Abstract
Forests provide the most stable and highest quality water supplies among all land uses. Quantitatively evaluating the benefits of forest water supply functions is important to effectively ...mitigate the impacts of land development, climate change, and population growth. Here, by integrating a water balance model and national drinking water data, we determined the amount of surface water yield originating on different forest ownership types at a fine resolution (88,000 watersheds) and tracked that water through the river network to drinking water intakes and the populations they serve. We found that forested lands comprised 36% of the total land area but contributed 50% of the total surface water yield. Of the 23,983 public surface drinking water intakes depending on surface water sources, 89% (serving around 150 million people) received some (>0.01%) surface water from forested lands, and 38% (serving about 60 million people) received more than 50% of their surface drinking water supply from forested lands. Privately-owned forests were the most important water source in the eastern U.S., benefiting 16 million people, followed by federal forests (14.4% of the total water supply). In contrast, federally-owned forested lands were the dominant water source (52% of the total water supply) in the West. Privately-owned forests are the most vulnerable to future land use change and associated water supply impacts. Continuing programs that support private forest landowners with financial and technical assistance through federal and state forest management agencies and potentially developing payment for ecosystem service schemes could maximize benefits for landowners so they may retain their land assets while minimizing forest loss and associated impacts on critical ecosystem services including the provisioning a clean and reliable water supply for the American public.
Canopy phenology is an important factor driving seasonal patterns of water and carbon exchange between land surface and atmosphere. Recent developments of real-time global satellite products (e.g., ...MODIS) provide the potential to assimilate dynamic canopy measurements with spatially distributed process-based ecohydrological models. However, global satellite products usually are provided with relatively coarse spatial resolutions, averaging out important spatial heterogeneity of both terrain and vegetation. Therefore, bias can result from lumped representation of ecological and hydrological processes especially in topographically complex terrain. Successful downscaling of canopy phenology to high spatial resolution would be indispensable for catchment-scale distributed ecohydrological modeling, aiming at understanding complex patterns of water, carbon and nutrient cycling in mountainous watersheds. Two downscaling approaches are developed in this study to overcome this issue by fusing multi-temporal MODIS and Landsat TM data in conjunction with topographic information to estimate high spatio-temporal resolution biophysical parameters over complex terrain. MODIS FPAR (fraction of absorbed photosynthetically active radiation) is used to provide medium spatial resolution phenology, while the variability of vegetation within a MODIS pixel is characterized by Landsat NDVI. The algorithms depend on the scale-invariant linear relationship between FPAR and NDVI, which is verified in this study. Downscaled vegetation dynamics are successfully validated both temporally and spatially with ground-based continuous FPAR and leaf area index measurements. Topographic correction during the downscaling process has a limited effect on downscaled FPAR products except for the period around the winter solstice in the study area.
► We present an MODIS–Landsat fusion model for downscaling FPAR in rugged terrain. ► The model depends on the scale-invariant linear relationship between FPAR and NDVI. ► Downscaled vegetation dynamics are successfully validated with field observations. ► The effect of topographic correction is limited except for the winter season.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•Eddy covariance and modeling were performed to study evaporation from an urban lake.•Annual lake evaporation is highly sensitive to the length of the ice-free season.•Modeling indicates the ice-free ...season will increase 0.5 days per year this century.•Lake evaporation is expected to increase as climate continues to warm this century.•Greater fluctuations in water levels are expected for the lakes within the region.
