Warmer temperatures associated with climate change have affected the phenology of most plants, but limited information exists for the American cranberry (Vaccinium macrocarpon Ait.), an important specialty crop. We examined long-term spatiotemporal trends in spring development of cranberry buds using field observations of cranberry bud stages over a 65-yr period, spanning from 1958–2022. A growing degree day (GDD) model was further used to interpret the observed trends in bud development over the study period. To assess spatial variability in cranberry bud development, the GDDs were computed using gridded weather data for four counties of Massachusetts, representing 85

AbstractExtreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968–2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek.

Compared to conventional crops, less is known about how genetic and environmental variability affect the yield and quality of specialty crops like cranberry (Vaccinium macrocarpon Ait.). Herein, we performed a multifaceted analysis of six commercial cranberry beds planted to the Stevens cultivar. The six beds included three with above-average multiyear yields and three that were lower than average. We considered genotype, edaphic factors, and plant nutrient content as driving variables of yield and fruit quality. We found that genetic purity within beds raised the odds of obtaining above-average yields over an 8-year period. The highest levels of genetic contamination (38%-75%) were found at the low-yield beds, where significant differences in yield and fruit quality were observed between genotypes, within beds. Across all beds, focusing only on plots genetically confirmed to be Stevens cultivar, we also found that plot-scale yield in 2020 was significantly higher for two of three high-yield beds, suggesting other factors besides genetic contamination influenced differences in bed-scale yield. A factor analysis of mixed data that jointly included genotype, edaphic variables, and plant tissue nutrient content revealed complex relations among these variables that were tied to grouping plots based on long-term yield. Findings highlight the need for further research into the complex genetic and environmental factors that control cranberry yield and fruit quality.

Peatlands have sequestered atmospheric carbon dioxide (CO2) for millennia and can also act as significant sources of atmospheric methane (CH4). Hydrological processes that control water table dynamics, and climatic conditions such as air temperature, play important roles in mediating peatland-atmosphere exchange of these greenhouse gases. These controls are likely to be impacted by climate change, particularly for those peatlands found in cold environments, including mountain regions. In this study, we developed empirical models to simulate hydrological dynamics and ecosystem-atmosphere C exchange in a mountain peatland under three climate scenarios (2012 air temperatures, +2 degrees C and +4 degrees C). Observed water table dynamics and air temperature were used to model ecosystem-atmosphere C exchange during the 2012 growing season. Modelled snowmelt dynamics were used to predict water table position at the beginning of the growing season for warming scenarios, and the subsequent water table dynamics and increased air temperature were used to drive the same C exchange models during the growing seasons. Increased air temperatures led to earlier snowmelt and water table decline, causing water tables to drop by 10 and 19 cm for the +2 and +4 degrees C scenarios, respectively. This led to roughly a two-fold decrease in growing season net ecosystem production (NEP) in both warming scenarios, as a result of increased ecosystem respiration relative to gross primary production. Methane efflux was positively correlated with NEP and therefore decreased under the warming scenarios, albeit to a lesser degree. These results indicate that reductions in NEP and CH4 efflux are possible in low-elevation mountain peatlands that are dependent on snowpack-derived hydrologic inputs. These ecosystems are found at elevations where future winter precipitation will increasingly fall as rain rather than snow and melting of snowpack will occur earlier under warmer conditions.

The advent of in situ optical sensors that can collect sub-daily measurements of nutrients and turbidity in flowing water bodies has yielded comparatively much larger water quality data sets than were previously available. With these newly available data sets, there has been increased interest in studying event-based concentration-discharge (c-Q) relationships to infer the sources and pathways of various watershed constituents during storms. With water quality data sets increasingly growing in size and scope, the need to automate the processing and analyses of such data has become apparent. However, consensus on storm event delineation methods as they pertain to c-Q analysis is currently lacking, and methodological details, including parameter values, are sometimes unreported in the literature. Here, we present an open-source workflow using the programming language R that automates the processing of sub-daily c-Q data to analyze event-based hysteresis patterns. Briefly, the workflow accepts a time series of concentration and discharge data, extracts stormflow from streamflow, delineates storm events and then evaluates c-Q relationships using widely applied metrics like the hysteresis index (HI) and the flushing index (FI). We applied the workflow to three watersheds in the mid-Atlantic United States, including a 0.4-km(2) agricultural watershed, a 150-km(2) urbanizing watershed and a 29 940-km(2) mixed land use river basin. Sub-daily sensor-based nutrient concentrations and discharge data were collected in each watershed. Using the small agricultural watershed as an example, we demonstrate the step-by-step application of the workflow. We then present results from the larger watersheds as a means for comparison and to illustrate the flexibility of the code. We believe that this rapid approach to event-based c-Q analysis will allow scientists and practitioners more time to focus on interpreting results, and promote greater scientific reproducibility. Likewise, we conclude this Scientific Briefing with suggested future improvements to the workflow to increase the automation of data analyses and reproducibility.

