Woodwell Climate Research Center
  • Falmouth, United States
Recent publications
Plain Language Summary Lakes and ponds are key indicators of the Arctic's vulnerability to rapid warming. Their presence influences the water cycle, wildlife habitat, permafrost temperatures, and the balance between carbon storage and release to the atmosphere. Scientists expect permafrost thaw to cause lake area to decline over time, representing a major shift in the landscape with consequences for ecosystems, water resources, and carbon cycling. The extent of lake drainage across the northern permafrost zone remains unclear, especially given recent studies that have found both increasing and decreasing lake area. Here, we demonstrate that differences in glacial history and geology can explain many of the conflicting trends reported in these previous studies. We show that thawing permafrost tends to reduce lake area in regions without past glaciation. However, in regions shaped by glaciers, lake areas can slightly increase with permafrost thaw. To do this, we use the new the Alaska Lake and Pond Occurrence Data set, which maps over 800,000 lakes and ponds and their seasonal fluctuations in unprecedented detail. We discuss potential mechanisms for long‐term landscape evolution to influence modern lake responses to permafrost thaw. Finally, we use our results to improve projections of future changes to lake area across Alaska.
The loss of ecosystem carbon (the sum of vegetation, litter, and soil carbon) may occur in a permafrost region under mitigation pathways, which could reduce the efficiency of carbon dioxide removal. Here, we investigate changes in permafrost under net-zero and negative emissions, based on idealized emission-driven simulations using a state-of-the-art Earth system model. While acting as a net ecosystem carbon sink during most of the positive emission phase, permafrost becomes a net ecosystem carbon source just before reaching net-zero and negative emissions. Permafrost slowly recovers, especially in regions with high organic carbon content, and net ecosystem carbon loss persists until the end of simulations, resulting in a cumulative net ecosystem carbon loss of approximately 14 petagrams of carbon (PgC) in both scenarios. In addition, methane emissions increase under net-zero and negative emissions, due to the irreversibility of the inundated areas. We conclude that the permafrost ecosystem carbon loss may continue under net-zero and negative emissions, which could hinder climate change mitigation efforts.
Heat-health early warning systems (HHWS) are an important collaborative activity between the meteorological and health communities. This study aimed to map the evidence on the socioeconomic assessment of HHWS and their effectiveness in terms of averting heat related health outcomes. It also aimed to map the technical, structural, and societal barriers and facilitators to implementation and use of HHWS. We use two methods: (i) a scoping review of literature on the economic assessment and health benefit of climate services for heat-health adaptation (ii) a set of interviews with climate service developers and providers in Europe and Africa to understand further technical and societal aspects as well as evaluation of such services. We find that HHWS can be a cost-effective adaptation option that can reduce heat-related mortality and morbidity, especially in vulnerable groups like the elderly. We find that challenges such as lack of long-term and reliable funding, difficulties in making the climate data relevant, comprehensible, and accessible to different end-users, cultural differences between climate and health professionals, and limited ability to assess the services' real impact need to be accounted for while implementing these services.
Understanding how the traits of lineages are related to diversification is key for elucidating the origin of variation in species richness. Here, we test whether traits are related to species richness among lineages of trees from all major biogeographical settings of the lowland wet tropics. We explore whether variation in mortality rate, breeding system and maximum diameter are related to species richness, either directly or via associations with range size, among 463 genera that contain wet tropical forest trees. For Amazonian genera, we also explore whether traits are related to species richness via variation among genera in mean species-level range size. Lineages with higher mortality rates—faster life-history strategies—have larger ranges in all biogeographic settings and have higher mean species-level range sizes in Amazonia. These lineages also have smaller maximum diameters and, in the Americas, contain dioecious species. In turn, lineages with greater overall range size have higher species richness. Our results show that fast life-history strategies influence species richness in all biogeographic settings because lineages with these ecological strategies have greater range sizes. These links suggest that dispersal has been a key process in the evolution of the tropical forest flora.
