A global climate model ensemble for downscaled monthly climate normals over North America

Mahony, Colin; Wang, Tongli; Hamann, Andreas; Cannon, Alex J.

doi:10.1002/joc.7566

Cited by 63 publications

(37 citation statements)

References 55 publications

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“…For each climate scenario, temperature values were based on an ensemble of 13 ESMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) designed for robust downscaling of monthly climate normals (2081 to 2100). These 13 selected ESMs are representative of the distribution of equilibrium climate sensitivity, which include ACCESS-ESM1-5, BCC-CSM2-MR, CNRM-ESM2-1, CanESM5, EC-Earth3, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL ( 54 , 76 ). A preliminary analysis showed that monthly temperature projections from the mean of the 13-model ensemble had the least difference from observed historical temperature for the central PPR.…”

Section: Methodsmentioning

confidence: 99%

Large increases in methane emissions expected from North America’s largest wetland complex

et al. 2023

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Natural methane (CH 4 ) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH 4 flux dataset (~19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH 4 emissions from the Prairie Pothole Region (PPR), North America’s largest wetland complex. Plot-scale CH 4 emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH 4 emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH 4 emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH 4 concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century.

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Section: Methodsmentioning

confidence: 99%

Large increases in methane emissions expected from North America’s largest wetland complex

et al. 2023

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“…We obtained climate data from the AdaptWest database (AdaptWest Project, 2021; Mahony et al, 2022; Wang et al, 2016) for climate variables for the current (1991–2020) and future (2071–2100) time periods. We used data for future climate scenario (CMIP6) associated with shared socioeconomic pathways (SSPs) to examine the degree to which habitat suitability differed under these alternative pathways.…”

Section: Methodsmentioning

confidence: 99%

Unpacking the ‘black box’: Improving ecological interpretation of regression‐based models

Prasad

Peters

Matthews

et al. 2023

Diversity and Distributions

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Aim Many tree species distribution models use black‐box machine learning techniques that often neglect interpretative aspects and instead focus mainly on maximizing predictive accuracy. In this study, we outline an interpretative modelling framework to gain better ecological insights while mapping abundance patterns of six North American species. Location Continental United States and Canada. Methods We develop an innovative procedure using regression trees by stabilizing variance, and mapping dominant rules which we term ‘optimized regression tree bagging for interpretation and mapping’ (ORTBIM). We apply this technique to understand ecological features influencing the abundance patterns of three eastern (Pinus strobus, Acer saccharum and Quercus montana), and three western (Picea engelmannii, Pinus ponderosa and Pseudotsuga menziesii) tree species in North America. For these species, we assess and map the dominant climate–terrain interactions that partly determine abundance patterns in the eastern and western regions. In the process, we examine the role of varying responses and scales and explore finer‐scale species climate–terrain niches and non‐linear relationships. Results Our study emphasizes the prominent role of elevation and heat–moisture variables in the west and the greater importance of seasonal precipitation and seasonal temperature in the east. The abundance patterns under future climate (SSP5‐8.5) show climate–terrain habitats shifting northward and westward into Canada and Alaska for the eastern species, and predominantly north‐westward for the western species. Conclusion Our interpretative modelling framework can be used to gain a more comprehensive understanding of the abundance patterns across the full species range, formulate better predictive models and facilitate improved management practices under climate change.

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“…As suggested by edge detection theory (Dakos et al 2012), the strength and direction the monthly correlation coefficients may also be interpreted as an indicator of the risk of threshold transgressions at the level of species assemblages (Trisos et al 2020), which are of particular interest to resource managers and conservationists (Millar and Stephenson 2015). A formal analysis of threats due to threshold transgressions would require inclusion of climate change projections, but given average ensembles of CMIP6 projections that project warmer and drier conditions for the Southwest (Mahony et al 2022), climate limitations from this analysis suggest that tree populations in this region are highly vulnerable to continued future declines. This has also already been documented based on past climate change trends over the last several decades (e.g.…”

Section: Implications and Management Applicationsmentioning

confidence: 99%

Climatic limiting factors of North American ecosystems: a remote-sensing based vulnerability analysis

Sang

Hamann

2022

Environ. Res. Lett.

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Remote-sensing based vulnerability assessments to climate change are a research priority of critical importance for landscape-scale efforts to prioritize conservation and management of ecosystems. Limiting climatic factors can serve as a proxy for quantifying ecosystem vulnerability, since theory predicts that ecosystems close to critical climate thresholds will be more sensitive to interannual variation in limiting climate factors. Here, we analyze time series of enhanced vegetation index (EVI) data for continental-scale vulnerability assessments. The analytical approach is a lagged monthly correlation analysis that accounts for memory effects from the previous growing season. Mapping multivariate correlation coefficients reveals that drought vulnerabilities can be found across the continent, including a distinct geographic band across the western boreal forest. The analytical approach reveals climate dependencies at high spatial and temporal resolution, with the direction and strength of correlation coefficients indicating the risk of threshold transgressions at the edge of species and ecosystem tolerance limits. The approach is further useful for hypothesis testing of contributing non-climatic factors to climatic vulnerability, allowing locally targeted management interventions to address climate change.

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A global climate model ensemble for downscaled monthly climate normals over North America

Cited by 63 publications

References 55 publications

Large increases in methane emissions expected from North America’s largest wetland complex

Large increases in methane emissions expected from North America’s largest wetland complex

Unpacking the ‘black box’: Improving ecological interpretation of regression‐based models

Climatic limiting factors of North American ecosystems: a remote-sensing based vulnerability analysis

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