Accurate and reliable forecasts of quickflow, including interflow and overland flow, are essential for predicting rainfall-runoff events that can wash off recently applied agricultural nutrients. In this study, we examined whether a gridded version of the Sacramento Soil Moisture Accounting model with Heat Transfer (SAC-HT) could simulate and forecast quickflow in two agricultural watersheds in east-central Pennsylvania. Specifically, we used the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) software, which incorporates SAC-HT, to conduct a 15-yr (2003-17) simulation of quickflow in the 420-km(2) Mahantango Creek watershed and in WE-38, a 7.3-km(2) headwater interior basin. We directly calibrated HL-RDHM using hydrologic observations at the Mahantango Creek outlet, while all grid cells within Mahantango Creek, including WE-38, were calibrated indirectly using scalar multipliers derived from the basin outlet calibration. Using the calibrated model, we then assessed the quality of short-range (24-72 h) deterministic forecasts of daily quickflow in both watersheds over a 2-yr period (July 2017-October 2019). At the basin outlet, HL-RDHM quickflow simulations showed low biases (PBIAS = 10.5%) and strong agreement (KGE '' = 0.81) with observations. At the headwater scale, HL-RDHM overestimated quickflow (PBIAS = 69.0%) to a greater degree, but quickflow simulations remained satisfactory (KGE '' = 0.65). When applied to quickflow forecasting, HL-RDHM produced skillful forecasts (>90% of Peirce and Gerrity skill scores above 0.5) at all lead times and significantly outperformed persistence forecasts, although skill gains in Mahantango Creek were slightly lower. Accordingly, short-range quickflow forecasts by HL-RDHM show promise for informing operational decision-making in agriculture. Significance StatementDaily runoff forecasts can alert farmers to rainfall-runoff events that have the potential to wash off recently applied fertilizers and manures. To gauge whether daily runoff forecasts are accurate and reliable, we used runoff monitoring data from a large agricultural watershed and one of its headwater tributaries to evaluate the quality of short-term runoff forecasts (1-3 days ahead) that were generated by a National Weather Service watershed model. Results showed that the accuracy and reliability of daily runoff forecasts generally improved in both watersheds as lead times increased from 1 to 3 days. Study findings highlight the potential for National Weather Service models to provide useful short-term runoff forecasts that can inform operational decision-making in agriculture.

Tracking changes in the quantity and variability of soil organic carbon (SOC) stocks associated with different land uses over time is a critical step in understanding decadal-scale impacts of soils on climate change, and can be an important reality check for more complex modeling efforts. In this study, we used a Bayesian statistical framework to quantify and compare SOC stocks among common southern New England land use types (sod farms, silage corn, forest, and turfgrass), including sod fields in continuous production for different periods of time (approximately 10, 20, and 30 years). Further, we modeled the export of SOC associated with sod har-vesting, propagating uncertainty from observations to export estimates. Despite unsustainable annual rates of soil removal (74 to 114 Mg ha-1), SOC stocks for sod fields in production for different time periods were not credibly lower than those of the other land uses examined. Mean exported SOC from sod harvest ranged from 1.67 to 3.23 Mg ha-1, which was enough to entirely deplete the 0-30 cm SOC stock in approximately 30 years. These results suggest that organic C inputs to the upper 30 cm of sod farm soils, from subsoil incorporation during post-harvest tillage and belowground net primary production, may have been maintaining SOC by offsetting loses over several decades. This is unlikely to continue, however, if the eolian mantle that characterizes these soils is depleted due to the cumulative impact of sod harvest on soil removal.

