to the Living Planet Index and global species conservation

Untangling the complexity of priority effects in multispecies communities

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