Afshin Pourmokhtarian

Streamflow responses to past and projected future changes in climate at the Hubbard Brook Experimental Forest, New Hampshire, United States

[1] Climate change has the potential to alter streamflow regimes, having ecological, economic, and societal implications. In the northeastern United States, it is unclear how climate change may affect surface water supply, which is of critical importance in this densely populated region. The objective of this study was to evaluate the impact of climate change on the timing and quantity of streamflow at small watersheds at the Hubbard Brook Experimental Forest in New Hampshire. The site is ideal for this analysis because of the availability of long-term hydroclimatological records for analyzing past trends and ample data to parameterize and test hydrological models used to predict future trends. In this study, future streamflow projections were developed with the forest watershed model PnETBGC, driven by climate change scenarios from statistically downscaled outputs of atmospheric-ocean general circulation models. Results indicated that earlier snowmelt and the diminishing snowpack is advancing the timing and reducing the magnitude of peak discharge associated with snowmelt. Past increases in precipitation have caused annual water yield to increase significantly, a trend that is expected to continue under future climate change. Significant declines in evapotranspiration have been observed over the long-term record, although the cause has not been identified. In the future, evapotranspiration is expected to increase in response to a warmer and wetter environment. These increases in evapotranspiration largely offset increases in precipitation, resulting in relatively little change in streamflow. Future work should aim to decrease uncertainty in the climate projections, particularly for precipitation, obtain a better understanding of the effect of CO2 on vegetation, determine if climate-induced changes in tree species composition will influence discharge, and assess the impacts of changing hydrology on downstream water supplies.

The Tao of open science for ecology

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes “open science.” Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life-cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that ...

Modeling potential hydrochemical responses to climate change and increasing CO2at the Hubbard Brook Experimental Forest using a dynamic biogeochemical model (PnET‐BGC)

[1]xa0Dynamic hydrochemical models are useful tools for understanding and predicting the interactive effects of climate change, atmospheric CO2, and atmospheric deposition on the hydrology and water quality of forested watersheds. We used the biogeochemical model, PnET-BGC, to evaluate the effects of potential future changes in temperature, precipitation, solar radiation, and atmospheric CO2on pools, concentrations, and fluxes of major elements at the Hubbard Brook Experimental Forest in New Hampshire, United States. Future climate projections used to run PnET-BGC were generated specifically for the Hubbard Brook Experimental Forest with a statistical technique that downscales climate output (e.g., air temperature, precipitation, solar radiation) from atmosphere-ocean general circulation models (AOGCMs) to a finer temporal and spatial resolution. These climate projections indicate that over the twenty-first century, average air temperature will increase at the site by 1.7°C to 6.5°C with simultaneous increases in annual average precipitation ranging from 4 to 32 cm above the long-term mean (1970–2000). PnET-BGC simulations under future climate change show a shift in hydrology characterized by later snowpack development, earlier spring discharge (snowmelt), greater evapotranspiration, and a slight increase in annual water yield (associated with CO2 effects on vegetation). Model results indicate that under elevated temperature, net soil nitrogen mineralization and nitrification markedly increase, resulting in acidification of soil and stream water, thereby altering the quality of water draining from forested watersheds. Invoking a CO2 fertilization effect on vegetation under climate change substantially mitigates watershed nitrogen loss, highlighting the need for a more thorough understanding of CO2 effects on forest vegetation.