Climate change has resulted in an increase in heat exposure globally. There is strong evidence that this increased heat stress is associated with poor maternal and fetal outcomes, especially in vulnerable populations. However, there remains poor understanding of the biological pathways and mechanisms involved in the impact of heat in pregnancy. This observational cohort study of 764 pregnant participants based in sub-Saharan Africa, a geographical region at risk of extreme heat events, aims to evaluate the physiological and biochemical changes that occur in pregnancy due to heat stress. The key objectives of the study are to 1) map exposure to heat stress in the cohort and understand what environmental, social and community factors increase the risk of extreme heat exposure; 2) assess the impact of heat stress on maternal health, e.g. heat strain, subjective psychological well-being, sleep and activity level; 3) evaluate how heat stress impacts placenta structure and function; 4) determine how chronic heat exposure impacts birth outcomes; and 5) explore the epigenetic changes in the placenta and infant by heat stress exposure per trimester. Pregnant women will be recruited from two distinct regions in The Gambia to exploit the naturally occurring heat gradient across the country. Microclimate mapping of the area of recruitment will give detailed exposure measurements. Participants will be asked to wear a watch-style device at 28- and 35-weeks gestational age to evaluate maternal heart rate, activity and sleep. At the end of the week, an ultrasound scan will be performed to evaluate fetal size and placental blood flow. At delivery, birth outcomes will be recorded and maternal, placental and cord samples taken for epigenetic, biochemical and histological evaluation. Evaluation of neuro-behaviour and final infant samples will be taken at 1 month following birth.
Recent advances in hardware technology have enabled the development of handheld sensors with comparable performance to laboratory‐grade near‐infrared (NIR) spectroradiometers. In this study, we explored the effect of the uncertainty from the NeoSpectra Scanner Handheld NIR Analyzer (Si‐Ware) on estimating farm‐level soil organic carbon (SOC) stocks at three small farms in Massachusetts, USA. A field campaign conducted in Falmouth, MA, collected 192 soil samples from three farms at depths of 0–10, 10–20 and 20–30 cm. All samples were scanned both in the field at field moisture and under laboratory conditions after being dried and sieved. Samples were analysed for SOC via elemental analysis, while bulk density was determined after weighing the dry fine earth sampled with cylindrical cores in the field. Several strategies for spectral prediction were tested for estimating SOC content and bulk density (BD) using both moist and dry scans, including testing the application of prebuilt models from the Open Soil Spectral Library. Cubist was used to train all models, and conformal prediction was used to estimate the prediction intervals to one standard deviation. The Cholesky decomposition algorithm allowed us to consider the correlation between variables over the three depth layers during uncertainty propagation with Monte Carlo to come up with robust estimates of field‐scale SOC stocks and uncertainty. This analysis revealed that spectroscopy predictions, although less precise, can detect the same statistical patterns in SOC stock across farms at a large cost savings compared with the traditional analytical methods.
Chaparral, a semi‐arid Mediterranean plant community, has the potential to act as a sink, which is an essential ecosystem to mitigate climate change. However, soil respiration (Rs) responses to meteorological variables remain uncertain in these regions, and no studies have quantified how much Rs attributes to Reco in chaparral shrublands. This study identifies the effects of soil temperature (Ts) and soil water content (SWC) on upscaled Rs and its contribution to Reco (Rs/Reco) in chaparral shrublands in Southern California between 2020 and 2021. Hourly Rs and net ecosystem exchange (NEE) were collected by automated chambers and the eddy covariance technique, respectively. Due to high daily variability and gaps in our data, 5‐day averages were calculated to understand the effects of meteorological on Rs and Rs/Reco. First, we proposed that SWC was the primary driver of Rs regardless of the season, while Ts effects were prominent when SWC was sufficient. Secondly, we hypothesized Rs/Reco to vary seasonally, particularly due to Rs contributing less under dry conditions. Our results showed SWC to have a strong significant effect on Rs throughout the year, whereas Ts was only a significant control when the soil was wet and Ts was below 20°C. Monthly Rs/Reco was highest during January and February, likely due to the reduced aboveground respiration. While Rs/Reco was lowest when the soil was the driest. These findings improve our understanding of Rs response to climatic conditions and emphasize the importance of estimating Rs/Reco in chaparral shrublands.
