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.

Impacts of re-vegetation on soil water dynamics in a semiarid region of Northwest China

Understanding how vegetation (shrub) cover in drylands affects local-to-regional soil water dynamics and associated water balances is of immense importance because of the abundance of afforestation projects worldwide. Vegetation's role in the control of soil water presents a particular challenge to soil water storage (SWS) management in the drylands of China. To address this knowledge gap, we conducted a two-year study in the Mu Us Desert of northwest China. The study involved the acquisition of in-situ soil water measurements within the first 180 cm of soil at three sand dune sites characterized by their differences in % shrub cover. The sand dunes varied from a vegetation-free, bare-ground sand dune site (BF) and two partly vegetated sites, one with medium-level (40 %) and another with high shrub cover (80 %; MF and HF, respectively). Results revealed that the site with the high shrub cover (HF) suffered a net reduction in soil water content (SWC) by up to 32.7 and 39.8 % in the shallow and deep subsoil (0-100 and 100-180 cm), respectively, when compared to corresponding changes at the BF site. Soil water content was shown to be largely influenced by site properties, namely shrub biomass and litter density (p < 0.05). Due to aboveground vegetation and rainfall interception by the litter, 32.2 mm of effective rainfall was reduced to the soil for every 10 %-increase in shrub cover. Bands of soil water depletion during the dry year did not fully recover during the following wet year, resulting in the development of a dried soil layer with an average SWC of 4.6-7.8 %. Increased evapotranspiration (ETtotal) led to a decrease in SWS and relative extractable soil water (REW), which caused ETtotal at HF to be lower than the rate observed at MF. These findings highlight the need for improvements in current restoration strategies, meant at striking a balance between vegetation restoration and SWC by developing optimal plant-community cover and mosaicked vegetation systems.

Vegetation-cover control of between-site soil temperature evolution in a sandy desertland

Vegetation has an important influence on soil temperature (ST). However, the possible effects of surface vegetation on ST and their feedback on microclimate remain uncertain due to the lack of in-situ and long-term environmental records, especially for arid and semiarid regions of the world. A continuous, two-year study was implemented over a bare sand dune (BF) and two scrub-vegetation sites of variable cover in the Mu Us Desert of northwest China. Surface vegetation at the two non-bare sites varied from about 40% (moderate cover, MF) and 80 % (high cover, HF) of their respective surface area. Depiction of the vertical ST-profile was based on an array of field-based measurements taken within the uppermost 180 cm of the soil complex at each site. Compared with the BF site, mean ST at MF and HF decreased by 1.2 and 1.6 °C during the uniform thaw period and increased by 0.1 and 1 °C during uniform freezing. Amplitude of seasonal variation in ST for both vegetated sites, i.e., MF and HF, was reduced by 2.4 and 4.9 °C, respectively. As soil cooling during the uniform thaw period was greater than soil warming during uniform freezing, annual mean ST decreased at both vegetated sites by 1.6 and 1.2 °C (for MF and HF, respectively) compared to ST at BF. Differences in ST among the three sites during the uniform freeze and thaw periods were exponentially correlated with the extent of site vegetation cover, leaf area index, aboveground biomass, and on-the-ground litter thickness. Vegetation cover was shown to reduce the depth of the frost layer by 30 cm and prolonged the uniform thaw period by 1-35 days at the HF site. Mean daily STs at the center of each soil layer at the three sites were simulated with a two-equation model developed for this study, yielding a coefficient of determination (R2) of 0.91 when modeled STs were compared against their corresponding field observations. Increases in winter ST has potential to safeguard ground-dwelling grubs and other agriculturally harmful insects from freezing and dying. Likewise, decreases in annual ST could help promote decreases in litter decomposition, potentially lessening the effects of wind erosion.

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.

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.

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.

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 cm² 5-year^-1 and volume: 0.0008 m³ 5-year^-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm² 5-year^-1 and 0.0393 m³ 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.

