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1. Detecting climate signals in populations across life histories. Global Change Biology

   https://doi.org/DOI: 10.1111/gcb.16041  

   Jenouvrier S., Long M. ( April 2022 , Global change biology)

   Editorial Board, Editor ; Executive Editor, Rachel Shekar ; Assistant Editor, Rhea Bruno ; Co-Founding Editor Harry Smith FRS, University of ; Reviews Editor Danielle Way, Australian National (Ed.)

   Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long-term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate-driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate-driven signals in population dynamics (urn:x-wiley:13541013:media:gcb16041:gcb16041-math-0001). We identify the dependence of urn:x-wiley:13541013:media:gcb16041:gcb16041-math-0002 on the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on urn:x-wiley:13541013:media:gcb16041:gcb16041-math-0003. We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research. 

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2. Climatic Drivers of Deglacial SST Variability in the Eastern Pacific

   https://doi.org/10.1029/2021PA004264  

   Meegan Kumar, Dervla ; Tierney, Jessica E. ; Bhattacharya, Tripti ; Zhu, Jiang ; McCarty, Logan ; Murray, James W. ( October 2021 , Paleoceanography and Paleoclimatology)

   We explore the response of northeastern Pacific sea surface temperature (SST) to deglacial (16–7 ka) climate variability as recorded in‐based SST reconstructions spanning 65°N to 10°S. Included in the analysis is a new 23 kyr SST record from core NH8P from the northwest Mexican Margin. We isolate spatiotemporal patterns in regional SSTs with trend empirical orthogonal function (TEOF) analysis. The dominant TEOF mode reflects deglacial warming associated with rising. Tropical and subtropical SSTs correlated most strongly with this mode, suggesting that the thermodynamic response of the tropical eastern Pacific to greenhouse gas forcing was the dominant driver of regional SST change during deglaciation. The second TEOF mode reflects millennial‐scale variability and is most strongly expressed in subpolar SSTs. The synchronous timing between North Pacific and North Atlantic SST oscillations is evidence for the rapid transmission of millennial‐scale climate perturbations between the basins, likely through an atmospheric teleconnection. SSTs at NH8P have no correlation with either leading TEOF mode as there is minimal change in SST at this site after20 ka. A model simulation of the LGM indicates that glacial cooling was muted in much of the Eastern Pacific Warm Pool (EPWP), in which NH8P lies, due to reductions in latent heat flux. This suggests that the wind‐evaporation‐SST feedback was responsible for the attenuation of EPWP cooling. Overall, this study highlights the distinct latitudinal trends in the Pacific's response to deglaciation.

    

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3. Earlier Ecological Drought Detection by Involving the Interaction of Phenology and Eco‐Physiological Function

   https://doi.org/10.1029/2022EF002667  

   Chang, Qing ; Ficklin, Darren L. ; Jiao, Wenzhe ; Denham, Sander O. ; Wood, Jeffrey D. ; Brunsell, Nathaniel A. ; Matamala, Roser ; Cook, David R. ; Wang, Lixin ; Novick, Kimberly A. ( February 2023 , Earth's Future)

   Meteorological drought indices like the Standardized Precipitation Evaporation Index (SPEI) are frequently used to diagnose “ecological drought,” despite the fact that they were not explicitly designed for this purpose. More recently developed indices like the Evaporative Stress Index (ESI), which is based on the degree of coupling between actual to potential evapotranspiration, may better capture dynamic plant response to moisture limitations. However, the skill of these indices at describing plant water stress is rarely evaluated at sub‐seasonal timescales over which drought evolves. Moreover, it remains unclear how variability in phenological timing impacts and complicates early drought detection. Here, we compared the ability of ESI and SPEI to reflect the dynamics of ecological drought in forests and grasslands, based on anomalies of Gross Primary Productivity (GPP), surface conductance (G_s, a proxy for stomatal conductance), soil moisture, and vapor pressure deficit. ESI performed better than SPEI in capturing the dynamics of GPP andG_s, but still missed early ecological drought signals due to biases linked to earlier onset of spring leaf development. Thus, we developed a modified variant of the ESI () that accounts for the complicating effects of phenological shifts in leaf area index (LAI). Thedetected drought onset up to 7–10 weeks earlier than SPEI and ESI. Additionally, drought onset dates determined fromare close to (±2 weeks) the dates determined from LAI‐corrected anomalies ofG_s, and GPP, as well as the onset dates of soil water deficit and atmospheric aridity.

    

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4. Impact of Changing Concavity Indices on Channel Steepness and Divide Migration Metrics

   https://doi.org/10.1029/2020JF006060  

   Gailleton, Boris ; Mudd, Simon M. ; Clubb, Fiona J. ; Grieve, Stuart W. D. ; Hurst, Martin D. ( October 2021 , Journal of Geophysical Research: Earth Surface)

   The concavity index,, describes how quickly river channel gradient declines downstream. It is used in calculations of normalized channel steepness index,, a metric for comparing the relative steepness of channels with different drainage area. It is also used in calculating a transformed longitudinal coordinate,, which has been employed to search for migrating drainage divides. Avalue of 0.45 is typically assumed in studies. Here we quantify the variability inacross multiple landscapes distributed across the globe. We describe the degree to which both the spatial distribution and magnitude ofandcan be distorted ifis assumed rather than constrained. Differences between constrained and assumedof 0.1 or less are unlikely to affect the spatial distribution and relative magnitude ofvalues, but larger differences can change the spatial distribution ofand in extreme cases invert differences in relative steepness: relatively steep reaches can appear relatively gentle as quantified by. These inversions are function of the range of drainage area in the considered watersheds. We also demonstrate that thecoordinate, and therefore the detection of migrating drainage divides, is sensitive to varying values of. The median of most likelyacross a wide range of mountainous and upland environments is 0.425. This wide range of variability suggests workers should not assume any value for, but should instead calculate a representativefor the landscape of interest, and exclude basins for which this value is a poor fit.

    

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5. Climatic Asynchrony and Hydrologic Inefficiency Explain the Global Pattern of Water Availability

   https://doi.org/10.1029/2022GL101214  

   Jawitz, James W. ; Klammler, Harald ; Reaver, Nathan G. F. ( December 2022 , Geophysical Research Letters)

   The mechanisms underlying observed global patterns of partitioning precipitation () to evapotranspiration () and runoff () are controversially debated. We test the hypothesis that asynchrony between climatic water supply and demand is sufficient to explain spatio‐temporal variability of water availability. We developed a simple analytical model forthat is determined by four dimensionless characteristics of intra‐annual water supply and demand asynchrony. The analytical model, populated with gridded climate data, accurately predicted global runoff patterns within 2%–4% of independent estimates from global climate models, with spatial patterns closely correlated to observations (). The supply‐demand asynchrony hypothesis provides a physically based explanation for variability of water availability using easily measurable characteristics of climate. The model revealed widespread responsiveness of water budgets to changes in climate asynchrony in almost every global region. Furthermore, the analytical model using global averages independently reproduced the Budyko curve () providing theoretical foundation for this widely used empirical relationship.

    

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