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Climate changes during the mid- to late-Holocene, after the last vestiges of glacial ice sheets dwindled, provide important context for climate change today. In the tropical Andes, most of the continuous paleoclimate records covering the late Holocene are derived from the oxygen isotope composition of ice cores, speleothems, and lake carbonates. These archives are powerful recorders of large-scale changes in circulation and monsoon intensity, but they do not necessarily capture local moisture balance, and so reconstructions of local precipitation and aridity remain scarce. Here we present contrasting histories of local effective moisture vs. regional circulation from several new biomarker records preserved in lakes and peat in the Colombian and Peruvian Andes. We focus on the hydrogen isotope composition of long-chain plant waxes, which reflects precipitation δ2H similarly to δ18O from ice cores and speleothems; and the δ13C of waxes and the δ2H of mid-chain waxes, which reflect local water stress and effective moisture. In both the Northern and Southern Hemisphere tropical Andes, fairly gradual δ2H shifts during the late Holocene indicate a progressive intensification of circulation in the South American lowlands. On the other hand, plant wax δ13C and mid-chain δ2H records indicate abrupt transitions into and out of intervals of water stress and aridity – similar to findings from pollen and sediment lithology from elsewhere in the tropical Andes. We draw on climate models and proxy data syntheses to help reconcile these curiously different accounts of effective moisture in the tropical Andes since the mid-Holocene and discuss implications for modern climate research. 

Impacts of a warming climate are amplified in the Arctic. One notorious impact is recent and record-breaking summertime sea-ice loss. Expanding areas of open water and a prolonged ice-free season create opportunity for some industries but challenge indigenous peoples relying on sea ice for transportation and access to food. The observed and projected increase of Arctic maritime activity requires accurate sea-ice forecasts to protect life, environment, and property. Motivated by emerging prediction needs on the operational timescale (≤10 days), this study explores where local indigenous knowledge (LIK) fits into the forecaster toolbox and how it can be woven into useful sea-ice information products. The 2011 spring ice retreat season in the Bering Sea is presented as a forecasting case study. LIK, housed in a database of community-based ice and weather logs, and an ice-ocean forecast model developed by the US Navy are analyzed for their ability to provide information relevant to stakeholder needs. Additionally, metrics for verifying numerical sea-ice forecasts on multiple scales are derived. The model exhibits skill relative to persistence and climatology on the regional scale. At the community scale, we discuss how LIK and new model guidance can enhance public sea-ice information resources. 

Abstract We mapped tidal wetland gross primary production (GPP) with unprecedented detail for multiple wetland types across the continental United States (CONUS) at 16‐day intervals for the years 2000–2019. To accomplish this task, we developed the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field‐based eddy covariance tower data into a single Bayesian framework, and used a super computer network and remote sensing imagery (Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index). We found a strong fit between the BC model and eddy covariance data from 10 different towers (r²= 0.83,p< 0.001, root‐mean‐square error = 1.22 g C/m²/day, average error was 7% with a mean bias of nearly zero). When compared with NASA's MOD17 GPP product, which uses a generalized terrestrial algorithm, the BC model reduced error by approximately half (MOD17 hadr²= 0.45,p< 0.001, root‐mean‐square error of 3.38 g C/m²/day, average error of 15%). The BC model also included mixed pixels in areas not covered by MOD17, which comprised approximately 16.8% of CONUS tidal wetland GPP. Results showed that across CONUS between 2000 and 2019, the average daily GPP per m²was 4.32 ± 2.45 g C/m²/day. The total annual GPP for the CONUS was 39.65 ± 0.89 Tg C/year. GPP for the Gulf Coast was nearly double that of the Atlantic and Pacific Coasts combined. Louisiana alone accounted for 15.78 ± 0.75 Tg C/year, with its Atchafalaya/Vermillion Bay basin at 4.72 ± 0.14 Tg C/year. The BC model provides a robust platform for integrating data from disparate sources and exploring regional trends in GPP across tidal wetlands.