Earth’s transient climate response (TCR) quantifies the global mean surface air temperature change due to a doubling of atmospheric CO2 concentration after 70 years of a compounding 1% per year increase. TCR is highly correlated with near-term climate projections, and thus of relevance for climate policy, but remains poorly constrained in part due to uncertainties in the representation of key physical processes in Earth System Models (ESMs). Within state-of-the-art ESMs participating in the Coupled Model Intercomparison Project (CMIP6), the TCR range (1.1 ∘C–2.9 ∘C) is too wide to offer useful guidance to policymakers. Similarly, the sixth report of the Intergovernmental Panel on Climate Change, while not solely reliant on ESMs for its TCR assessment, produced a very likely range of 1.2 ∘C–2.4 ∘C. To complement earlier, ESM-based, estimates, we here present a new TCR estimate of 2.17 (1.72–2.77) ∘C (95% confidence interval), derived based on a statistical relationship between surface air temperature and observational proxies for its main drivers, i.e. changes in atmospheric greenhouse gases and aerosols. We show that, within uncertainty, this method correctly diagnoses TCR from 20 CMIP6 ESMs if the same input variables are taken from the ESMs that are available from observations. This increases confidence in the new observation-based central estimate and range, which is respectively higher and narrower than the mean and spread of the estimates from the entire ensemble of CMIP6. Many ESM-based estimates tend to produce TCRs lower than the observational range reported here. Our findings suggest that a misrepresentation of the aerosol cooling effect could be the cause of this discrepancy. Further, the revised TCR estimate suggests a downward revision of the remaining carbon budgets aligned with the overarching goal of the Paris agreement.
Extreme weather events influence carbon cycling and lead to pervasive changes in ecosystem structure and function. Vegetation at high latitudes and in alpine bioclimatic zones can be particularly sensitive to winter warming events, which are short‐lived climatic events where temperatures are unusually high and often include rainfall. With climate change the frequency and severity of winter warming events are increasing. We report here from a field experiment on a lichen‐dominated ridge at a high mountain plateau in central Norway. This is a common vegetation type at high latitudes and altitudes, yet little is known about ecophysiological responses to winter warming events in lichens, and how it may differ from responses in bryophytes and vascular plants. We ran a week‐long simulation of vegetation stress from winter warming events through thaw–freeze and ice encasement, during late winter in 2021 and 2022. The thaw–freeze treatment had minor effects on summer ecophysiology in lichens (Cladonia mitis, Cetraria islandica and Nephromopsis nivalis), while the species N. nivalis and to a lesser extent, C. mitis had reduced vitality after the ice encasement treatment. Contrastingly, the bryophyte Polytrichum juniperinum, and vascular plant Empetrum nigrum had reduced photosynthetic efficiency and seasonal growth in both thaw–freeze and ice encasement treatments. The ice encasement treatment was overall more lethal and led to reduced NDVI (Normalised Difference Vegetation Index). However, reduction in vitality of vascular and non‐vascular plants was not enough to impact overall ecosystem carbon flux. Synthesis: The lichen's stronger tolerance against thaw–freeze and ice encasement than co‐existing plants oppose the general effects of summer climate warming, where lichens may succumb under greater plant‐growth and warmer soils. This study advocates for the importance of year‐round ecology to understand vegetation change under climate change.
Land surface models require continuous validation against observations to improve and reduce simulation uncertainty. However, inferred model performance can be heavily influenced by subjective choices made in the selection and application of observational data products. A key area often misrepresented by models is the Arctic–Boreal region, which is a potential tipping point region in Earth’s climate system due to large permafrost carbon stocks that are vulnerable to release with climate warming. We use the International Land Model Benchmarking (ILAMB) framework to evaluate how the model skill of TRENDY-v9 models varies based on the choice of observational-based benchmark and how benchmarks are applied in model evaluation. This analysis uses global datasets integrated into ILAMB and new, regionally-specific observational products from the Arctic–Boreal Vulnerability Experiment. Our results cover the overall time period of 1979–2019 and show that model scores can vary substantially depending on the data product applied, with higher model scores indicating better model performance against observations. The lowest model scores occur when benchmarked against regional, compared to global, datasets. We also evaluate observed and modeled functional relationships between ecosystem respiration and air temperature and between gross primary production and precipitation. Here, we find that the magnitude and shape of the responses are strongly impacted by the choice of observational dataset and the approach used to construct the functional relationship benchmark. These results suggest that model evaluation studies could conclude a false sense of model skill if only using a single benchmark data product or if not applying regional data products when performing a regional model analysis. Collectively, our findings highlight the influence of benchmarking choices on model evaluation and point to the need for benchmarking guidelines when assessing model skill.
