Integrated modelling of insect population dynamics at two temporal scales

Dennis, Emily B.; Kéry, Marc; Morgan, Byron J. T.; Coray, Armin; Schaub, Michael; Baur, Bruno

doi:10.1016/j.ecolmodel.2020.109408

Cited by 10 publications

(7 citation statements)

References 36 publications

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“…Finally, to contextualize our results back into the world of modeling practice, we note several key findings from researchers on the forefront of statistical modeling with presence-only data. First, several statistical advances have emerged from research teams to process community sourced survey data to estimate various biodiversity metrics (Dennis et al 2021;Belitz et al 2022). These advancements are exciting and with the integration of emerging technologies, including those from machine-learning (Joseph 2020) we may be approaching a technological boom in biodiversity science, especially as it pertains to reconstructing historical distributions.…”

Section: Discussionmentioning

confidence: 99%

Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America

Shirey

Neupane

Guralnick

et al. 2023

Preprint

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Global climate change has been identified as a major driver of observed insect declines, yet in many regions there are critical knowledge gaps for how communities are responding to climate. Poleward regions are of particular interest because warming is most rapid while biodiversity data are most sparse. Building on recent advances in occupancy modeling of presence-only data, we reconstructed 50 years (1970-2019) of butterfly population trends in response to rising minimum temperatures in one of the most under sampled regions of the continent. Among 90 modeled species, we found that cold-adapted species are far more often in decline compared to their warm-adapted, more southerly distributed counterparts. Further, in a post-hoc analysis using species' traits, we find that species' range-wide average annual temperature and wingspan are a consistent predictor of occupancy changes. Species with warmer ranges and larger wingspans were most likely to be increasing in occupancy. Our results provide the first look at macroscale butterfly biodiversity shifts in a critically under sampled region of North America. Further, these results highlight the potential of leveraging the wealth of presence only data, the most abundant source of historical insect biodiversity. New approaches to the modeling of presence only data will match recent increases in community science participation with sparse historical records to reconstruct trends even in poorly sampled regions.

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Section: Discussionmentioning

confidence: 99%

Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America

Shirey

Neupane

Guralnick

et al. 2023

Preprint

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“…The GAI is also relevant for other taxa, for example birds on migration—see Matechou et al ( 2013 ), beetles—see Dennis et al ( 2021 ) who model the two‐year life cycle of fuliginators, Iberodorcadion fuliginator —and bees—see Matechou et al ( 2018 ) who use a dynamic stopover model to analyze citizen science data on bumblebees, from the BeeWalk scheme. We anticipate that the rGAI package will enhance and enable further research by ecologists and applied statisticians, which can improve our understanding of changes in species' populations and phenology.…”

Section: Discussion/future Avenuesmentioning

confidence: 99%

“…, beetles-seeDennis et al (2021) who model the two-year life cycle of fuliginators, Iberodorcadion fuliginator-and bees-seeMatechou et al (2018) who use a dynamic stopover model to analyze citizen science data on bumblebees, from the BeeWalk scheme. We anticipate that the British Trust for Ornithology, and the Joint Nature Conservation Committee.…”

mentioning

confidence: 99%

rGAI: An R package for fitting the generalized abundance index to seasonal count data

Dennis

Fagard-Jenkin

Morgan

2022

Ecology and Evolution

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The generalized abundance index (GAI) provides a useful tool for estimating relative population sizes and trends of seasonal invertebrates from species' count data and offers potential for inferring which external factors may influence phenology and demography through parametric descriptions of seasonal variation. We provide an R package that extends previous software with the ability to include covariates when fitting parametric GAI models, where seasonal variation is described by either a mixture of Normal distributions or a stopover model which provides estimates of life span. The package also generalizes the models to allow any number of broods/generations in the target population within a defined season. The option to perform bootstrapping, either parametrically or nonparametrically, is also provided. The new package allows models to be far more flexible when describing seasonal variation, which may be dependent on site‐specific environmental factors or consist of many broods/generations which may overlap, as demonstrated by two case studies. Our open‐source software, available at https://github.com/calliste‐fagard‐jenkin/rGAI , makes these extensions widely and freely available, allowing the complexity of GAI models used by ecologists and applied statisticians to increase accordingly.

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“…Despite the commercial and ecological importance of crustaceans worldwide, no previous study used an integrative approach to estimate demographic parameters, and environmental and density-dependence effects on crustacean populations. The use of IPMs to study invertebrate populations is still rare, probably due to the difficulty to mark individuals (Dennis et al, 2021). Crustaceans are particularly more difficult to track because any mark or tag is lost during ecdysis.…”

Section: Discussionmentioning

confidence: 99%

Ocean temperature and density dependence as key drivers of the population dynamics of an intertidal crab at the Brazilian oceanic islands

et al. 2022

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Understanding how climatic and density‐dependent processes affect demography is crucial for predicting population responses to climate change. For marine invertebrates with complex life cycle such as decapod crustaceans, increasing temperatures might affect survival and development of early pelagic stages, whereas high density can increase competition and thus reduce growth and fecundity of older life stages. In this study, we investigate the effects of warm ocean events, body size and density on the population dynamics of the intertidal Sally lightfoot crab (Grapsus grapsus) at the Brazilian oceanic islands. Firstly, we assessed the trends of marine heatwaves (MHW) and positive temperature anomalies (ΔSST+) at the equatorial St Peter and St Paul (SPSP) Archipelago and Rocas Atoll and the subtropical Trindade Island. We then jointly analyzed short‐term count, capture‐recapture and fecundity data, and long‐term population monitoring data (2003–2019) using an integrated population model. Warm ocean events have become more frequent and intense only at the equatorial islands. Increasing MHW frequency positively influenced recruitment in the high‐density SPSP population, while MHW intensity and ΔSST+ frequency had negative impacts. Conversely, no climatic effects were observed for the low‐density Rocas population, which has the largest crabs. Despite a lack of warming in Trindade, this subtropical population with intermediate density and body size was negatively affected by ΔSST+. Our findings revealed population‐specific responses to climate change when accounting for local life history and ecology. Thus, environmental and density‐dependent effects should be broadly considered in future conservation studies regarding ocean warming impacts on marine invertebrate populations.

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Integrated modelling of insect population dynamics at two temporal scales

Cited by 10 publications

References 36 publications

Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America

Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America

rGAI: An R package for fitting the generalized abundance index to seasonal count data

Ocean temperature and density dependence as key drivers of the population dynamics of an intertidal crab at the Brazilian oceanic islands

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