Rethinking the importance of the structure of ecological networks under an environment‐dependent framework

Cenci, Simone; Song, Chuliang; Saavedra, Serguei

doi:10.1002/ece3.4252

Cited by 31 publications

(32 citation statements)

References 66 publications

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“…The same logic applies to ecological networks, as they are not merely the product of internal dynamical processes but also of the external environmental conditions [1,4]. In other words, the architecture of a network is much less useful without knowing the environmental pressures acting upon a community [30]. Following this rationale, we have confirmed that antagonistic and mutualistic communities cannot be differentiated using network metrics alone, but this differentiation becomes possible by adding environmental information.…”

Section: Discussionmentioning

confidence: 52%

“…In other words, ignoring temperature variability is throwing out the opposing and predictable patterns of network architectures along environmental gradients [21,32]. Thus, we strongly believe that ecological networks should be analyzed under an environment-dependent approach [30].…”

Section: Discussionmentioning

confidence: 99%

“…For example, temperature variability affects both species interactions [26,27] and network structures [21,28,29]. Thus, under this rationale, the network architecture itself may not carry enough information about the interaction types if the environment is unknown [30]. That is, a locked box (network architecture) is useless unless one also has the right key (environmental conditions).…”

Section: Introductionmentioning

confidence: 99%

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Telling ecological networks apart by their structure: An environment-dependent approach

Song

Saavedra

2020

PLoS Comput Biol

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The network architecture of an ecological community describes the structure of species interactions established in a given place and time. It has been suggested that this architecture presents unique features for each type of ecological interaction: e.g., nested and modular architectures would correspond to mutualistic and antagonistic interactions, respectively. Recently, Michalska-Smith and Allesina (2019) proposed a computational challenge to test whether it is indeed possible to differentiate ecological interactions based on network architecture. Contrary to the expectation, they found that this differentiation is practically impossible, moving the question to why it is not possible to differentiate ecological interactions based on their network architecture alone. Here, we show that this differentiation becomes possible by adding the local environmental information where the networks were sampled. We show that this can be explained by the fact that environmental conditions are a confounder of ecological interactions and network architecture. That is, the lack of association between network architecture and type of ecological interactions changes by conditioning on the local environmental conditions. Additionally, we find that environmental conditions are linked to the stability of ecological networks, but the direction of this effect depends on the type of interaction network. This suggests that the association between ecological interactions and network architectures exists, but cannot be fully understood without attention to the environmental conditions acting upon them.

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Section: Discussionmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Telling ecological networks apart by their structure: An environment-dependent approach

Song

Saavedra

2020

PLoS Comput Biol

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“…We note that ours is just one possible way to capture the stability contribution of a link. Although other definitions could be used to measure different properties of community stability [32,33], we chose the feasibility approach to avoid constraints on the choice of parameters and type of perturbations that most stability metrics impose [4,34]. Feasibility largely avoids these issues by considering all possible sets of parameters and how these parameters can be changed by perturbations in any direction, thus allowing for a more generalisable and consistent metric of dynamic importance that is comparable across different networks (see Methods).…”

Section: Relationship Between Link Vulnerability and Link Feasibilitymentioning

confidence: 99%

Estimating the risk of species interaction loss in mutualistic communities

et al. 2020

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Interactions between species generate the functions on which ecosystems and humans depend. However, we lack an understanding of the risk that interaction loss poses to ecological communities. Here, we quantify the risk of interaction loss for 4,330 species interactions from 41 empirical pollination and seed dispersal networks across 6 continents. We estimate risk as a function of interaction vulnerability to extinction (likelihood of loss) and contribution to network feasibility, a measure of how much an interaction helps a community tolerate environmental perturbations. Remarkably, we find that more vulnerable interactions have higher contributions to network feasibility. Furthermore, interactions tend to have more similar vulnerability and contribution to feasibility across networks than expected by chance, suggesting that vulnerability and feasibility contribution may be intrinsic properties of interactions, rather than only a function of ecological context. These results may provide a starting point for prioritising interactions for conservation in species interaction networks in the future.

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“…Were such an extreme event to occur 380 when the network is less connected, less nested, and more specialized, its consequences might be 381 more severe. Thus, cumulative networks may overlook a relevant temporal scale for 382 understanding network robustness (or other aspects of community dynamics: e.g., Saavedra et al 383 2016a, b; Cenci et al 2018). However, we stress that many responses to disturbance are likely to 384 play out over time scales longer than weeks.…”

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confidence: 99%

On the temporally flexible structure of plant-pollinator interaction networks

CaraDonna

Waser

2020

Preprint

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Ecological communities consist of species that are joined in complex networks of 14 interspecific interaction. The interactions that networks depict often form and dissolve rapidly, 15 but this temporal variation is not well integrated into our understanding of the causes and 16 consequences of network structure. If interspecific interactions exhibit temporal flexibility across 17 time periods over which organisms co-occur, then the emergent structure of the corresponding 18 network may also be temporally flexible, something that a temporally-static perspective would 19 miss. Here, we use an empirical system to examine short-term flexibility in network structure 20 (connectance, nestedness, and specialization), and in individual species interactions that 21 contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine 22 ecosystem across three summer growing seasons. To link the interactions of individual species to 23properties of their networks, we examined weekly temporal variation in species' contributions to 24 network structure. As a test of the potential robustness of networks to perturbation, we also 25 simulated the random loss of species from weekly networks. We then compared the properties of 26 weekly networks to the properties of cumulative networks that aggregate field observations over 27 each full season. A week-to-week view reveals considerable flexibility in the interactions of 28 individual species and their contributions to network structure. For example, species that would 29 be considered relatively generalized across their entire activity period may be much more 30 specialized at certain times, and at no point as generalized as the cumulative network may 31 suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network 32 structure and potential robustness throughout each summer growing season. We conclude that 33 short-term flexibility in species interactions leads to short-term variation in network properties, 34 and that a season-long, cumulative perspective may miss important aspects of the way in which 35 species interact, with implications for understanding their ecology, evolution, and conservation. 36 37 3 KEYWORDS 38 connectance, interaction turnover, nestedness, robustness, specialization, temporal ecology, 39 seasonality, subalpine 40 41 Structure of pollination networks. For all 42 weekly networks and for all three cumulative, 126 season-long networks, we investigated temporal variation in three metrics that describe different 127 aspects of the structure of interactions: (i) connectance; (ii) network-level specialization; and (iii) 128 network nestedness. For network connectance and nestedness, we calculated both binary 129 (unweighted) and frequency-based (weighted) metrics (network specialization is already a 130 frequency-based metric); because overall patterns were qualitatively similar when we calculated 131 either binary or frequency-based metrics for connectance and nestedness, we limit description and 132 ...

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Rethinking the importance of the structure of ecological networks under an environment‐dependent framework

Cited by 31 publications

References 66 publications

Telling ecological networks apart by their structure: An environment-dependent approach

Telling ecological networks apart by their structure: An environment-dependent approach

Estimating the risk of species interaction loss in mutualistic communities

On the temporally flexible structure of plant-pollinator interaction networks

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