Assessing watershed-scale impacts of best management practices and elevated atmospheric carbon dioxide concentrations on water yield.

Changes in water yield are influenced by many intersecting biophysical elements, including climate, on-land best management practices, and landcover. Large-scale reductions in water yield may present a significant threat to water supplies globally. Many of these intersecting factors are intercorrelated and confounded, making it challenging to separate the factors' individual contributions to shaping local streamflow dynamics. Comprehensive hydrological models constructed based on a well-established understanding of biophysical processes are often employed to address these matters. However, these models rarely incorporate all relevant factors influencing local hydrological processes, due to the reliance of these models on the latest, albeit limited, state-of-the-art research. For instance, complexities inherent in watershed hydrology, which involve multilayered interactions among potentially many biophysical factors, leave the direct analysis of subtle impacts on water yields measured in-situ largely intractable. Therefore, we propose an innovative approach to assess impacts of elevated atmospheric CO2 concentrations and flow diversion terraces (FDTs) on stream discharge rates at the watershed scale. Initially, we use a comprehensive hydrological model to account for the impacts of major climatic and landuse/landcover factors on changes in field-acquired measurements of water yield. Next, we employ conventional and advanced statistical methods to decompose the residuals of model predictions to facilitate the identification of subtle influences promoted by increases in atmospheric CO2 concentrations and the application of FDTs in an agriculture-dominated watershed. Through this innovative approach, we find that FDTs contributed to a watershed-wide, net water-yield reduction of 188.0 mm (or 28.9 %) from 1992 to 2014. Ongoing increases in ambient CO2 concentrations, which are responsible for an overall reduction in a watershed-level assessment of stomatal conductance, have led to a minor increase in stream discharge rates during the same 23-year period, i.e., 0.45 mm of water yield per year, or 1.6 % overall. Streamflow reductions explicitly caused by regional warming in the area alone, on account of increased evapotranspiration, may be overestimated due to the opposing, synergistic effects on water yield associated with CO2-enrichment of the lower atmosphere and the annual application of FDTs.

Using the soil and water assessment tool to estimate achievable water quality targets through implementation of beneficial management practices in an agricultural watershed.

Runoff from crop production in agricultural watersheds can cause widespread soil loss and degradation of surface water quality. Beneficial management practices (BMPs) for soil conservation are often implemented as remedial measures because BMPs can reduce soil erosion and improve water quality. However, the efficacy of BMPs may be unknown because it can be affected by many factors, such as farming practices, land-use, soil type, topography, and climatic conditions. As such, it is difficult to estimate the impacts of BMPs on water quality through field experiments alone. In this research, the Soil and Water Assessment Tool was used to estimate achievable performance targets of water quality indicators (sediment and soluble P loadings) after implementation of combinations of selected BMPs in the Black Brook Watershed in northwestern New Brunswick, Canada. Four commonly used BMPs (flow diversion terraces [FDTs], fertilizer reductions, tillage methods, and crop rotations), were considered individually and in different combinations. At the watershed level, the best achievable sediment loading was 1.9 t ha(-1) yr(-1) (89% reduction compared with default scenario), with a BMP combination of crop rotation, FDT, and no-till. The best achievable soluble P loading was 0.5 kg ha(-1) yr(-1) (62% reduction), with a BMP combination of crop rotation and FDT and fertilizer reduction. Targets estimated through nonpoint source water quality modeling can be used to evaluate BMP implementation initiatives and provide milestones for the rehabilitation of streams and rivers in agricultural regions.

Photosynthetic parameters and stomatal conductance in attached and detached balsam fir foliage.

