Data from: A new tool to improve the estimates of interaction rewiring considering the whole community composition
Data files
May 27, 2024 version files 116.94 KB
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01_Conventional_vs_INIS_Qualitative.xlsx
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01_Conventional_vs_INIS_Quantitative.xlsx
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02_SamplingEffort_Interannual.xlsx
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02_SamplingEffort_Seasonal.xlsx
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03_SamplingCompleteness.xlsx
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README.md
Abstract
Understanding temporal dynamics in ecological networks is crucial to predicting their capability to cope with global changes. Despite this, proper quantification of network dynamics still remains a challenge. Temporal dynamics are typically studied using data of interaction networks over time, through the evaluation of interaction turnover and its two components: changes related to species turnover (species gains and losses) or rewiring (switching partners among the set of species shared over time). However, with this approach based exclusively on network data, dynamics are computed similarly for species that are truly missing from the community at a given temporal period, and for species occurring in the community but that do not interact with any other. This might lead to an underestimation of the real extent of rewiring, while overestimating the species turnover component of interaction turnover.
We used data on 20 plant-pollinator communities to calculate interaction turnover components accounting also for the species that occurred in the communities at different temporal periods but did not appear in some of the temporal interaction networks (non-interacting species), and then compared these estimates with conventional ones. Besides, we used empirical data and simulations to evaluate the extent to which dynamics estimates were affected by sampling effort when including and excluding non-interacting species.
As expected, disregarding the non-interacting species that occur in the communities at different temporal periods leads to the underestimation of rewiring and the overestimation of species turnover as components of interaction turnover. Effect size was moderate when independent pollinator data were included, and large when including plants or both trophic levels. Simulations indicated that, in general, considering the non-interacting species reduced biases at the time of identifying changes due to the different interaction turnover components. Accounting for non-interacting species was particularly important to reduce bias when sampling effort was low and when dynamics were calculated seasonally. Despite sampling effort effects, phenology was the main determinant of species’ rewiring frequencies.
Our approach contributes to reducing biases and improving the estimates of interaction flexibility in networks, which are necessary to comprehend the response of communities in the face of global change.
README: Data from: A new tool to improve the estimates of interaction rewiring considering the whole community composition
https://doi.org/10.5061/dryad.ffbg79d38
Data used in the analyses of the paper "A new tool to improve the estimates of interaction rewiring considering the whole community composition".
Description of the data and file structure
01_Conventional_vs_INIS_Qualitative.xlsx and 01_Conventional_vs_INIS_Quantitative.xlsx contain the values of Interaction turnover and its components estimated in 20 natural communities in Mallorca Island (Gómez-Martínez et al. 2022, Lázaro et al. 2022), following the Conventional or the INIS approach, and using Qualitative or Quantitative data. Description of each variable within the file.
02_SamplingEffort_Interannual.xlsx contains the values of Interaction turnover and its components between plant-pollinator interaction networks of 2016 and 2017 in Son Bosc, Mallorca Island (Lázaro et al. 2020), with an increasing sampling effort estimated by accumulating sampling days. Description of each variable within the file.
02_SamplingEffort_Seasonal.xlsx contains the values of Interaction turnover and its components between plant-pollinator interaction networks of different sampling days in Son Bosc, Mallorca Island (Lázaro et al. 2020), with an increasing sampling effort estimated by accumulating minutes of sampling. Description of each variable within the file.
03_SamplingCompleteness.xlsx contains the rewiring events of species (pollinators and plants) in 2016 and 2017 in Son Bosc, Mallorca Island (Lázaro et al. 2020) following the Conventional and the INIS approach, and the sampling completeness of interactions for each species. Description of each variable within the file.
References
Gómez-Martínez, Carmelo, Miguel A. González-Estévez, Joana Cursach, and Amparo Lázaro. 2022. “ Pollinator Richness, Pollination Networks, and Diet Adjustment along Local and Landscape Gradients of Resource Diversity.” Ecological Applications 32(6): e2634. https://doi.org/10.1002/eap.2634
Lázaro, A., & Gómez-Martínez, C. (2022). Habitat loss increases seasonal interaction rewiring in plant–pollinator networks. Functional Ecology, 36, 2673–2684. https://doi.org/10.1111/1365-2435.14160
Lázaro A, Gómez-Martínez C, Alomar D, González-Estévez MA, Traveset A. Linking species-level network metrics to flower traits and plant fitness. J Ecol. 2020; 108: 1287–1298. https://doi.org/10.1111/1365-2745.13334