Lakes provide enormous economic, recreational, and aesthetic benefits to citizens. These ecosystem services may be adversely impacted by climate change. In the Twin Cities Metropolitan Area of Minnesota, USA, many lakes have been at historic low levels and water augmentation strategies have been proposed to alleviate the problem. White Bear Lake (WBL) is a notable example. Its water level declined 1.5 m during 2003–2013 for reasons that are not fully understood. This study examined current, past, and future lake evaporation to better understand how climate will impact the water balance of lakes within this region. Evaporation from WBL was measured from July 2014 to February 2017 using two eddy covariance (EC) systems to provide better constraints on the water budget and to investigate the impact of evaporation on lake level. The estimated annual evaporation losses for years 2014 through 2016 were 559 ± 22 mm, 779 ± 81 mm, and 766 ± 11 mm, respectively. The higher evaporation in 2015 and 2016 was caused by the combined effects of larger average daily evaporation and a longer ice-free season. The EC measurements were used to tune the Community Land Model 4 – Lake, Ice, Snow and Sediment Simulator (CLM4-LISSS) to estimate lake evaporation over the period 1979–2016. Retrospective analyses indicate that WBL evaporation increased during this time by about 3.8 mm year−1, which was driven by increased wind speed and lake-surface vapor pressure gradient. Using a business-as-usual greenhouse gas emission scenario (RCP8.5), lake evaporation was modeled forward in time from 2017 to 2100. Annual evaporation is expected to increase by 1.4 mm year−1 over this century, largely driven by lengthening ice-free periods. These changes in ice phenology and evaporation will have important implications for the regional water balance, and water management and water augmentation strategies that are being proposed for these Metropolitan lakes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree ...biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Soil respiration is an important component of terrestrial carbon cycling and can be influenced by many factors that vary spatially. This research aims to determine the extent and causes of spatial ...variation of soil respiration, and to quantify the importance of scale on measuring and modeling soil respiration within and among common forests of Northern Wisconsin. The potential sources of variation were examined at three scales: 1 variation among the litter, root, and bulk soil respiration components within individual 0.1
m measurement collars, 2 variation between individual soil respiration measurements within a site (<1
m to 10
m), and 3 variation on the landscape caused by topographic influence (100
m to 1000
m). Soil respiration was measured over a two-year period at 12 plots that included four forest types. Root exclusion collars were installed at a subset of the sites, and periodic removal of the litter layer allowed litter and bulk soil contributions to be estimated by subtraction. Soil respiration was also measured at fixed locations in six northern hardwood sites and two aspen sites to examine the stability of variation between individual measurements. These study sites were added to an existing data set where soil respiration was measured in a random, rotating, systematic clustering which allowed the examination of spatial variability from scales of <1
m to 100+
m. The combined data set for this area was also used to examine the influence of topography on soil respiration at scales of over 1000
m by using a temperature and moisture driven soil respiration model and a 4
km
2 digital elevation model (DEM) to model soil moisture. Results indicate that, although variation of soil respiration and soil moisture is greatest at scales of 100
m or more, variation from locations 1
m or less can be large (standard deviation during summer period of 1.58 and 1.28
μmol
CO
2
m
−2
s
−1, respectively). At the smallest of scales, the individual contributions of the bulk soil, the roots, and the litter mat changed greatly throughout the season and between forest types, although the data were highly variable within any given site. For scales of 1–10
m, variation between individual measurements could be explained by positive relationships between forest floor mass, root mass, carbon and nitrogen pools, or root nitrogen concentration. Lastly, topography strongly influenced soil moisture and soil properties, and created spatial patterns of soil respiration which changed greatly during a drought event. Integrating soil fluxes over a 4
km
2 region using an elevation dependent soil respiration model resulted in a drought induced reduction of peak summer flux rates by 37.5%, versus a 31.3% when only plot level data was used. The trends at these important scales may help explain some inter-annual and spatial variability of the net ecosystem exchange of carbon.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Most studies of land use effects on solute concentrations in streams have focused on smaller streams with watersheds dominated by a single land‐use type. Using land cover as a proxy for land use, the ...objective of this study was to determine whether the hydrologically‐driven response of solutes to land use in small streams could be scaled up to predict concentrations in larger receiving streams and rivers in the rural area of the Little Tennessee River basin. We measured concentrations of typically limiting nutrients (nitrogen, phosphorus), abundant anions (chloride, sulfate), and base cations in 17 small streams and four larger river sites. In the small streams, total solute concentration was strongly related to land cover ‐‐ highest in streams with developed watersheds, lowest in streams with forested watersheds, and streams with agricultural watersheds were in between. In general, the best predictor of solute concentrations in the small streams was forest land cover. We then predicted solute concentrations for the river sites based on the solute‐‐land cover relationships of the small streams using multiple linear regressions. Results were mixed ‐‐ some of the predicted river concentrations were close to measured values, others were greater or less than measured concentrations. In general, river concentrations did not scale with land cover‐solute relationships found in small tributaries. Measured values of nitrogen solutes in the river sites were greater than predicted, perhaps due to the presence of waste water treatment plants. We attributed other differences between measured and predicted river concentrations to the heterogeneous geochemistry of this mountainous region. The combined complexity of hydrology, geochemistry, and human land‐use of this mountainous region make it difficult to scale up from small streams to larger river basins.
