How Robust Is the Apparent Break‐Down of Northern High‐Latitude Temperature Control on Spring Carbon Uptake?

Vegetation growth in northern high‐latitudes during springtime is strongly temperature limited, and thus anomalously warm springs are expected to result in an increased drawdown of carbon dioxide (CO2). However, a recent analysis of the relationship between spring temperature anomalies and atmospheric CO2 anomalies at Point Barrow, Alaska, suggests that the link between spring carbon uptake by northern ecosystems and temperature anomalies has been weakening over recent decades due to a diminishing control of temperature on plant productivity. Upon further analysis, covering the 1982‐2015 period, we found no significant change in the relationship between spring vegetation productivity derived from remote sensing data and air temperature. We showed that a reduction in spatial coherence of temperature anomalies, alongside a significant sensitivity to atmospheric transport, is likely responsible for the apparent weakening. Our results, therefore, suggest that spring temperature remains as an important control of northern high‐latitude CO2 uptake

Increasing impact of warm droughts on northern ecosystem productivity over recent decades

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: The data to reproduce and further interpret the main results presented are publicly available at figshare. The TRENDY v.6 datasets applied in this study have been preprocessed by M.O. and are available from the University of Exeter (https://doi.org/10.24378/exe.2883) and on request. The original TRENDY v.6 datasets can be requested from S. Sitch ([email protected]) and P. Friedlingstein ([email protected]). The FLUXCOM dataset is publicly available through the FLUXCOM data portal (https://www.bgc-jena.mpg.de/geodb/projects/FileDetails.php). The LUE datasets are provided by W.K.S. and publicly available at https://wkolby.org/data-code/. The CRUNCEP reanalysis data are available through the Climatic Research Unit data portal (https://crudata.uea.ac.uk/cru/data/ncep/#dataset_access).Code availability: All relevant codes to reproduce the figures presented in this study are publicly available at figshare (https://doi.org/10.6084/m9.figshare.14845005). Further codes and materials are available from D.G. on request.Climate extremes such as droughts and heatwaves have a large impact on terrestrial carbon uptake by reducing gross primary production (GPP). While the evidence for increasing frequency and intensity of climate extremes over the last decades is growing, potential systematic adverse shifts in GPP have not been assessed. Using observationally-constrained and process-based model data, we estimate that particularly northern midlatitude ecosystems experienced a +10.6% increase in negative GPP extremes in the period 2000–2016 compared to 1982–1998. We attribute this increase predominantly to a greater impact of warm droughts, in particular over northern temperate grasslands (+95.0% corresponding mean increase) and croplands (+84.0%), in and after the peak growing season. These results highlight the growing vulnerability of ecosystem productivity to warm droughts, implying increased adverse impacts of these climate extremes on terrestrial carbon sinks as well as a rising pressure on global food security.Swiss National Science Foundation (SNSF)Helmholtz Initiative and Networking FundNewton FundNAS

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation‐based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS‐LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture‐atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long‐term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP

Robust Amazon precipitation projections in climate models that capture realistic land–atmosphere interactions

Land–atmosphere interactions have an important influence on Amazon precipitation (P), but evaluation of these processes in climate models has so far been limited. We analysed relationships between Amazon P and evapotranspiration (ET) in the 5th Coupled Model Intercomparison Project models to evaluate controls on surface moisture fluxes and assess the credibility of regional P projections. We found that only 13 out of 38 models captured an energy limitation on Amazon ET, in agreement with observations, while 20 models instead showed Amazon ET is limited by water availability. Models that misrepresented controls on ET over the historical period projected both large increases and decreases in Amazon P by 2100, likely amplified by unrealistic land–atmosphere interactions. In contrast, large future changes in annual and seasonal-scale Amazon P were suppressed in models that simulated realistic controls on ET, due to modulating land–atmosphere interactions. By discounting projections from models that simulated unrealistic ET controls, our analysis halved uncertainty in basin-wide future P change. The ensemble mean of plausible models showed a robust drying signal over the eastern Amazon and in the dry season, and P increases in the west. Finally, we showed that factors controlling Amazon ET evolve over time in realistic models, reducing climate stability and leaving the region vulnerable to further change

Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models

Water recycled through transpiring forests influences the spatial distribution of precipitation in the Amazon and has been shown to play a role in the initiation of the wet season. However, due to the challenges and costs associated with measuring evapotranspiration (ET) directly and high uncertainty in remote-sensing ET retrievals, the spatial and temporal patterns in Amazon ET remain poorly understood. In this study, we estimated ET over the Amazon and 10 sub-basins using a catchment-balance approach, whereby ET is calculated directly as the balance between precipitation, runoff, and change in groundwater storage. We compared our results with ET from remote-sensing datasets, reanalysis, models from Phase 5 and Phase 6 of the Coupled Model Intercomparison Projects (CMIP5 and CMIP6 respectively), and in situ flux tower measurements to provide a comprehensive overview of current understanding. Catchment-balance analysis revealed a gradient in ET from east to west/southwest across the Amazon Basin, a strong seasonal cycle in basin-mean ET primarily controlled by net incoming radiation, and no trend in ET over the past 2 decades. This approach has a degree of uncertainty, due to errors in each of the terms of the water budget; therefore, we conducted an error analysis to identify the range of likely values. Satellite datasets, reanalysis, and climate models all tended to overestimate the magnitude of ET relative to catchment-balance estimates, underestimate seasonal and interannual variability, and show conflicting positive and negative trends. Only two out of six satellite and model datasets analysed reproduced spatial and seasonal variation in Amazon ET, and captured the same controls on ET as indicated by catchment-balance analysis. CMIP5 and CMIP6 ET was inconsistent with catchment-balance estimates over all scales analysed. Overall, the discrepancies between data products and models revealed by our analysis demonstrate a need for more ground-based ET measurements in the Amazon as well as a need to substantially improve model representation of this fundamental component of the Amazon hydrological cycle