Leaf level gas-exchange measurements can be made on detached foliage to address the challenge of access to the crown of tall trees. However, detachment may impact leaf gas exchange. This necessitates the study of gas-exchange characteristics of foliage on detached branches to assess the feasibility of using detached branches for gas-exchange analysis. We compared photosynthetic parameters and stomatal conductance in foliage of attached and detached branches of balsam fir [Abies balsamea (L.) Mill.] during the growing season. Data were analyzed using a linear mixed-effect model, with fixed and random effects (branch status and measurement month, and tree number, respectively). Branch detachment had no significant effects on: (i) photosynthesis at the current ambient CO2 concentration (400 µmol mol-1, A 400); (ii) maximum rates of Ribulose-1,5-bisphosphate (RuBP) carboxylation (V cmax) and regeneration (J max); (iii) the ratio of J max to V cmax (i.e., J max:V cmax), and (iv) stomatal conductance (g s) during the study period (p = 0.120-0.335). There was a strong seasonal effect on all gas-exchange variables (p ≤ 0.001-0.015). Gas-exchange measurements made on detached foliage during the warm summer months should be performed with care. Reliable gas-exchange measurements can be obtained using balsam fir foliage on detached branches 50-80 cm in length, in cooler growing-season months, up to 30 min after detachment.

Conditional inference trees in the assessment of tree mortality rates in the transitional mixed forests of Atlantic Canada.

Long-term predictions of forest dynamics, including forecasts of tree growth and mortality, are central to sustainable forest-management planning. Although often difficult to evaluate, tree mortality rates under different abiotic and biotic conditions are vital in defining the long-term dynamics of forest ecosystems. In this study, we have modeled tree mortality rates using conditional inference trees (CTREE) and multi-year permanent sample plot data sourced from an inventory with coverage of New Brunswick (NB), Canada. The final CTREE mortality model was based on four tree- and three stand-level terms together with two climatic terms. The correlation coefficient (R2) between observed and predicted mortality rates was 0.67. High cumulative annual growing degree-days (GDD) was found to lead to increased mortality in 18 tree species, including Betula papyrifera, Picea mariana, Acer saccharum, and Larix laricina. In another ten species, including Abies balsamea, Tsuga canadensis, Fraxinus americana, and Fagus grandifolia, mortality rates tended to be higher in areas with high incident solar radiation. High amounts of precipitation in NB's humid maritime climate were also found to contribute to heightened tree mortality. The relationship between high GDD, solar radiation, and high mortality rates was particularly strong when precipitation was also low. This would suggest that although excessive soil water can contribute to heightened tree mortality by reducing the supply of air to the roots, occasional drought in NB can also contribute to increased mortality events. These results would have significant implications when considered alongside regional climate projections which generally entail both components of warming and increased precipitation.

A watershed-scale assessment of cost-effectiveness of sediment abatement with flow diversion terraces.

Soil conservation beneficial management practices (BMPs) are effective at controlling soil loss from farmlands and minimizing water pollution in agricultural watersheds. However, costs associated with implementing and maintaining these practices are high and often deter farmers from using them. Consequently, it is necessary to conduct cost-benefit analysis of BMP implementation to assist decision-makers with planning to provide the greatest level of environmental protection with limited resources and funding. The Soil and Water Assessment Tool (SWAT) was used to evaluate the efficacy of flow diversion terraces (FDT) in abating sediment yield at the outlet of Black Brook Watershed (BBW), northwestern New Brunswick. Different FDT-implementation scenarios were expressed as the ratio of land area protected by FDT to the total cultivated area. From this analysis, we found that average annual sediment yield decreased exponentially with increased FDT protection. When the proportion of FDT-protected areas was low, sediment reductions caused by FDT increased sharply with increasing use of FDT. Similarly, marginal sediment yield abatement costs (dollar per tonne of sediment reduction) increased exponentially with increasing proportion of FDT-protected area. The results indicated that increasing land protection with FDT from 6 to 50% would result in a reduction of about 2.1 tonne ha(-1) yr(-1) and costs of sediment reduction increased from $7 to $12 per tonne. Increasing FDT-protected cropland from 50 to 100%, a reduction of about 0.9 tonne of sediment ha(-1) yr(-1) would occur and the costs would increase from $12 to $53 per tonne of sediment yield reduction.

Characterizing the impacts of land use on nitrate load and water yield in an agricultural watershed in Atlantic Canada.

