Streamflow controls many freshwater and marine processes, including salinity profiles, sediment composition, fluxes of nutrients, and the timing of animal migrations. Watersheds that border the Gulf of Alaska (GOA) comprise over 400,000 km2 of largely pristine freshwater habitats and provide ecosystem services such as reliable fisheries for local and global food production. Yet no comprehensive watershed‐scale description of current temporal and spatial patterns of streamflow exists within the coastal GOA. This is an immediate need because the spatial distribution of future streamflow patterns may shift dramatically due to warming air temperature, increased rainfall, diminishing snowpack, and rapid glacial recession. Our primary goal was to describe variation in streamflow patterns across the coastal GOA using an objective set of descriptors derived from flow predictions at the downstream‐most point within each watershed. We leveraged an existing hydrologic runoff model and Bayesian mixture model to classify 4,140 watersheds into 13 classes based on seven streamflow statistics. Maximum discharge timing (annual phase shift) and magnitude relative to mean discharge (amplitude) were the most influential attributes. Seventy‐six percent of watersheds by number showed patterns consistent with rain or snow as dominant runoff sources, while the remaining watersheds were driven by rain‐snow, glacier, or low‐elevation wetland runoff. Streamflow classes exhibited clear mechanistic links to elevation, ice coverage, and other landscape features. Our classification identifies watersheds that might shift streamflow patterns in the near future and, importantly, will help guide the design of studies that evaluate how hydrologic change will influence coastal GOA ecosystems.
We estimate the ecosystem service value of water supplied by the San Bernardino National Forest in Southern California under climate change projections through the 21st century. We couple water flow projections from a dynamic vegetation model with an economic demand model for residential water originating from the San Bernardino National Forest. Application of the method demonstrates how estimates of consumer welfare changes due to variation in water supply from public lands in Southern California can inform policy and land management decisions. Results suggest variations in welfare changes over time due to alterations in the projected water supply surpluses, shifting demand limited by water supply shortages or surpluses, and price increases. Results are sensitive to future climate projections—in some cases large decreases in welfare due to supply shortages—and to assumptions about the demand model.
The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.
The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.
Although nitrogen deposition and tropospheric ozone have impacted California forests for decades, broad scale studies of these impacts on forest growth and mortality are lacking. Because of the summer-dry climate over most of the state, forest responses to air pollution are expected to differ from more mesic climates. In this study, data from US Forest Service Forest Inventory and Analysis (FIA) permanent (remeasured) plots were combined with modelled atmospheric N and S deposition and an ozone exposure index to evaluate tree growth and mortality responses in California. Seven of 18 species exhibited significantly greater carbon increment (CI) in tree boles as N deposition increased, though the magnitude of the effect was quite small in most California forests. However, increases in CI were substantial in the coastal ecosections of central and northern California where precipitation and fog exposure are greatest. Redwood (Sequoia sempervirens (D. Don) Endl.) trees exhibited the strongest CI response to N deposition. Our model results imply a mean CI increase of 4.2 kg ha−1 yr−1 of C per kg ha−1 yr−1 of N deposition statewide versus 13.6 in the Central and Northern California Coast ecosections, where > 50% of the trees are redwood or tanoak (Lithocarpus densiflorus (Hook. & Arn.) Rehd.). Increased carbon sequestration rates in response to N deposition in these California coastal regions were similar to increases reported for Europe and global estimates. Nitrogen and S deposition significantly increased the odds of top damage and trees with crown damage exhibited higher mortality, although the effect was small. Elevated ozone exposure was associated with significantly larger rates of overall tree growth. However, for ozone-sensitive ponderosa pine at moderate ozone levels (ozone index values of ca. 20–30 ppb) and moderately-elevated N deposition (15–25 kg ha−1 hr−1), CI begins to decline, before increasing at higher pollution levels, presumably because of the fertilizing effect of N deposition; although data are limited for these more polluted conditions. Sulfur deposition in California forests was low, ranging from 0.3 to 3.1 kg ha−1 yr−1, but was associated with positive growth response in seven coniferous species. The combined effect of N and S deposition and ozone exposure statewide is a net increase in bole CI. However, aridity reduces the stimulatory growth effect of N deposition, and alters the threshold, capacity and sometimes the direction (e.g., S deposition) of the CI response to deposition, factors that need to be considered in global change models.