Pyrogenic carbon (PyC) from biomass burning is a large, but poorly quantified, slow‐cycling component of the soil organic carbon pool. Modeling of soil carbon dynamics can be improved by including the processes governing the input and cycling of PyC in the soil. The carbon isotope composition of PyC (δ¹³CPyC) provides a tracer for the partitioning of PyC into the soil from biomass. We report the stocks and δ¹³C values for PyC and organic carbon (OC) for 41 regions dominated by savannas and seasonally wet to arid regions of Australia and Africa. Stocks of PyC in the 0–5 cm interval ranged from 0 to 1.17 MgC ha⁻¹ (mean 0.43 ± 0.25 MgC ha⁻¹) and in the 0–30 cm interval ranged from 0.25 to 3.89 MgC ha⁻¹ (mean 1.65 ± 0.77 MgC ha⁻¹). PyC stocks averaged 8% (but were up to 25%) of total organic carbon (TOC) stocks. Stocks tended to highest in relatively wet, but seasonally dry, regions such as tropical savannas. PyC abundance could be predicted (r = 0.8 to 0.95) from environmental variables only. δ¹³CPyC values varied widely between regions, but with no systematic differences within regions related to current vegetation or sample depth, likely due to the long residence time of PyC in the soil. δ¹³CPyC values were strongly correlated with δ¹³COC values but were systematically 1–2‰ higher even in C3 only regions.
Antarctic toothfish are a commercially exploited upper‐level predator in the Southern Ocean. As many of its prey, the ectothermic, water‐breathing Antarctic toothfish is specifically adapted to the temperature and oxygen conditions present in the high‐latitude Southern Ocean. Additionally, the life cycle of Antarctic toothfish depends on sea‐ice dynamics and the transport of individuals by currents between regions with different prey. To assess the impact of 21st‐century climate change on potential interactions of Antarctic toothfish and its prey, we here employ the extended aerobic growth index (AGI), which quantifies the effect of ocean temperature and oxygen levels on the habitat viability of individual species. We quantify changes in predator–prey interactions by a change in viable habitat overlap as obtained with the AGI. As environmental data, we use future projections for four emission scenarios from the model FESOM‐REcoM, which is specifically designed for applications on and near the Antarctic continental shelf. For the two highest‐emission scenarios, we find that warming and deoxygenation in response to climate change cause a subsurface decline of up to 40% in viable habitat overlap of Antarctic toothfish with important prey species, such as Antarctic silverfish and icefish. Acknowledging regional differences, our results demonstrate that warming and deoxygenation alone can significantly perturb predator–prey habitat overlap in the Southern Ocean. Our findings highlight the need for a better quantitative understanding of climate change impacts on Antarctic species to better constrain future ecosystem impacts of climate change.
Deforestation and forest degradation are of continued and growing concern for biodiversity loss, carbon emissions, and a host of ecosystem services for local and global communities. Current remote sensing-based products of forest condition offer valuable information, but typically require extensive training data and represent snapshots in time. Here we provide complementary analyses that address some of these limitations by quantifying forest stability, a key component of ecosystem integrity, of wet tropical forests in the Amazon Basin over a 20-year period using an unsupervised classification method and identify areas of primary and secondary forest. Canopy stability was explored using a time series of remotely sensed MODIS data for the period 2003–2019 at a 500 m pixel resolution. We built on previous work to develop a pixel-based Canopy Stability Index based on the slope and coefficient of variation in fPAR (the fraction of photosynthetically active radiation intercepted by sunlit vegetation canopy) and SIWSI (the shortwave infrared water stress index), which collectively provide information on biophysical processes, canopy structure, and water stress. We examined temporal trends in canopy responses to environmental factors, natural disturbances and land use impacts and compared our results with the MapBiomas forest condition product. Analyses were focused on the Brazilian Amazon but extended to the entire Amazon Basin. The findings revealed a high level of agreement between the Canopy Stability Index and forest categories classified by MapBiomas. However, notable mismatches exist, particularly in ecoregions which contain non-forest ecosystems (e.g., Guianan Highlands Moist Forests, Gurupa varzea, and Pantepui forests and shrublands). Disturbances such as fires are correlated with high levels of canopy instability. The time series analysis revealed prior land use impacts and the occurrence of otherwise unrecognized degraded forest. High resolution modelled data on forest structure can be usefully complemented in tropical wet forests by the kinds of time series analyses presented here, which can assist in tracking changes in forest condition and responses to disturbances.