Mapping tropical disturbed forests using multi-decadal 30 m optical satellite imagery

Tropical disturbed forests play an important role in global carbon sequestration due to their rapid post-disturbance biomass accumulation rates. However, the accurate estimation of the carbon sequestration capacity of disturbed forests is still challenging due to large uncertainties in their spatial distribution. Using Google Earth Engine (GEE), we developed a novel approach to map cumulative disturbed forest areas based on the 27-year time-series of Landsat surface reflectance imagery. This approach integrates single date features with temporal characteristics from six time-series trajectories (two Landsat shortwave infrared bands and four vegetation indices) using a random forest machine learning classification algorithm. We demonstrated the feasibility of this method to map disturbed forests in three different forest ecoregions (seasonal, moist and dry forest) in Mato Grosso, Brazil, and found that the overall mapping accuracy was high, ranging from 81.3% for moist forest to 86.1% for seasonal forest. According to our classification, dry forest ecoregion experienced the most severe disturbances with 41% of forests being disturbed by 2010, followed by seasonal forest and moist forest ecoregions. We further separated disturbed forests into degraded old-growth forests and post-deforestation regrowth forests based on an existing post-deforestation land use map (TerraClass) and found that the area of degraded old-growth forests was up to 62% larger than the extent of post-deforestation regrowth forests, with 18% of old-growth forests actually being degraded. Application of this new classification approach to other tropical areas will provide a better constraint on the spatial extent of disturbed forest areas in Tropics and ultimately towards a better understanding of their importance in the global carbon cycle

Impacts of large-scale climatic disturbances on the terrestrial carbon cycle

BACKGROUND: The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO(2 )growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP) and heterotrophic respiration (Rh) during the two largest anomalies in atmospheric CO(2 )increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake) in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release), was caused by the strong El Niño event of 1997/98. RESULTS: We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO(2 )flux. CONCLUSION: Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events

Using Remote Sensing to Map the Risk of Human Monkeypox Virus in the Congo Basin

Although the incidence of human monkeypox has greatly increased in Central Africa over the last decade, resources for surveillance remain extremely limited. We conducted a geospatial analysis using existing data to better inform future surveillance efforts. Using active surveillance data collected between 2005 and 2007, we identified locations in Sankuru district, Democratic Republic of Congo (DRC) where there have been one or more cases of human monkeypox. To assess what taxa constitute the main reservoirs of monkeypox, we tested whether human cases were associated with (i) rope squirrels (Funisciurus sp.), which were implicated in monkeypox outbreaks elsewhere in the DRC in the 1980s, or (ii) terrestrial rodents in the genera Cricetomys and Graphiurus, which are believed to be monkeypox reservoirs in West Africa. Results suggest that the best predictors of human monkeypox cases are proximity to dense forests and associated habitat preferred by rope squirrels. The risk of contracting monkeypox is significantly greater near sites predicted to be habitable for squirrels (OR = 1.32; 95% CI 1.08–1.63). We recommend that semi-deciduous rainforests with oil-palm, the rope squirrel’s main food source, be prioritized for monitoring

Model parameterization to simulate and compare the PAR absorption potential of two competing plant species

Mountain pastures dominated by the pasture grass Setaria sphacelata in the Andes of southern Ecuador are heavily infested by southern bracken (Pteridium arachnoideum), a major problem for pasture management. Field observations suggest that bracken might outcompete the grass due to its competitive strength with regard to the absorption of photosynthetically active radiation (PAR). To understand the PAR absorption potential of both species, the aims of the current paper are to (1) parameterize a radiation scheme of a two-big-leaf model by deriving structural (LAI, leaf angle parameter) and optical (leaf albedo, transmittance) plant traits for average individuals from field surveys, (2) to initialize the properly parameterized radiation scheme with realistic global irradiation conditions of the Rio San Francisco Valley in the Andes of southern Ecuador, and (3) to compare the PAR absorption capabilities of both species under typical local weather conditions. Field data show that bracken reveals a slightly higher average leaf area index (LAI) and more horizontally oriented leaves in comparison to Setaria. Spectrometer measurements reveal that bracken and Setaria are characterized by a similar average leaf absorptance. Simulations with the average diurnal course of incoming solar radiation (1998–2005) and the mean leaf–sun geometry reveal that PAR absorption is fairly equal for both species. However, the comparison of typical clear and overcast days show that two parameters, (1) the relation of incoming diffuse and direct irradiance, and (2) the leaf–sun geometry play a major role for PAR absorption in the two-big-leaf approach: Under cloudy sky conditions (mainly diffuse irradiance), PAR absorption is slightly higher for Setaria while under clear sky conditions (mainly direct irradiance), the average bracken individual is characterized by a higher PAR absorption potential. (∼74 MJ m−2 year−1). The latter situation which occurs if the maximum daily irradiance exceeds 615 W m−2 is mainly due to the nearly orthogonal incidence of the direct solar beam onto the horizontally oriented frond area which implies a high amount of direct PAR absorption during the noon maximum of direct irradiance. Such situations of solar irradiance favoring a higher PAR absorptance of bracken occur in ∼36% of the observation period (1998–2005). By considering the annual course of PAR irradiance in the San Francisco Valley, the clear advantage of bracken on clear days (36% of all days) is completely compensated by the slight but more frequent advantage of Setaria under overcast conditions (64% of all days). This means that neither bracken nor Setaria show a distinct advantage in PAR absorption capability under the current climatic conditions of the study area