Browsing by Author "Corcoran, Derek"

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    NetworkExtinction: An R package to simulate extinction propagation and rewiring potential in ecological networks
    (2023) Ávila Thieme, María Isidora; Kusch, Erik; Corcoran, Derek; Castillo, Simón P.; Valdovinos, Fernanda S.; Navarrete C., Sergio; Marquet, P. A.
    Earth's biosphere is undergoing drastic reorganization due to the sixth mass extinction brought on by the Anthropocene. Impacts of local and regional extirpation of species have been demonstrated to propagate through the complex interaction networks they are part of, leading to secondary extinctions and exacerbating biodiversity loss. Contemporary ecological theory has developed several measures to analyse the structure and robustness of ecological networks under biodiversity loss. However, a toolbox for directly simulating and quantifying extinction cascades and creating novel interactions (i.e. rewiring) remains absent. Here, we present NetworkExtinction—a novel R package which we have developed to explore the propagation of species extinction sequences through ecological networks and quantify the effects of rewiring potential in response to primary species extinctions. With NetworkExtinction, we integrate ecological theory and computational simulations to develop functionality with which users may analyse and visualize the structure and robustness of ecological networks. The core functions introduced with NetworkExtinction focus on simulations of sequential primary extinctions and associated secondary extinctions, allowing user-specified secondary extinction thresholds and realization of rewiring potential. With the package NetworkExtinction, users can estimate the robustness of ecological networks after performing species extinction routines based on several algorithms. Moreover, users can compare the number of simulated secondary extinctions against a null model of random extinctions. In-built visualizations enable graphing topological indices calculated by the deletion sequence functions after each simulation step. Finally, the user can estimate the network's degree distribution by fitting different common distributions. Here, we illustrate the use of the package and its outputs by analysing a Chilean coastal marine food web. NetworkExtinction is a compact and easy-to-use R package with which users can quantify changes in ecological network structure in response to different patterns of species loss, thresholds and rewiring potential. Therefore, this package is particularly useful for evaluating ecosystem responses to anthropogenic and environmental perturbations that produce nonrandom and sometimes targeted, species extinctions.
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    Reconstructing ecological networks with noisy dynamics
    (ROYAL SOC, 2020) Freilich, Mara A.; Rebolledo, Rolando; Corcoran, Derek; Marquet, Pablo A.
    Ecosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the diversity of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the network structure of ecosystems from time series of species abundance, but it is not clear how well can networks be reconstructed, especially in the presence of stochasticity that propagates through ecological networks. We evaluate the effects of intrinsic noise and network topology on the performance of different methods of inferring network structure from time-series data. Analysis of seven different four-species motifs using a stochastic model demonstrates that star-shaped motifs are differentially detected by these methods while rings are differentially constructed. The ability to reconstruct the network is unaffected by the magnitude of stochasticity in the population dynamics. Instead, interaction between the stochastic and deterministic parts of the system determines the path that the whole system takes to equilibrium and shapes the species covariance. We highlight the effects of long transients on the path to equilibrium and suggest a path forward for developing more ecologically sound statistical techniques.