Light-stress avoidance mechanisms in a Sphagnum-dominated wet coastal Arctic tundra ecosystem in Alaska

The Arctic experiences a high-radiation environment in the summer with 24-hour daylight for more than two months. Damage to plants and ecosystem metabolism can be muted by overcast conditions common in much of the Arctic. However, with climate change, extreme dry years and clearer skies could lead to the risk of increased photoxidation and photoinhibition in Arctic primary producers. Mosses, which often exceed the NPP of vascular plants in Arctic areas, are often understudied. As a result, the effect of specific environmental factors, including light, on these growth forms is poorly understood. Here, we investigated net ecosystem exchange (NEE) at the ecosystem scale, net Sphagnum CO2 exchange (NSE), and photoinhibition to better understand the impact of light on carbon exchange from a moss-dominated coastal tundra ecosystem during the summer season 2006. Sphagnum photosynthesis showed photoinhibition early in the season coupled with low ecosystem NEE. However, later in the season, Sphagnum maintained a significant CO2 uptake, probably for the development of subsurface moss layers protected from strong radiation. We suggest that the compact canopy structure of Sphagnum reduces light penetration to the subsurface layers of the moss mat and thereby protects the active photosynthetic tissues from damage. This stress avoidance mechanism allowed Sphagnum to constitute a significant percentage (up to 60%) of the ecosystem net daytime CO2 uptake at the end of the growing season despite the high levels of radiation experienced.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Framing an independent,integrated and evidence-based evaluation of the state of Australia's biophysical and human environments

A new approach was developed for Australia's 2011 national State of the Environment (SoE) report to integrate the assessment of biophysical and human elements of the environment. A Common Assessment and Reporting Framework (CARF) guided design and implementation, responding to jurisdictional complexity, outstanding natural diversity and ecosystem values, high levels of cultural and heritage diversity, and a paucity of national-scale data. The CARF provided a transparent response to the need for an independent, robust and evidence-based national SoE report. We conclude that this framework will be effective for subsequent national SoE assessments and other integrated national-scale assessments in data-poor regions.     

Effects of Climate and Land Cover on Hydrology in the Southeastern U.S.: Potential Impacts on Watershed Planning

The hydrologic response to statistically downscaled general circulation model simulations of daily surface climate and land cover through 2099 was assessed for the Apalachicola‐Chattahoochee‐Flint River Basin located in the southeastern United States. Projections of climate, urbanization, vegetation, and surface‐depression storage capacity were used as inputs to the Precipitation‐Runoff Modeling System to simulate projected impacts on hydrologic response. Surface runoff substantially increased when land cover change was applied. However, once the surface depression storage was added to mitigate the land cover change and increases of surface runoff (due to urbanization), the groundwater flow component then increased. For hydrologic studies that include projections of land cover change (urbanization in particular), any analysis of runoff beyond the change in total runoff should include effects of stormwater management practices as these features affect flow timing and magnitude and may be useful in mitigating land cover change impacts on streamflow. Potential changes in water availability and how biota may respond to changes in flow regime in response to climate and land cover change may prove challenging for managers attempting to balance the needs of future development and the environment. However, these models are still useful for assessing the relative impacts of climate and land cover change and for evaluating tradeoffs when managing to mitigate different stressors.     

Resolution and Analysis of Spatial Variations and Patterns in an Urban Lake with Rapid Profiling Instrumentation

Rapid response vertical profiling instrumentation was used to document spatial variability and patterns in a small urban lake, Onondaga Lake, associated with multiple drivers. Paired profiles of temperature, specific conductance (SC), turbidity (T_n), fluorometric chlorophyll a (Chl_f), and nitrate nitrogen (NO₃^?) were collected at >30 fixed locations (a “gridding”) weekly, over the spring to fall interval of several years. These gridding data are analyzed (1) to characterize phytoplankton (Chl_f) patchiness in the lake's upper waters, (2) to establish the representativeness of a single long‐term site for monitoring lake‐wide conditions, and (3) to resolve spatial patterns of multiple tracers imparted by buoyancy effects of inflows. Multiple buoyancy signatures were resolved, including overflows from less dense inflows, and interflows to metalimnetic depths and underflows to the bottom from the plunging of more dense inputs. Three different metrics had utility as tracers in depicting the buoyancy signatures as follows: (1) SC, for salinity‐enriched tributaries and the more dilute river that receives the lake's outflow, (2) T_n, for the tributaries during runoff events, and (3) NO₃^?, for the effluent of a domestic waste treatment facility and from the addition of NO₃^? solution to control methyl mercury. The plunging inflow phenomenon, which frequently prevailed, has important management implications.     

Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 2. Criteria Derivation

Nitrogen and phosphorus criteria were developed for 233 km of the Yellowstone River, one of the first cases where a mechanistic model has been used to derive large river numeric nutrient criteria. A water quality model and a companion model which simulates lateral algal biomass across transects were used to simulate effects of increasing nutrients on five variables (dissolved oxygen, total organic carbon, total dissolved gas, pH, and benthic algal biomass in depths ≤1 m). Incremental increases in nutrients were evaluated relative to their impact on predefined thresholds for each variable; the first variable to exceed a threshold set the nutrient criteria. Simulations were made at a low flow, the 14Q5 (lowest average 14 consecutive day flow, July‐September, recurring one in five years), which was derived using benthic algae growth curves and EPA guidance on excursion frequency. An extant climate dataset with an annual recurrence was used, and tributary water quality and flows were coincident with the river's 10 lowest flow years. The river had different sensitivities to nutrients longitudinally, pH being the most sensitive variable in the upstream reach and algal biomass in the lower. Model‐based criteria for the Yellowstone River are as follows: between the Bighorn and Powder river confluences, 55 μg TP/l and 655 μg TN/l; from the Powder River confluence to Montana state line, 95 μg TP/l and 815 μg TN/l. Pros and cons of using steady‐state models to derive river nutrient criteria are discussed.