Hydrological dynamics act as a primary control on ecosystem function in mountain peatlands, serving as an important regulator of carbon fluxes. In western North America, mountain peatlands exist in different hydro geological settings, across a range climatic conditions, and vary in floristic composition. The sustainability of these ecosystems, particularly those at the low end of their known elevation range, is susceptible to a changing climate via changes in the water cycle. We conducted a hydrological investigation of two mountain peatlands, with differing vegetation, hydrogeological setting (sloping vs basin), and climate (strong vs weak monsoon influence). Growing season saturated zone water budgets were modeled on a daily basis, and subsurface flow characterizations were performed during multiple field campaigns at each site. The sloping peatland expectedly showed a strong lateral groundwater potential gradient throughout the growing season. Alternatively, the basin peatland had low lateral gradients but more pronounced vertical gradients. A zero-flux plane was apparent at a depth of approximately 50 cm below the peat surface at the basin peatland; shallow groundwater above this depth moved upward towards the surface via evapotranspiration. The differences in groundwater flow dynamics between the two sites also influenced water budgets. Higher groundwater inflow at the sloping peatland offset higher rates of evapotranspiration losses from the saturated zone, which were apparently driven by differences in vegetative cover. This research revealed that although sloping peatlands cover relatively small portions of mountain watersheds, they provide unique settings where vegetation directly utilizes groundwater for transpiration, which were several-fold higher than typically reported for surrounding uplands.

Mountain pine beetle outbreaks in western North America have led to extensive forest mortality, justifiably generating interest in improving our understanding of how this type of ecological disturbance affects hydrological cycles. While observational studies and simulations have been used to elucidate the effects of mountain beetle mortality on hydrological fluxes, an ecologically mechanistic model of forest evapotranspiration (ET) evaluated against field data has yet to be developed. In this work, we use the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to incorporate the ecohydrological impacts of mountain pine beetle disturbance on ET for a lodgepole pine‐dominated forest equipped with an eddy covariance tower. An existing degree‐day model was incorporated that predicted the life cycle of mountain pine beetles, along with an empirically derived submodel that allowed sap flux to decline as a function of temperature‐dependent blue stain fungal growth. The eddy covariance footprint was divided into multiple cohorts for multiple growing seasons, including representations of recently attacked trees and the compensatory effects of regenerating understory, using two different spatial scaling methods. Our results showed that using a multiple cohort approach matched eddy covariance‐measured ecosystem‐scale ET fluxes well, and showed improved performance compared to model simulations assuming a binary framework of only areas of live and dead overstory. Cumulative growing season ecosystem‐scale ET fluxes were 8 – 29% greater using the multicohort approach during years in which beetle attacks occurred, highlighting the importance of including compensatory ecological mechanism in ET models.

Mountain fens found in western North America have sequestered atmospheric carbon dioxide (CO2) for millennia, provide important habitat for wildlife, and serve as refugia for regionally-rare plant species typically found in boreal regions. It is unclear how Rocky Mountain fens are responding to a changing climate. It is possible that fens found at lower elevations may be particularly susceptible to changes because hydrological cycles that control water tables are likely to vary the most. In this study, we fit models of growing season ecosystem-atmosphere CO2 exchange to field-measured data among eight fen plant communities at four mountain fens along a climatic gradient in the Rocky Mountains of Colorado and Wyoming. Differences in growing season net ecosystem production (NEP) among study sites were not well correlated with monsoon precipitation, despite a twofold increase in summer rainfall between two study regions. Our results show that NEP was higher for fens located at high elevations compared to those found at lower elevations, with growing season estimates ranging from −342 to 256 g CO2-C m−2. This was reflected in the negative correlation of growing season NEP with air temperature, and positive correlation with water table position, as the high elevation sites had the lowest air temperatures and highest water tables due to greater snowpack and later onset of melt. Our results suggest that sustainability of mountain fens occurring at the lower end of the known elevation range may be particularly susceptible to a changing climate, as these peatlands already experience lower snowpack, earlier snow melt, and warmer growing season air temperatures, which are all likely to be exacerbated under a future climate.

Commercial sod farms occupy about 1.62 × 10 3 km 2 of the landscape of the United States. Land managers generally consider sod farms on an equal footing with other, sustainable agricultural land uses. We measured soil losses associated with sod harvesting in farms in the northeastern United States. Sod harvest resulted in soil losses ranging from 74 to 114 Mg ha −1 yr −1 , considerably higher than the tolerable soil loss of 6.7 Mg ha −1 yr −1 Soil losses were proportional to time under sod production, with soil removal rates of 0.833 cm yr −1 We estimate that sod harvesting in the United States results in the net, permanent loss of 12.0 to 18.7 Tg of agriculturally productive soil from sod farms—and associated ecosystem services—every year. The soil losses reported here have important implications in terms of land use planning, transactions involving the purchase of development rights, and tax deductions for