We determined whether the hydrologically driven response of solutes to land use in small streams could be scaled up to predict concentrations in larger rivers. In the small streams, total solute concentration was strongly related to land cover. In general, river concentrations did not scale with land cover‐solute relationships found in small tributaries. The combined complexity of hydrology, geochemistry, and human land‐use make it difficult to scale up from small streams to larger rivers.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The Coweeta Hydrologic Laboratory (CHL) is a USDA Forest Service (FS) Experimental Forest, located in western North Carolina, in the southern Appalachian Mountains. Established in 1934, CHL has ...long‐term data records that include climate, streamflow, stream and atmospheric chemistry, and vegetation in several small, experimentally‐manipulated and reference watersheds. In addition to these long‐term data, additional data associated with specific projects have been collected and are available through publications and electronic archives. Notably, CHL was a member of the National Science Foundation‐funded Long‐Term Ecological Research (LTER) program from 1980–2020, which resulted in significant scientific advances and rich data sets on the five core LTER research areas: primary productivity, population studies, movement of organic matter, movement of inorganic matter, and disturbance patterns. Here we provide a brief site description and history of the CHL, including descriptions of gauged watersheds and data archives.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote ...sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis techniques. Here, we provide guidelines that will enable land managers to more effectively collaborate with remote sensing scientists to develop and apply remote sensing science to achieve monitoring objectives. We first describe fundamental characteristics of remotely sensed data and change detection analysis that affect the types and range of phenomena that can be tracked. Using that background, we describe four general steps in natural resource remote sensing projects: image and reference data acquisition, pre-processing, analysis, and evaluation. We emphasize the practical considerations that arise in each of these steps. We articulate a four-phase process that guides natural resource and remote sensing specialists through a collaborative process to articulate goals, evaluate data and options for image processing, refine or eliminate unrealistic paths, and assess the cost and utility of different options.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
We measured soil respiration and soil carbon stocks, as well as micrometeorological variables in a chronosequence of deciduous forests in Wisconsin and Michigan. The chronosequence consisted of (1) ...four recently disturbed stands, including a clearcut and repeatedly burned stand (burn), a blowdown and partial salvage stand (blowdown), a clearcut with sparse residual overstory (residual), and a regenerated stand from a complete clearcut (regenerated); (2) four young aspen (Populus tremuloides) stands in average age of 10 years; (3) four intermediate aspen stands in average age of 26 years; (4) four mature northern hardwood stands in average age of 73 years; and (5) an old‐growth stand approximately 350‐years old. We fitted site‐based models and used continuous measurements of soil temperature to estimate cumulative soil respiration for the growing season of 2005 (days 133–295). Cumulative soil respiration in the growing season was estimated to be 513, 680, 747, 747, 794, 802, 690, and 571 g C m−2 in the burn, blowdown, residual, regenerated, young, intermediate, mature, and old‐growth stands, respectively. The measured apparent temperature sensitivity of soil respiration was the highest in the regenerated stand, and declined from the young stands to the old‐growth. Both, cumulative soil respiration and basal soil respiration at 10 °C, increased during stand establishment, peaked at intermediate age, and then decreased with age. Total soil carbon at 0–60 cm initially decreased after harvest, and increased after stands established. The old‐growth stand accumulated carbon in deep layers of soils, but not in the surface soils. Our study suggests a complexity of long‐term soil carbon dynamics, both in vertical depth and temporal scale.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Many current models of ecosystem carbon exchange based on remote sensing, such as the MODIS product termed MOD17, still require considerable input from ground based meteorological measurements and ...look up tables based on vegetation type. Since these data are often not available at the same spatial scale as the remote sensing imagery, they can introduce substantial errors into the carbon exchange estimates. Here we present further development of a gross primary production (GPP) model based entirely on remote sensing data. In contrast to an earlier model based only on the enhanced vegetation index (EVI), this model, termed the
Temperature and
Greenness (TG) model, also includes the land surface temperature (LST) product from MODIS. In addition to its obvious relationship to vegetation temperature, LST was correlated with vapor pressure deficit and photosynthetically active radiation. Combination of EVI and LST in the model substantially improved the correlation between predicted and measured GPP at 11 eddy correlation flux towers in a wide range of vegetation types across North America. In many cases, the TG model provided substantially better predictions of GPP than did the MODIS GPP product. However, both models resulted in poor predictions for sparse shrub habitats where solar angle effects on remote sensing indices were large. Although it may be possible to improve the MODIS GPP product through improved parameterization, our results suggest that simpler models based entirely on remote sensing can provide equally good predictions of GPP.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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