Climate-driven risks to the climate mitigation potential of forests

Science, Journal Year: 2020, Volume and Issue: 368(6497)

Published: June 18, 2020

Risks to mitigation potential of forests Much recent attention has focused on the trees and mitigate ongoing climate change by acting as sinks for carbon. Anderegg et al. review growing evidence that forests' is increasingly at risk from a range adversities limit forest growth health. These include physical factors such drought fire biotic factors, including depredations insect herbivores fungal pathogens. Full assessment quantification these risks, which themselves are influenced climate, key achieving science-based policy outcomes effective land management. Science , this issue p. eaaz7005

Language: Английский

---

Perspectives on the Future of Land Surface Models and the Challenges of Representing Complex Terrestrial Systems

Journal of Advances in Modeling Earth Systems, Journal Year: 2020, Volume and Issue: 12(4)

Published: March 11, 2020

Abstract Land surface models (LSMs) are a vital tool for understanding, projecting, and predicting the dynamics of land its role within Earth system, under global change. Driven by need to address set key questions, LSMs have grown in complexity from simplified representations biophysics encompass broad interrelated processes spanning disciplines biophysics, biogeochemistry, hydrology, ecosystem ecology, community human management, societal impacts. This vast scope complexity, while warranted problems designed solve, has led enormous challenges understanding attributing differences between LSM predictions. Meanwhile, wide range spatial scales that govern heterogeneity, spectrum timescales dynamics, create tractably representing LSMs. We identify three “grand challenges” development use LSMs, based around these issues: managing process parametric across asked changing world. In this review, we discuss progress been made, as well promising directions forward, each challenges.

Language: Английский

---

Process‐Guided Deep Learning Predictions of Lake Water Temperature

Water Resources Research, Journal Year: 2019, Volume and Issue: 55(11), P. 9173 - 9190

Published: Nov. 1, 2019

Abstract The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use advanced deep learning tools. Hybrid models that integrate theory state‐of‐the art empirical techniques have potential improve predictions while remaining true physical laws. This paper evaluates Process‐Guided Deep Learning (PGDL) hybrid modeling framework a use‐case predicting depth‐specific lake temperatures. PGDL model three primary components: temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation energy), and pretraining initialize network synthetic (water temperature from process‐based model). In situ temperatures were used train model, (DL) (PB) model. Model performance was evaluated various conditions, including when training sparse made outside range set. (as measured by root‐mean‐square error (RMSE)) superior DL PB two detailed study lakes, but only included greater variability than period. also performed well extended 68 median RMSE 1.65 °C during test period (DL: 1.78 °C, PB: 2.03 °C; small number lakes or more accurate). case‐study demonstrates integrating scientific into tools shows promise improving many important environmental variables.

Language: Английский

---

A practical guide to selecting models for exploration, inference, and prediction in ecology

Ecology, Journal Year: 2021, Volume and Issue: 102(6)

Published: March 12, 2021

Abstract Selecting among competing statistical models is a core challenge in science. However, the many possible approaches and techniques for model selection, conflicting recommendations their use, can be confusing. We contend that much confusion surrounding selection results from failing to first clearly specify purpose of analysis. argue there are three distinct goals modeling ecology: data exploration, inference, prediction. Once goal articulated, an appropriate procedure easier identify. review highlight strengths weaknesses relative each goals. then present examples prediction using time series butterfly population counts. These show how approach flows naturally goal, leading different selected purposes, even with exactly same set. This illustrates best practices ecologists should serve as reminder recipes cannot substitute critical thinking or use independent test hypotheses validate predictions.