Excessive nitrate loading from agricultural non-point source is threatening the health of receiving water bodies at the global scale. Quantifying the drivers/sources of water and nitrate flux in watersheds and relating them to spatial and temporal land uses is essential for developing effective mitigation strategies. This study investigated the impact of land use on water yield and nitrate loading to surface water in a typical agricultural watershed in Prince Edward Island (PEI), Canada. We used historical streamflow and water quality records to calibrate the comprehensive hydrological model Soil and Water Assessment Tool (SWAT), which was setup with detailed annual land use records. The SWAT model performed well in predicting both daily streamflow and nitrate load. Land use demonstrated little impact on water yield but affected nitrate load significantly. Annual nitrate load ranged from 5.6 to 44.4 kg N ha-1 yr-1 for forest and soybean, respectively. Potato rotated land contributed 84.5% of annual nitrate load to the watershed. Source of water yield demonstrated high variability between the growing season and non-growing season. About 90% of water yield was contributed by groundwater during growing season, while runoff contributed over 60% of water yield during the non-growing season. Groundwater was the dominant source of nitrate loading for both seasons. The watershed estuary faced the highest threats from subbasins in the south western area due to the high nitrate load and proximity to the watershed outlet. Results by the machine learning algorithm random Forest analysis indicated that the climatic variables of temperature and precipitation were the top two factors affecting water yield, with a combined relative importance of 61%. Land use was the dominant factor affecting nitrate load, the relative importance of land use alone was ~50%. The results of this study provided critical insights for watershed management in Atlantic Canada.

Evaluation of the suitability of six drought indices in naturally growing, transitional vegetation zones in Inner Mongolia (China).

Naturally growing vegetation often suffers from the effects of drought. There exists a vast number of drought indices (DI's) to assess the impact of drought on the growth of crops and naturally occurring vegetation. However, assessing the fitness of these indices for large areas with variable vegetation cover is often problematic because of the absence of adequate spatial information. In this study, we compared six DI's to NDVI (the normalized difference vegetation index), a common indicator of vegetation occurrence and health based on satellite-acquired reflectance data. The study area covers an aridity gradient from forests to deserts along a 2,400-km-long section across the Inner Mongolia Autonomous Region of China. On an annual timescale, standardized precipitation index (SPI) was the most appropriate in assessing drought in steppes and deserts. On a seasonal timescale, the self-calibrated Palmer drought severity index (scPDSI) displayed the greatest sensitivity during the summer, but not during the other seasons. On a monthly timescale, scPDSI demonstrated the greatest sensitivity to the various vegetation zones (i.e., forests, steppes, and deserts) in June and July. Further analysis indicated that summer drought had a lag-effect on vegetation growth, which varied from one to six months according to the specific vegetation cover. The mixed response of DI's to NDVI and the lag-effect in transitional vegetation on annual, seasonal, and monthly timescales were ascribed to differences in DI definition and the dominant plant species within the transitional cover. The current study has the potential to inform the drafting of selection criteria of DI's for the study of drought-related impact on naturally growing vegetation at timescales from month to year.

Validating Evapotranspiraiton Equations Using Bowen Ratio in New Brunswick, Maritime, Canada.

Three methods including the Penman-Monteith (PM), Priestley-Taylor (PT), and 1963 Penman equation (PE) for calculating daily reference evapotranspiration (ETo) were evaluated in the Maritime region of Canada with the data collected from 2004 to 2007. An automatically operated meteorological station located on the Potato Research Centre, Agriculture and Agri-Food Canada, Fredericton, New Brunswick, Canada, was used to collect required meteorological data for evapotranspiration modeling. A Bowen Ratio system (BR) was setup near the Environment Canada grade one weather station to provide evapotranspiration observations for the validation research of reference evapotranspiration models. The results showed that the prediction from each of the tested models had a certain degree of offset in comparison with the observations obtained by the BR method. All of the tested models slightly overestimated evapotranspiration compared to the BR system by 5-14%, depending on the method. However, the PM generated a better fit to the pooled dataset while the PT produced the best prediction for the 2007 validation dataset. The PM generated the best estimation of evapotranspiration for year 2004 during a inter-annual comparison. The BR revealed that the average daytime ET for the site was around 2.5 mm day-1(±0.1) averaged for Julian day 157-276 in 2004 to 2006 and possible condensation was 0.16 mm day-1 for the same period. Crop coefficient (Kc) varied with different models, for example, 0.42 for the PM, 0.44 for the PT, and 0.67 for the PE with a slight yearly variation. With this set of Kc values, a validation with additional dataset collected in 2007 indicated that all three equations achieved a good fit with observations using the above Kc values. The PT performed slightly better than the other two models. A single factor analysis did not show any statistically significant difference between predicted and measured ET. With a consideration of simplicity and application for scaling up to landscape, this research suggested that the PT is the preferable method for estimating ET values in this region.