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.

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.

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.

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.

Cloning and characterization of leaf cDNAs that are differentially expressed between wheat hybrids and their parents

Previous studies have shown that heterosis is associated with differential gene expression between hybrids and their parents. In this study, we performed a screen for genes that are differentially expressed between wheat hybrids and their parents in jointing-stage leaves and flag leaves using the differential display technique. Twenty-four differentially expressed cDNA were cloned and sequenced, and their expression patterns were confirmed by reverse-Northern blotting. Sequence analysis and database searches revealed that among the genes that showed differential expression between hybrid and parents were transcription factor genes and genes involved in metabolism, signal transduction, disease resistance, and retrotransposons. These results indicate that hybridization between two parental lines can cause changes in the expression of a variety of genes, and it is concluded that the altered pattern of gene expression in the hybrid may be responsible for the observed heterosis.

Gaseous carbon dioxide and methane, as well as dissolved organic carbon losses from a small temperate wetland under a changing climate

Temperate forests can contain large numbers of wetlands located in areas of low relief and poor drainage. These wetlands can make a large contribution to the dissolved organic carbon (DOC) load of streams and rivers draining the forests, as well as the exchange of methane (CH4) and carbon dioxide (CO2) with the atmosphere. We studied the carbon budget of a small wetland, located in Kejimkujik National Park, Nova Scotia, Canada. The study wetland was the Pine Marten Brook site, a poor fen draining a mixed hardwood-softwood forest. We studied the loss of DOC from the wetland via the outlet stream from 1990 to 1999 and related this to climatic and hydrologic variables. We added the DOC export information to information from a previously published model describing CH4 and CO2 fluxes from the wetland as a function of precipitation and temperature, and generated a new synthesis of the major C losses from the wetland. We show that current annual C losses from this wetland amount to 0.6% of its total C mass. We then predicted that under climate changes caused by a doubling of atmospheric CO2 expected between 2040 and 2050, total C loss from the wetland will almost double to 1.1% of total biomass. This may convert this wetland from what we assume is currently a passive C storage area to an active source of greenhouse gases.

Foliage responses of spruce trees to long-term low-grade sulfur dioxide deposition

Foliage on spruce trees (Picea rubens Sarg.) growing on dry SO(2) deposition zones (dry SO(2) deposition ranging from 0.5 and 8.5 S kg ha(-1) year(-1)) downwind from a SO(2) emission source was analyzed to assess chronic effects of long-term low-grade SO(2) deposition on net photosynthesis, stomatal conductance, dark respiration, stomatal antechamber wax structures, elemental concentrations in and on foliage (bulk and surficial concentrations), and types of epiphytic fungi that reside in the phylloplane. Elemental distributions on stomatal antechambers, on fungal colonies, and on smooth surfaces between stomates and fungus colonies were determined with a scanning electronic microscope (SEM) by way of X-ray scanning. It was found that net photosynthesis of newly developed spruce foliage (current-year, and 1-year-old) was not significantly affected by the local SO(2) deposition rates. Sulfur dioxide deposition, however, may have contributed to the gradual decrease in net photosynthesis with increasing needle age. Dark respiration rates were significantly higher on foliage taken from high SO(2) deposition zones. Stomatal rod-web structures deteriorated to flakes with increasing needle age and increasing SO(2) deposition. Further inspection of the needle surfaces revealed an increasing abundance of fungal colonies with increasing needle age. Many fungal taxa were isolated and identified. It was found that black yeasts responded positively, and Xylohypha pinicola responded negatively to high rates of SO(2) deposition. Surficial concentrations of elements such as P, S, K, Cl, Ca were about 10 times higher on fungal colonies than on smooth needle surfaces. Surficial Ca contents on 4 or 5-year-old needles decreased with increasing SO(2) deposition, but surficial S concentrations remained the same. In contrast, bulk foliar Ca and S concentrations increased with increasing SO(2) deposition.