Biology subjects

Bastazini, V. A. G.

Publications and source records attributed to Bastazini, V. A. G..

4 recordsLinked to original sources

bioRxiv2024

Wildlife-vehicle collisions simplify regional food webs

Roads stands as major threats to biodiversity, affecting the functioning of ecosystems and their provision of ecosystem services. Understanding how road-related impacts affect the dynamics of ecological interactions is essential to help manage human impacts on biodiversity, but such studies remain largely unexplored. We investigated the intricate relationship between roads, species vulnerability to road density, and the ensuing effects on food webs across Europe. Utilizing species-specific road density thresholds and trophic interaction data, we constructed regional food webs to assess the potential loss of trophic interactions due to roadkill. Our analysis, encompassing 551 species across three trophic levels, revealed spatially varied impacts, with areas surrounding major cities facing drastic losses of trophic interaction exceeding 90%. Notably, 191 species may be affected by trophic interaction losses (loss of prey or predator). Apex predators exhibited lower direct impacts from road density, while basal-level species seem to be more exposed to direct road-related effects, potentially triggering a cascade of interaction disruptions. Our findings emphasize the need for informed road infrastructure development and targeted conservation strategies to mitigate the negative impacts of roads and traffic, thereby preserving the integrity of ecological networks. This research offers valuable insights for policymakers and conservation practitioners globally by identifying critical areas where road-induced cascade effects may be most pronounced and highlighting trophic groups of species that may be at higher risk.

ecology↗

bioRxiv2021

The role of evolutionary modes for trait-based cascades in mutualistic networks

The erosion of functional diversity may foster the collapse of ecological systems. Functional diversity is ultimately determined by the distribution of species traits. As species traits are a legacy of species evolutionary history, one might expect that the mode of trait evolution influences community resistance under the loss of functional diversity. In this paper, we investigate the role of trait evolutionary dynamics on the robustness of mutualistic networks undergoing the following scenarios of species loss: i) random extinctions, ii) loss of functional distinctiveness and iii) extinctions biased towards larger sizes. We simulated networks defined by models of single trait complementary and evolutionary modes where traits can arise in recent diversification events with weak phylogenetic signal, in early diversification events with strong phylogenetic signal, or as a random walk through evolutionary time. Our simulations show that mutualistic networks are especially vulnerable to extinctions based on trait distinctiveness and more robust to random extinction dynamics. The networks show an intermediate level of robustness against size-based extinctions. Despite the small range of variation in network robustness, our results show that the mode of trait evolution matters for network robustness in all three scenarios. Networks with low phylogenetic signal are more robust than networks with high phylogenetic signal across all scenarios. As a consequence, our results predict that mutualistic networks based upon current adaptations are more likely to cope with extinction dynamics than those networks that are based upon conserved traits.

ecology↗

bioRxiv2017

Loss of generalist plant species and functional diversity decreases the robustness of a seed dispersal network

Understanding cascading effects of species loss has become a major challenge for ecologists. Traditionally, the robustness of ecological networks has been evaluated based on simulation studies where primary extinctions occur at random or as a function of species specialization, ignoring other important biological factors. Here, we estimate the robustness of a seed dispersal network from a grassland-forest mosaic in southern Brazil, simulating distinct scenarios of woody plant species extinction, including scenarios where species are eliminated based on their evolutionary and functional distinctiveness. Our results suggest that the network is more robust when species are eliminated based on their evolutionary uniqueness, followed by random extinctions, the extinction of the most specialist species, functional distinctiveness and, at last, when the most generalist species are sequentially eliminated. Our results provide important information for grassland-forest mosaic management, as they indicate that loss of generalist species and functional diversity makes the system more likely to collapse.

ecology↗

bioRxiv2016

Assessing sampling sufficiency of network metrics using bootstrap

Sampling the full diversity of interactions in an ecological community is a highly intensive effort. Recent studies have demonstrated that many network metrics are sensitive to both sampling effort and network size. Here, we develop a statistical framework, based on bootstrap resampling, that aims to assess sampling sufficiency for some of the most widely used metrics in network ecology, namely connectance, nestedness (NODF-nested overlap and decreasing fill) and modularity (using the QuaBiMo algorithm). Our framework can generate confidence intervals for each network metric with increasing sample size (i.e., the number of sampled interaction events, or number of sampled individuals), which can be used to evaluate sampling sufficiency. The sample is considered sufficient when the confidence limits reach stability or lie within an acceptable level of precision for the aims of the study. We illustrate our framework with data from three quantitative networks of plant and frugivorous birds, varying in size from 16 to 115 species, and 17 to 2,745 interactions. These data sets illustrate that, for the same dataset, sampling sufficiency may be reached at different sample sizes depending on the metric of interest. The bootstrap confidence limits reached stability for the two largest networks, but were wide and unstable with increasing sample size for all three metrics estimated based on the smallest network. The bootstrap method is useful to empirical ecologists to indicate the minimum number of interactions necessary to reach sampling sufficiency for a specific network metric. It is also useful to compare sampling techniques of networks in their capacity to reach sampling sufficiency. Our method is general enough to be applied to different types of metrics and networks.

ecology↗