Thermal Forcing Versus Chilling? Misspecification of Temperature Controls in Spring Phenology Models

Global Ecology and Biogeography, Journal Year: 2024, Volume and Issue: 33(12)

Published: Oct. 28, 2024

ABSTRACT Background Climate‐change‐induced shifts in the timing of leaf emergence during spring have been widely documented and important ecological consequences. However, mechanistic knowledge regarding what controls is incomplete. Field‐based studies under natural conditions suggest that climate‐warming‐induced decreases cold temperature accumulation (chilling) expanded dormancy duration or reduced sensitivity plants to warming temperatures (thermal forcing) spring, thereby slowing rate at which shifting earlier response ongoing climate change. recent argued apparent reductions may arise from artefacts way calculated, while other based on statistical models specifically designed quantify role chilling shown conflicting results. Methods We analysed four commonly used combinations phenology datasets obtained remote sensing ground observations elucidate whether current model‐based approaches robustly how chilling, concert with thermal forcing, conditions. Results show modeling are calibrated using field‐based misspecify as a result inherent parameterised. Our results highlight limitations existing modelling observational data quantifying affects decreasing arising not constrain near‐future towards extra‐tropical ecosystems worldwide.

Language: Английский

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What can we learn from 100,000 freshwater forecasts? A synthesis from the NEON Ecological Forecasting Challenge

Ecological Applications, Journal Year: 2025, Volume and Issue: 35(1)

Published: Jan. 1, 2025

Abstract Near‐term, iterative ecological forecasts can be used to help understand and proactively manage ecosystems. To date, more have been developed for aquatic ecosystems than other worldwide, likely motivated by the pressing need conserve these essential threatened increasing availability of high‐frequency data. Forecasters implemented many different modeling approaches forecast freshwater variables, which demonstrated promise at individual sites. However, a comprehensive analysis performance varying models across multiple sites is needed broader controls on performance. Forecasting challenges (i.e., community‐scale efforts generate while also developing shared software, training materials, best practices) present useful platform bridging this gap evaluate how range methods perform axes space, time, systems. Here, we analyzed from aquatics theme National Ecological Observatory Network (NEON) Challenge hosted Initiative. Over 100,000 probabilistic water temperature dissolved oxygen concentration 1–30 days ahead seven NEON‐monitored lakes were submitted in 2023. We assessed varied among with structures, covariates, sources uncertainty relative baseline null models. A similar proportion skillful both variables (34%–40%), although outperformed forecasting (10 out 29) (6 15). These top performing came classes structures. For temperature, found that skill degraded increases horizons, process‐based models, included air as covariate generally exhibited highest performance, most often accounted lower The where observations divergent historical conditions (resulting poor model performance). Overall, NEON provides an exciting opportunity intercomparison learn about strengths diverse suite advance our understanding ecosystem predictability.

Language: Английский

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Decision‐making under uncertainty for species introductions into ecological networks

Ecology Letters, Journal Year: 2023, Volume and Issue: 26(6), P. 983 - 1004

Published: April 10, 2023

Abstract Ecological communities are increasingly subject to natural and human‐induced additions of species, as species shift their ranges under climate change, introduced for conservation unintentionally moved by humans. As such, decisions about how manage ecosystems introductions considering multiple management objectives need be made. However, the impacts gaining new on ecological difficult predict due uncertainty in characteristics, novel interactions that will produced recipient ecosystem structure. Drawing decision theory, we synthesise literature into a conceptual framework introduction decision‐making based networks high‐uncertainty contexts. We demonstrate application this theoretical surrounding assisted migration both biodiversity service objectives. show can used evaluate trade‐offs between outcomes, worst‐case scenarios, suggest when one should collect additional data, allow improving knowledge system over time.

Language: Английский

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Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adélie penguin abundance time series

Ecological Indicators, Journal Year: 2023, Volume and Issue: 150, P. 110239 - 110239

Published: April 20, 2023

Ecological predictions are necessary for testing whether processes hypothesized to regulate species population dynamics generalizable across time and space. In order demonstrate generalizability, model should be transferable in one or more dimensions, where transferability is the successful prediction of responses outside data bounds. While much known as what makes spatially-oriented models transferable, there no general consensus spatio-temporal ecological series models. Here, we examine intrinsic predictability a series, measured by its complexity, could limit such using an exceptional long-term dataset Adélie penguin breeding abundance collected at 24 colonies around Antarctica. For each colony, select suite environmental variables from Community Earth System Model, version 2 predict growth rates, before assessing how well these environmentally-dependent transfer temporally reliably temporal signals replicate through We show that weighted permutation entropy (WPE), model-free measure recently introduced ecology, varies spatially populations, perhaps response stochastic events. WPE can strongly predictive performance, although this relationship weakened if not constant over time. Lastly, also spatial forecast horizon, which define decay performance with respect physical distance between focal colony predicted colony. Irrespective predictability, horizons all included study surprisingly short our often have similar compared null based on average rates. cases complex, WPE, biologically-motivated mechanistic poor, advise instead used prediction. These likely better capturing relationships rates conditions. recommend provide valuable insights when evaluating designing sampling monitoring programs, appropriateness preexisting datasets making conservation management decisions change.

Language: Английский

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Forecasting insect dynamics in a changing world

Current Opinion in Insect Science, Journal Year: 2023, Volume and Issue: 60, P. 101133 - 101133

Published: Oct. 17, 2023

Predicting how insects will respond to stressors through time is difficult because of the diversity insects, environments, and approaches used monitor model. Forecasting models take correlative/statistical, mechanistic models, integrated forms; in some cases, temporal processes can be inferred from spatial models. Because heterogeneity associated with broad community measurements, are often unable identify explanations. Many present efforts forecast insect dynamics restricted single-species which offer precise predictions but limited generalizability. Trait-based may a good compromise that limits masking ranges responses while still offering insight. Regardless modeling approach, data parameterize forecasting model should carefully evaluated for autocorrelation, minimum needs, sampling biases data. tested using near-term revised improve future forecasts.

Language: Английский

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