Language: Английский

---

Pollen-based climate reconstruction techniques for late Quaternary studies

Earth-Science Reviews, Journal Year: 2020, Volume and Issue: 210, P. 103384 - 103384

Published: Sept. 28, 2020

Fossil pollen records are well-established indicators of past vegetation changes. The prevalence across environmental settings including lakes, wetlands, and marine sediments, has made palynology one the most ubiquitous valuable tools for studying climatic change globally decades. A complementary research focus been development statistical techniques to derive quantitative estimates conditions from assemblages. This paper reviews commonly used their rationale seeks provide a resource facilitate inclusion in more palaeoclimatic research. To this end, we first address fundamental aspects fossil data that should be considered when undertaking pollen-based climate reconstructions. We then introduce range currently available, history development, situations which they can best employed. review literature on how define robust calibration datasets, produce high-quality reconstructions, evaluate suggest methods products could developed accessibility global usability. continue foster reconstruction methods, promote reporting standards. When established, such standards 1) enable broader application techniques, especially regions where underused, 2) evaluation reproduction individual structuring them evolving open-science era, optimising use as vital means study variability. also strongly encourage developers users palaeoclimate methodologies make associated programming code publicly will further help disseminate these interested communities.

Language: Английский

---

Situating Ecology as a Big-Data Science: Current Advances, Challenges, and Solutions

BioScience, Journal Year: 2018, Volume and Issue: 68(8), P. 563 - 576

Published: May 26, 2018

Ecology has joined a world of big data. Two complementary frameworks define data: data that exceed the analytical capacities individuals or disciplines "Four Vs" axes volume, variety, veracity, and velocity. Variety predominates in ecoinformatics limits scalability ecological science. Volume varies widely. Ecological velocity is low but growing as throughput societal needs increase. big-data systems include situ remote sensors, community resources, biodiversity databases, citizen science, permanent stations. Technological solutions development open code- data-sharing platforms, flexible statistical models can handle heterogeneous sources uncertainty, cloud-computing delivery high-velocity computing to large-volume analytics. Cultural training targeted early current scientific workforce strengthening collaborations among ecologists scientists. The broader goal maximize power, scalability, timeliness insights forecasting.

Language: Английский

---

Seasonality and uncertainty in global COVID-19 growth rates

Proceedings of the National Academy of Sciences, Journal Year: 2020, Volume and Issue: 117(44), P. 27456 - 27464

Published: Oct. 13, 2020

The virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown, as April 2020, whether summer weather will reduce its spread, thereby alleviating strains on hospitals providing time for vaccine development. Early insights from laboratory studies research related viruses predicted that would decline with higher temperatures, humidity, ultraviolet (UV) light. Using current, fine-scaled data global reports infections, we develop a model explains 36% the variation in maximum growth rates based demography (17%) country-specific effects (19%). UV light is most strongly associated lower growth. Projections suggest that, without intervention, decrease temporarily during summer, rebound by autumn, peak next winter. Validation May June 2020 confirms generality climate signal detected. However, uncertainty high, probability weekly doubling >20% throughout absence social interventions. Consequently, aggressive interventions likely be needed despite seasonal trends.

Language: Английский

---

When tree rings go global: Challenges and opportunities for retro- and prospective insight

Quaternary Science Reviews, Journal Year: 2018, Volume and Issue: 197, P. 1 - 20

Published: Aug. 8, 2018

Language: Английский

---

A guide to ecosystem models and their environmental applications

Nature Ecology & Evolution, Journal Year: 2020, Volume and Issue: 4(11), P. 1459 - 1471

Published: Sept. 14, 2020

Language: Английский

---

Towards the fully automated monitoring of ecological communities

Ecology Letters, Journal Year: 2022, Volume and Issue: 25(12), P. 2753 - 2775

Published: Oct. 20, 2022

Abstract High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real‐time automated abiotic components has been possible for some time, biotic components—for example, individual behaviours traits, species abundance distribution—is far more challenging. Recent technological advancements offer potential solutions achieve this through: (i) increasingly affordable high‐throughput recording hardware, which can collect rich multidimensional data, (ii) accessible artificial intelligence approaches, extract ecological knowledge from large datasets. However, automating the facets communities via such technologies primarily achieved at low spatiotemporal resolutions within limited steps workflow. Here, we review existing data processing that enable communities. We then present novel frameworks combine technologies, forming fully pipelines detect, track, classify count multiple species, record behavioural morphological have previously impossible achieve. Based on these rapidly developing illustrate a solution one greatest challenges ecology: ability generate high‐resolution, standardised across complex ecologies.

Language: Английский

---