Interactive effects of air pollution and climate change on forest ecosystems in the United States: current understanding and future scenarios

A review of the current status of air pollution and climate change (CC) in the United States from a perspective of their impacts on forest ecosystems is provided. Ambient ozone (O3) and nitrogen (N) deposition have important and widespread ecological impacts in U.S. forests. Effects of sulphurous (S) air pollutants and other trace pollutants have significant ecological importance only at much smaller geographic scales. Complex interactive effects of air pollution and CC for selected future CC scenarios are reviewed. In addition, simulations of past, present, and future hydrologic, nutrient, and growth changes caused by interactive effects of air pollution and CC are described for two U.S. forest ecosystems. Impacts of O3, N deposition, and CC on growth and hydrology of mixed conifer forests in the San Bernardino Mountains in southern California were projected with the DayCent model. Effects of N deposition, CO2 fertilization, N deposition, and CC on northern hardwood forests at the Hubbard Brook Experimental Forest in New Hampshire were simulated with the PnET-BGC model. Projected changes in these forests can influence the provision of ecosystem services such as C sequestration and water supply. The extent of these effects will vary depending on the future intensity and extent of CC, air pollutant emission levels, the distribution of air pollution, and other factors such as drought, pest outbreaks, fire, etc. Our chapter ends with research and management recommendations intended to increase our ability to cope with uncertainties related to the future interactive effects of multiple air pollutants, atmospheric deposition, CC, and other biotic and abiotic stressors.

The effects of climate downscaling technique and observational data set on modeled ecological responses

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change.

Predicting Acidification Recovery at the Hubbard Brook Experimental Forest, New Hampshire: Evaluation of Four Models

The performance and prediction uncertainty (owing to parameter and structural uncertainties) of four dynamic watershed acidification models (MAGIC, PnET-BGC, SAFE, and VSD) were assessed by systematically applying them to data from the Hubbard Brook Experimental Forest (HBEF), New Hampshire, where long-term records of precipitation and stream chemistry were available. In order to facilitate systematic evaluation, Monte Carlo simulation was used to randomly generate common model input data sets (n = 10,000) from parameter distributions; input data were subsequently translated among models to retain consistency. The model simulations were objectively calibrated against observed data (streamwater: 1963-2004, soil: 1983). The ensemble of calibrated models was used to assess future response of soil and stream chemistry to reduced sulfur deposition at the HBEF. Although both hindcast (1850-1962) and forecast (2005-2100) predictions were qualitatively similar across the four models, the temporal pattern of key indicators of acidification recovery (stream acid neutralizing capacity and soil base saturation) differed substantially. The range in predictions resulted from differences in model structure and their associated posterior parameter distributions. These differences can be accommodated by employing multiple models (ensemble analysis) but have implications for individual model applications.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere-ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO2 effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.

Factors influencing critical and target loads for the acidification of lake-watersheds in the Adirondack region of New York

AbstractnCritical loads (CLs) and target loads (TLs) are tools used to guide air emissions control strategies for recovery of forest and aquatic ecosystems impacted by elevated atmospheric deposition. We use the dynamic hydrochemical model-PnET-BGC (photosynthesis evapotranspiration biogeochemical) to evaluate biophysical factors that affect CLs and TLs of acidity for the Constable Pond watershed, as an example of a chronically acidic drainage lake in the Adirondack region of New York, USA. These factors included a range of future scenarios of decreases in atmospheric nitrate, ammonium and sulfate deposition from present to 2200; historical forest harvesting; supply of naturally occurring organic acids; and variations in lake hydraulic residence time. Simulations show that decreases in sulfate deposition were more effective in increasing lake acid neutralizing capacity (ANC) than equivalent decreases in nitrate deposition, 4.6 times greater in 2040–2050 but decreasing to 2 times greater by 2200. Future lake ANC is anticipated to increase to a greater extent when the watershed experiences past forest cutting compared to a scenario without historical land disturbance. Under higher rates of watershed supply of naturally occurring dissolved organic carbon (DOCxa0~1000xa0µmol C/L), ANC is lower than under relatively low DOC supply (~100xa0µmol C/L) due to strongly acidic functional groups associated with dissolved organic matter. Lakes with longer hydrologic residence time exhibit less historical acidification and can achieve a greater ANC from recovery than lakes with shorter hydrologic residence times due to in-lake production of ANC. This study improves understanding of how biogeochemical processes at the landscape level can influence the rate and extent of recovery of lake–watersheds in response to decreases in atmospheric deposition.