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Climate change threatens our ability to grow food for an ever-increasing population. There is a need for high-quality soil moisture predictions in under-monitored regions like Africa. However, it is unclear if soil moisture processes are globally similar enough to allow our models trained on available in situ data to maintain accuracy in unmonitored regions. We present a multitask long short-term memory (LSTM) model that learns simultaneously from global satellite-based data and in situ soil moisture data. This model is evaluated in both random spatial holdout mode and continental holdout mode (trained on some continents, tested on a different one). The model compared favorably to current land surface models, satellite products, and a candidate machine learning model, reaching a global median correlation of 0.792 for the random spatial holdout test. It behaved surprisingly well in Africa and Australia, showing high correlation even when we excluded their sites from the training set, but it performed relatively poorly in Alaska where rapid changes are occurring. In all but one continent (Asia), the multitask model in the worst-case scenario test performed better than the soil moisture active passive (SMAP) 9 km product. Factorial analysis has shown that the LSTM model's accuracy varies with terrain aspect, resulting in lower performance for dry and south-facing slopes or wet and north-facing slopes. This knowledge helps us apply the model while understanding its limitations. This model is being integrated into an operational agricultural assistance application which currently provides information to 13 million African farmers. [ABSTRACT FROM AUTHOR]

Climate change threatens our ability to grow food for a growing population. There are concurrent droughts and floods happening globally, with the greatest impacts felt in Africa. There is a need for high-quality soil moisture predictions in under-monitored regions like Africa. Yet it is unclear if soil moisture processes are globally similar enough to allow our models to maintain accuracy in unmonitored regions. We present a multitask long short-term memory (LSTM) model that learns simultaneously from global satellite-based and in-situ soil moisture data. This model is evaluated in both random spatial holdout mode and continental holdout mode (trained on some continents, tested on a different one). The model compared favorably to current land surface models, satellite products, and a candidate machine learning model, reaching a global median correlation of 0.792 for the random spatial holdout test. It behaved surprisingly well in Africa and Australia, showing high correlation even when we excluded their sites from the training set, but performed relatively poorly in Alaska where rapid changes are occurring. In all but one continent (Asia), the multitask model in the worst-case scenario test performed better than the soil moisture active passive (SMAP) 9-km product. Factorial analysis shows that the LSTM model’s accuracy with representing impacts of terrain aspect, resulting in lower performance for dry and south-facing slopes or wet and north-facing slopes. This knowledge helps us apply the model while understanding its limitations. This model is being integrated into an operational agricultural assistance application which currently provides information to 13 million African farmers. [ABSTRACT FROM AUTHOR]

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010–2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon–climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes. [ABSTRACT FROM AUTHOR]

• Start of snowmelt predominates spring vegetation phenology in alaska. • Snowmelt-induced synergistic changes in soil temperature and moisture drive greenup. • Responses of greenup to snowmelt are associated with vegetation and climate feature. Snow is considered a vital component in the northern climate system, however, our understanding of the impacts of snowmelt on spring phenological shifts is still limited for high-latitude ecosystems. In this study, we analyzed the start of growing season (SOS) and its response to the process of snowmelt over 2000–2019 using multiple ground observations, satellite data products, and climate datasets in Alaska and part of Canada Yukon among five ecoregions. We found that the earlier snowmelt resulting from warming spring dominates the advanced spring vegetation phenology in the region. Spring vegetation greenup follows the start of snowmelt (SOM). During 2000–2019, the SOM and SOS advanced in a similar spatial pattern across the ecoregions, and SOS experienced further advancement than SOM. On average, SOS advanced about 0.49 days per day of SOM advancement. The impacts of snowmelt on vegetation phenology are largely driven by the snowmelt-induced synergistic changes in soil temperature and soil water content. As snowmelt starts, the infiltration of snowmelt water and insulation of the remaining snow cover stimulate the vegetation activities below the snow. The responses of SOS to the snowmelt phenology varied among the different ecoregions are associated with the varied climate backgrounds and vegetation types. Greater SOS and SOM advancements were found in the taiga-tundra ecotone, while lower changes were detected over the tundra. This study suggests that the snow cover and snowmelt phenology should be considered to better understand the vegetation seasonality under climate change in the high latitudes. [ABSTRACT FROM AUTHOR]

Recent warming at high-latitudes has accelerated permafrost thaw in northern peatlands, and thaw can have profound effects on local hydrology and ecosystem carbon balance. To assess the impact of permafrost thaw on soil organic carbon (OC) dynamics, we measured soil hydrologic and thermal dynamics and soil OC stocks across a collapse-scar bog chronosequence in interior Alaska. We observed dramatic changes in the distribution of soil water associated with thawing of ice-rich frozen peat. The impoundment of warm water in collapse-scar bogs initiated talik formation and the lateral expansion of bogs over time. On average, Permafrost Plateaus stored 137 ± 37 kg C m, whereas OC storage in Young Bogs and Old Bogs averaged 84 ± 13 kg C m. Based on our reconstructions, the accumulation of OC in near-surface bog peat continued for nearly 1,000 years following permafrost thaw, at which point accumulation rates slowed. Rapid decomposition of thawed forest peat reduced deep OC stocks by nearly half during the first 100 years following thaw. Using a simple mass-balance model, we show that accumulation rates at the bog surface were not sufficient to balance deep OC losses, resulting in a net loss of OC from the entire peat column. An uncertainty analysis also revealed that the magnitude and timing of soil OC loss from thawed forest peat depends substantially on variation in OC input rates to bog peat and variation in decay constants for shallow and deep OC stocks. These findings suggest that permafrost thaw and the subsequent release of OC from thawed peat will likely reduce the strength of northern permafrost-affected peatlands as a carbon dioxide sink, and consequently, will likely accelerate rates of atmospheric warming. [ABSTRACT FROM AUTHOR]

Climate warming is expected to have a large impact on plant species composition and productivity in northern latitude ecosystems. Warming can affect vegetation communities directly through temperature effects on plant growth and indirectly through alteration of soil nutrient availability. In addition, warming can cause permafrost to thaw and thermokarst (ground subsidence) to develop, which can alter the structure of the ecosystem by altering hydrological patterns within a site. These multiple direct and indirect effects of permafrost thawing are difficult to simulate in experimental approaches that often manipulate only one or two factors. Here, we used a natural gradient approach with three sites to represent stages in the process of permafrost thawing and thermokarst. We found that vascular plant biomass shifted from graminoid-dominated tundra in the least disturbed site to shrub-dominated tundra at the oldest, most subsided site, whereas the intermediate site was co-dominated by both plant functional groups. Vascular plant productivity patterns followed the changes in biomass, whereas nonvascular moss productivity was especially important in the oldest, most subsided site. The coefficient of variation for soil moisture was higher in the oldest, most subsided site suggesting that in addition to more wet microsites, there were other microsites that were drier. Across all sites, graminoids preferred the cold, dry microsites whereas the moss and shrubs were associated with the warm, moist microsites. Total nitrogen contained in green plant biomass differed across sites, suggesting that there were increases in soil nitrogen availability where permafrost had thawed. [ABSTRACT FROM AUTHOR]