A Wetness Index Using Terrain-Corrected Surface Temperature and Normalized Difference Vegetation Index Derived from Standard MODIS Products: An Evaluation of Its Use in a Humid Forest-Dominated Region of Eastern Canada.

In this paper we develop a method to estimate land-surface water content in amostly forest-dominated (humid) and topographically-varied region of eastern Canada. Theapproach is centered on a temperature-vegetation wetness index (TVWI) that uses standard 8-day MODIS-based image composites of land surface temperature (TS) and surface reflectanceas primary input. In an attempt to improve estimates of TVWI in high elevation areas, terrain-induced variations in TS are removed by applying grid, digital elevation model-basedcalculations of vertical atmospheric pressure to calculations of surface potential temperature(θS). Here, θS corrects TS to the temperature value to what it would be at mean sea level (i.e.,~101.3 kPa) in a neutral atmosphere. The vegetation component of the TVWI uses 8-daycomposites of surface reflectance in the calculation of normalized difference vegetation index(NDVI) values. TVWI and corresponding wet and dry edges are based on an interpretation ofscatterplots generated by plotting θS as a function of NDVI. A comparison of spatially-averaged field measurements of volumetric soil water content (VSWC) and TVWI for the 2003-2005 period revealed that variation with time to both was similar in magnitudes. Growing season, point mean measurements of VSWC and TVWI were 31.0% and 28.8% for 2003, 28.6% and 29.4% for 2004, and 40.0% and 38.4% for 2005, respectively. An evaluation of the long-term spatial distribution of land-surface wetness generated with the new θS-NDVI function and a process-based model of soil water content showed a strong relationship (i.e., r² = 95.7%).

Production of high-resolution forest-ecosite maps based on model predictions of soil moisture and nutrient regimes over a large forested area.

Forest ecosite reflects the local site conditions that are meaningful to forest productivity as well as basic ecological functions. Field assessments of vegetation and soil types are often used to identify forest ecosites. However, the production of high-resolution ecosite maps for large areas from interpolating field data is difficult because of high spatial variation and associated costs and time requirements. Indices of soil moisture and nutrient regimes (i.e., SMR and SNR) introduced in this study reflect the combined effects of biogeochemical and topographic factors on forest growth. The objective of this research is to present a method for creating high-resolution forest ecosite maps based on computer-generated predictions of SMR and SNR for an area in Atlantic Canada covering about 4.3 × 106 hectares (ha) of forestland. Field data from 1,507 forest ecosystem classification plots were used to assess the accuracy of the ecosite maps produced. Using model predictions of SMR and SNR alone, ecosite maps were 61 and 59% correct in identifying 10 Acadian- and Maritime-Boreal-region ecosite types, respectively. This method provides an operational framework for the production of high-resolution maps of forest ecosites over large areas without the need for data from expensive, supplementary field surveys.

Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape.