Arctic ecosystems are experiencing extreme climatic, biotic and physical disturbance events that can cause substantial loss of plant biomass and productivity, sometimes at scales of >1000 km². Collectively known as browning events, these are key contributors to the spatial and temporal complexity of Arctic greening and vegetation dynamics. If we are to properly understand the future of Arctic terrestrial ecosystems, their productivity, and their feedbacks to climate, understanding browning events is essential. Here we bring together understanding of browning events in Arctic ecosystems to compare their impacts and rates of recovery, and likely future changes in frequency and distribution. We also seek commonalities in impacts across these contrasting event types. We find that while browning events can cause high levels of plant damage (up to 100% mortality), ecosystems have substantial capacity for recovery, with biomass largely re-established within five years for many events. We also find that despite the substantial loss of leaf area of dominant species, compensatory mechanisms such as increased productivity of undamaged subordinate species lessen the impacts on carbon sequestration. These commonalities hold true for most climatic and biotic events, but less so for physical events such as fire and abrupt permafrost thaw, due to the greater removal of vegetation. Counterintuitively, some events also provide conditions for greater productivity (greening) in the longer-term, particularly where the disturbance exposes ground for plant colonisation. Finally, we find that projected changes in the causes of browning events currently suggest many types of events will become more frequent, with events of tundra fire and abrupt permafrost thaw expected to be the greatest contributors to future browning due to their severe impacts and occurrence in many Arctic regions. Overall, browning events will have increasingly important consequences for ecosystem structure and function, and for feedback to climate.
Circulation budgets can identify physical processes underpinning tropical cyclones, mesoscale convective vortices, and other weather systems where there are interactions across scales. It is unclear, however, how well these budgets close in practice. The present study uses the rapid intensification of Tropical Cyclone Nepartak (2016) as a case study to quantify the practical limitations of calculating circulation budgets using standard reanalyzes and numerical weather model data. First, we evaluate the circulation budget with ERA5. The budget residual can be reduced considerably by including contributions to circulation changes from subgrid‐scale momentum transports, and reduced further with 24‐hr smoothing, which dampens the discontinuous effects of data assimilation. Second, using a high‐resolution Met Office Unified Model simulation, we examine how the choice of the path used (the domain boundary) affects the budget closure. Third, the truncation errors associated with numerical differentiation in time and space are investigated. The circulation budget improves as the model data are analyzed with more frequent time output intervals, and as the output grid spacing decreases. For the tropical convective examples evaluated here, the column mean budget residuals increase by up to 50% as the output intervals increase from 5 min to 3 hr. Errors also increase if the data are regridded to a coarser horizontal grid spacing and when convection straddles the domain boundary. A key result is that the circulation budget need not close for physical inferences made about the circulation and its evolution to be meaningful, thus validating the use of the technique in prior studies.
Previous health impact assessments of temperature-related mortality in Europe indicated that the mortality burden attributable to cold is much larger than for heat. Questions remain as to whether climate change can result in a net decrease in temperature-related mortality. In this study, we estimated how climate change could affect future heat-related and cold-related mortality in 854 European urban areas, under several climate, demographic and adaptation scenarios. We showed that, with no adaptation to heat, the increase in heat-related deaths consistently exceeds any decrease in cold-related deaths across all considered scenarios in Europe. Under the lowest mitigation and adaptation scenario (SSP3-7.0), we estimate a net death burden due to climate change increasing by 49.9% and cumulating 2,345,410 (95% confidence interval = 327,603 to 4,775,853) climate change-related deaths between 2015 and 2099. This net effect would remain positive even under high adaptation scenarios, whereby a risk attenuation of 50% is still insufficient to reverse the trend under SSP3-7.0. Regional differences suggest a slight net decrease of death rates in Northern European countries but high vulnerability of the Mediterranean region and Eastern Europe areas. Unless strong mitigation and adaptation measures are implemented, most European cities should experience an increase of their temperature-related mortality burden.
