Perceptions of Bark Beetle Landscape Disturbance Effects on Natural Resources and Drinking Water: Assessing Communication and Knowledge Exchange in the Rocky Mountain Region, USA

Widespread changes to forested watersheds affected by the mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic across western North America raised concerns about the effects of this climate-induced disturbance on drinking water and natural resources. Effective communication and knowledge exchange across scientists and stakeholders (i.e., drinking water managers) is essential for constructively responding to such landscape scale disturbances, providing improved adaptive capacity through knowledge sharing. An assessment of stakeholder knowledge levels, information needs, primary concerns, and suggested communication strategies were conducted via an online elicitation survey and World Science Café workshops. Knowledge levels, assessed via a survey of local water managers and experts, were relatively low with approximately half of the respondents reporting little to no knowledge of the effects of mountain pine beetle on drinking water quality and quantity, thereby indicating limited knowledge exchange between scientists and drinking water stakeholders. Increased accessibility and dissemination of research findings pertinent to the mountain pine beetle epidemic’s effects on drinking water quality and quantity is necessary for natural resource management. Recommendations for improved communication among scientists and drinking water stakeholders in particular and forest health in general include dispersal of non-academic research summaries, information exchange through existing media and community resources, demonstration projects, and information clearinghouses. This information provides a better understanding of the challenges, concerns, and first-hand experience of stakeholders of a landscape disturbance issue to apply this knowledge to enhance land management practice and how researchers on this overall project enhanced science communication efforts.

A regional suspended load yield estimation model for ungauged watersheds

Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.

Nitrogen sink in a small forested watershed of subtropical China

Global nitrogen （N） emission and deposition have been increased rapidly due to massive mobilization of N which may have long- reaching impacts on ecosystems. Many agricultural and forest ecosystems have been identified as secondary N sources. In the present study, the input-output budget of inorganic N in a small forested watershed of subtropical China was investigated. Inorganic N wet deposition and discharge by stream water were monitored from March, 2007 to February, 2009. The concentrations and fluxes of inorganic N in wet precipitation and stream water and net retention of N were calculated. Global N input by dry deposition and biological fixation and N output by denitrification for forested watersheds elsewhere were reported as references to evaluate whether the studied forested watershed is a source or a sink for N. The results show that the inorganic N output by the stream water is mainly caused by NO3-N even though the input is dominated by NH4＋-N. The mean flux of inorganic N input by wet precipitation and output by stream water is 1.672 and 0.537 g N/（m2.yr）, respectively, which indicates that most of inorganic N input is retained in the forested watershed. Net retention of inorganic N reaches 1.135 g N/（m2.yr） considering wet precipitation as the main input and stream water as the main output, ff N input by dry deposition and biological fixation and output by denitlification are taken into account, this subtropical forested watershed currently acts as a considerable sink for N, with a net sink ranging from 1.309 to 1.913 g N/（m2-yr） which may enhance carbon sequestration of the terrestrial ecosystem.