There are a number of overarching questions and debate in the scientific community concerning the importance of biotic interactions in species distribution models at large spatial scales. In this paper, we present a framework for revising the potential distribution of tree species native to the Western Ecoregion of Nova Scotia, Canada, by integrating the long-term effects of interspecific competition into an existing abiotic-factor-based definition of potential species distribution (PSD). The PSD model is developed by combining spatially explicit data of individualistic species' response to normalized incident photosynthetically active radiation, soil water content, and growing degree days. A revised PSD model adds biomass output simulated over a 100-year timeframe with a robust forest gap model and scaled up to the landscape using a forestland classification technique. To demonstrate the method, we applied the calculation to the natural range of 16 target tree species as found in 1,240 provincial forest-inventory plots. The revised PSD model, with the long-term effects of interspecific competition accounted for, predicted that eastern hemlock (Tsuga canadensis), American beech (Fagus grandifolia), white birch (Betula papyrifera), red oak (Quercus rubra), sugar maple (Acer saccharum), and trembling aspen (Populus tremuloides) would experience a significant decline in their original distribution compared with balsam fir (Abies balsamea), black spruce (Picea mariana), red spruce (Picea rubens), red maple (Acer rubrum L.), and yellow birch (Betula alleghaniensis). True model accuracy improved from 64.2% with original PSD evaluations to 81.7% with revised PSD. Kappa statistics slightly increased from 0.26 (fair) to 0.41 (moderate) for original and revised PSDs, respectively.

Carbon and biomass partitioning in balsam fir (Abies balsamea).

Balsam fir (Abies balsamea (L.) Mill) was extensively sampled to investigate the effects of forest management practices, site location, within-crown position, tree component (i.e., stem, foliage, branches and roots), and tree social classes on biomass and carbon (C) partitioning at the individual tree level and across ecological regions. The sites were located in three ecologically distinct forest regions of west-central New Brunswick, Canada. There were no significant differences in %C content of trees across ecological regions or across tree social classes. However, at the individual tree level, significant differences were evident in biomass and C allocation between different parts of the tree, between treatment types (i.e., unmanaged and pre-commercially thinned stands) and between within-crown positions, indicating the need for separate estimates of biomass and C content of tree components to obtain more precise estimates of quantities at the stand level. Calculating stand C content based on constant allocation values, as is commonly done, produced errors of up to 15% compared with the values calculated in this study. Three allometric equations of biomass and C that account for partitioning among different parts of the tree were developed and compared: (1) a third-order polynomial, (2) a modified inverse polynomial and (3) a modified Weibull equation. Diameter at breast height (DBH) was used as the only explanatory variable to describe fresh biomass, dry biomass and C content. All regressions derived showed a high correlation with DBH, with most r2 values > 0.95. A comparison of the equation results showed that the modified Weibull equation gave consistent results with the best overall fit and was the simplest of the three equations investigated. The regressions can be used to estimate forest biomass and tree C content at the stand level, given specific information on DBH.

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.

Protective effects of baicalein against rotenone-induced neurotoxicity in PC12 cells and isolated rat brain mitochondria.

Baicalein is one of the major flavonoids obtained from the Scutellaria root. Previous pharmacological studies found that baicalein had neuroprotective effects in animal models of Parkinson's disease. The purpose of this paper was to explore the molecular mechanism of the action of baicalein on PC12 cells and isolated rat brain mitochondria. Firstly, we investigated the effects of baicalein on rotenone-induced toxicity in PC12 cells. The results showed that baicalein suppressed rotenone-induced apoptosis, and inhibited the accumulation of reactive oxidant species, ATP deficiency, mitochondrial membrane potential dissipation, and caspase-3/7 activation in a concentration-dependent manner, indicating that baicalein likely improved mitochondrial function. Furthermore, we used isolated rat brain mitochondria to evaluate the effect of baicalein. Treatment with baicalein prevented rotenone-induced reactive oxidant species production, ATP deficiency and mitochondrial swelling in isolated brain mitochondria. Interestingly, exposure of isolated mitochondria to baicalein promoted mitochondrial active respiration. These results suggest that baicalein may be a mitochondria-targeted antioxidant and exerts neuroprotective effects on rotenone-induced neurotoxicity. This study supports our previous research that baicalein possesses neuroprotective activity in vivo and it is worthy of further study.