Irrigation rapidly expanded during the 20th century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP). Results show that irrigation expansion causes a rapid increase in irrigation water withdrawal, which leads to less frequent 2-meter air temperature heat extremes across heavily irrigated areas (≥4 times less likely). However, due to the irrigation-induced increase in air humidity, the cooling effect of irrigation expansion on moist-heat stress is less pronounced or even reversed, depending on the heat stress metric. In summary, this study indicates that irrigation deployment is not an efficient adaptation measure to escalating human heat stress under climate change, calling for carefully dealing with the increased exposure of local people to moist-heat stress.
Vegetation is often viewed as a consequence of long‐term climate conditions. However, vegetation itself plays a fundamental role in shaping Earth's climate by regulating the energy, water, and biogeochemical cycles across terrestrial landscapes. It exerts influence by consuming water resources through transpiration and interception, lowering atmospheric CO2 concentration, altering surface roughness, and controlling net radiation and its partitioning into sensible and latent heat fluxes. This influence propagates through the atmosphere, from microclimate scales to the entire atmospheric boundary layer, subsequently impacting large‐scale circulation and the global transport of heat and moisture. Understanding the feedbacks between vegetation and atmosphere across multiple scales is crucial for predicting the influence of land use and land cover changes, and for accurately representing these processes in climate models. This review discusses the biophysical and biogeochemical mechanisms through which vegetation modulates climate across spatial and temporal scales. Particularly, we evaluate the influence of vegetation on circulation patterns, precipitation, and temperature, considering both long‐term trends and extreme events, such as droughts and heatwaves. Our goal is to highlight the state of science and review recent studies that may help advance our collective understanding of vegetation feedbacks and the role they play in climate.
Recently, the rapid increase in global plastics production has caused variousecological and economic issues, worsened by poor material and waste management.Among the market-based instruments that could help mitigate the environmental impactsof plastics throughout their life-cycle, we evaluate the advantages and limitations ofincorporating a cap-and-trade (CAT) system into future policy mixes. Our aim is toinspire further investigation of CAT’s feasibility rather than presenting it as the ultimatesolution. Drawing from past CAT implementations in domains such as water resourcemanagement and carbon emissions, we outline three key policy design considerations: (1)material and target group identification, (2) cap establishment and permit allocation, and(3) development of a competitive market environment. We explore a three-tieredapproach with global, national, and sectoral caps covering the plastic lifecycle from cradleto grave. While there are viable reasons to consider a plastics CAT, significant challengespersist, which may ultimately limit its implementation. In the context of ongoing UNPlastics Treaty negotiations or future policy developments, this evaluation of CAT can be beneficial for assessing when and how thistool can address the negative externalities of plastics
Glaciers serve as natural archives for reconstructing past changes of atmospheric aerosol concentration and composition. While most ice-core studies have focused on inorganic species, organic compounds, which can constitute up to 90% of the submicrometer aerosol mass, have been largely overlooked. To our knowledge, this study presents the first nontarget screening record of secondary organic aerosol species preserved in a Belukha ice core (Siberia, Russian Federation), ranging from the pre-industrial to the industrial period (1800–1980 CE). We identified a total of 398 molecules, primarily polar and low-volatile compounds. Since the 1950s, the atmospheric aerosol composition has changed, with the appearance of organic molecules, including nitrogen-containing compounds, deriving from enhanced atmospheric reactions with anthropogenic NO x , or direct emissions. In addition, there was a significant increase in the oxygen-to-carbon ratio (+3%) and the average carbon oxidation state (+18%) of the detected molecules compared to the pre-industrial period, suggesting an increased oxidative capacity of the atmosphere.
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