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The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes air temperature, soil temperature at 5 cm, and soil volumetric water content at 5 cm, and soil CO2 flux at the time of sampling, as well as gap-filled soil CO2 fluxes using non-linear least squares regression. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH. 

The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes data from snow depth sensors. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH. 

Globally, winter temperatures are rising, and snowpack is shrinking or disappearing entirely. Despite previous research and published literature reviews, it remains unknown whether biomes across the globe will cross important thresholds in winter temperature and precipitation that will lead to significant ecological changes. Here, we combine the widely used Köppen–Geiger climate classification system with worst-case-scenario projected changes in global monthly temperature and precipitation to illustrate how multiple climatic zones across Earth may experience shifting winter conditions by the end of this century. We then examine how these shifts may affect ecosystems within corresponding biomes. Our analysis demonstrates potential widespread losses of extreme cold (<−20°C) in Arctic, boreal, and cool temperate regions. We also show the possible disappearance of freezing temperatures (<0°C) and large decreases in snowfall in warm temperate and dryland areas. We identify important and potentially irreversible ecological changes associated with crossing these winter climate thresholds. 

The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes data from the air temperature, soil temperature, soil volumetric water content, and electrical conductivity sensors. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH. 

Climate zones play a significant role in shaping the forest ecosystems located within them by influencing multiple ecological processes, including growth, disturbances, and species interactions. Therefore, delineation of current and future climate zones is essential to establish a framework for understanding and predicting shifts in forest ecosystems. In this study, we developed and applied an efficient approach to delineate regional climate zones in the northeastern United States and maritime Canada, aiming to characterize potential shifts in climate zones and discuss associated changes in forest ecosystems. The approach comprised five steps: climate data dimensionality reduction, sampling scenario design, cluster generation, climate zone delineation, and zone shift prediction. The climate zones in the study area were delineated into four different orders, with increasing subzone resolutions of 3, 9, 15, and 21. Furthermore, projected climate normals under Shared Socioeconomic Pathways 4.5 and 8.5 scenarios were used to predict the shifts in climate zones until 2100. Our findings indicate that climate zones characterized by higher temperatures and lower precipitation are expected to become more prevalent, potentially becoming the dominant climate condition across the entire region. These changes are likely to alter regional forest composition, structure, and productivity. In short, such shifts in climate underscore the significant impact of environmental change on forest ecosystem dynamics and carbon sequestration potential. 

Climate change is reducing snowpack across temperate regions with negative consequences for human and natural systems. Because forest canopies create microclimates that preserve snowpack, managing forests to support snow refugia—defined here as areas that remain relatively buffered from contemporary climate change over time that sustain snow quality, quantity, and/or timing appropriate to the landscape—could reduce climate change impacts on snow cover, sustaining the benefits of snow. We review the current understanding of how forest canopies affect snow, finding that while closed‐conifer forests and snow interactions have been extensively studied in western North America, there are knowledge gaps for deciduous and mixed forests with dormant season leaf loss. We propose that there is an optimal, intermediate zone along a gradient of dormant season canopy cover (DSCC; the proportion of the ground area covered by the canopy during the dormant season), where peak snowpack depth and the potential for snow refugia will be greatest because the canopy‐mediated effects of snowpack sheltering (which can preserve snowpack) outweigh those of snowfall interception (which can limit snowpack). As an initial test of our hypothesis, we leveraged snowpack measurements in the northeastern United States spanning the DSCC gradient (low, <25% DSCC; medium, 25%–50% DSCC; and high, >50% DSCC), including from 2 sites in Old Town, Maine; 12 sites in Acadia National Park, Maine; and 30 sites in the northern White Mountains of New Hampshire. Medium DSCC forests (typically mature mixed coniferous–deciduous forests) exhibited the deepest peak snowpacks, likely due to reduced snowfall interception compared to high DSCC forests and reduced snowpack loss compared to low DSCC forests. Many snow accumulation or snowpack studies focus on the contrast between coniferous and open sites, but our results indicate a need for enhanced focus on mixed canopy sites that could serve as snow refugia. Measurements of snowpack depth and timing across a wider range of forest canopies would advance understanding of canopy–snow interactions, expand the monitoring of changing winters, and support management of forests and snow‐dependent species in the face of climate change. 

Winters in northeastern North America have warmed faster than summers, with impacts on ecosystems and society. Global climate models (GCMs) indicate that winters will continue to warm and lose snow in the future, but uncertainty remains regarding the magnitude of warming. Here, we project future trends in winter indicators under lower and higher climate-warming scenarios based on emission levels across northeastern North America at a fine spatial scale (1/16°) relevant to climate-related decision making. Under both climate scenarios, winters continue to warm with coincident increases in days above freezing, decreases in days with snow cover, and fewer nights below freezing. Deep snowpacks become increasingly short-lived, decreasing from a historical baseline of 2 months of subnivium habitat to <1 month under the warmer, higher-emissions climate scenario. Warmer winter temperatures allow invasive pests such as Adelges tsugae (Hemlock Woolly Adelgid) and Dendroctonus frontalis (Southern Pine Beetle) to expand their range northward due to reduced overwinter mortality. The higher elevations remain more resilient to winter warming compared to more southerly and coastal regions. Decreases in natural snowpack and warmer temperatures point toward a need for adaptation and mitigation in the multi-million-dollar winter-recreation and forest-management economies.