Evaluating Microbial Indicators of Environmental Condition in Oregon Rivers

Traditional bacterial indicators used in public health to assess water quality and the Biolog system were evaluated to compare their response to biological, chemical, and physical habitat indicators of stream condition both within the state of Oregon and among ecoregion aggregates (Coast Range, Willamette Valley, Cascades, and eastern Oregon). Forty-three randomly selected Oregon river sites were sampled during the summer in 1997 and 1998. The public health indicators included heterotrophic plate counts (HPC), total coliforms (TC), fecal coliforms (FC) and Escherichia coli (EC). Statewide, HPC correlated strongly with physical habitat (elevation, riparian complexity, % canopy presence, and indices of agriculture, pavement, road, pasture, and total disturbance) and chemistry (pH, dissolved O2, specific conductance, acid-neutralizing capacity, dissolved organic carbon, total N, total P, SiO2, and SO4). FC and EC were significantly correlated generally with the river chemistry indicators. TC bacteria significantly correlated with riparian complexity, road disturbance, dissolved O2, and SiO2 and FC. Analyzing the sites by ecoregion, eastern Oregon was characterized by high HPC, FC, EC, nutrient loads, and indices of human disturbance, whereas the Cascades ecoregion had correspondingly low counts of these indicators. The Coast Range and Willamette Valley presented inconsistent indicator patterns that are more difficult to characterize. Attempts to distinguish between ecoregions with the Biolog system were not successful, nor did a statistical pattern emerge between the first five principle components and the other environmental indicators. Our research suggests that some traditional public health microbial indicators may be useful in measuring the environmental condition of lotic systems.     

Simulating Spatial and Temporal Context of Forest Management Using Hypothetical Landscapes

/ Spatially explicit models that combine remote sensing with geographic information systems (GIS) offer great promise to land managers because they consider the arrangement of landscape elements in time and space. Their visual and geographic nature facilitate the comparison of alternative landscape designs. Among various activities associated with forest management, none cause greater concern than the impacts of timber harvesting on the composition, structure, and function of landscape ecosystems. A timber harvest allocation model (HARVEST) was used to simulate different intensities of timber harvest on 23,592-ha hypothetical landscapes with varying sizes of timber production areas and different initial stand age distributions. Our objectives were to: (1) determine the relative effects of the size of timber production areas, harvest intensity, method used to extract timber, and past timber harvest activity on the production of forest interior and edge; and (2) evaluate how past management (in the form of different initial stand age distributions) constrains future timber production options. Our simulations indicated that the total area of forest interior and the amount of forest edge were primarily influenced by the intensity of timber harvest and the size of openings created by harvest. The size of the largest block of interior forest was influenced most by the size of timber harvests, but the intensity of harvest was also significant, and the size of nontimber production areas was important when harvests were numerous and widely dispersed within timber management areas, as is often the case in managed forests. Stand age-class distributions produced by past harvest activity limited the amount of timber production primarily when group selection was used, but also limited clear-cutting when recent harvest levels were high.KEY WORDS: Simulation modeling; Timber harvest; Historical context; Spatial context; Landscape pattern; Forest interior; Forest edge     

SELECTING RECONNAISSANCE STRATEGIES FOR FLOODPLAIN SURVEYS1

ABSTRACT: Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to floodplain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The boundaries thus obtained were found to be more striking and continuous in the Landsat data than in the low altitude aircraft data. The digital approach permitted satellite results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas than in areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.     

Linking dissolved and particulate phosphorus export in rivers draining California's Central Valley with anthropogenic sources at the regional scale

Pollution of water resources by phosphorus (P) is a critical issue in regions with agricultural and urban development. In this study, we estimated P inputs from agricultural and urban sources in 24 catchments draining to the Central Valley in California and compared them with measured river P export to investigate hydrologic and anthropogenic factors affecting regional P retention and export. Using spatially explicit information on fertilizer use, livestock population, agricultural production, and human population, we calculated that net surface balances for anthropogenic P ranged from -12 to 648 kg P km yr in the early 2000s. Inorganic P fertilizer and manure P comprised the largest fraction of total input for all but two catchments. From 2000 to 2003, a median of 7% (range, -287 to 88%) of net annual anthropogenic P input was exported as total P (TP). Yields (kg P km yr) of dissolved inorganic P (DIP), dissolved organic P, particulate P, and TP were not significantly related to catchment-level, per area anthropogenic P input. However, there were significant relationships between mean annual P concentrations and P input from inorganic fertilizers and manure due to the concentration of agricultural land near catchment mouths and regional variation in runoff. Catchment-level P fertilizer and manure inputs explained 4 to 23% more variance in mean annual DIP and TP concentrations than percent of catchment area in agriculture. This study suggests that spatially explicit estimates of anthropogenic P input can help identify sources of multiple forms of P exported in rivers at management-relevant spatial scales.     

干旱区绿洲土地覆盖变化遥感应用研究--以新疆于田绿洲为例

从人地关系理论出发以土地利用变化为切入点通过野外调查和遥感动态监测对干旱区绿洲土地覆盖变化规律进行了研究.在考察数据和对遥感图像的分类结果的评价的基础上对干旱区绿洲土地利用/土地覆盖空间动态变化进行规律性分析提出只有协调人地关系、加强区域地理建设才是使干旱区绿洲地区避免荒漠化的唯一道路.     

Carbon sinks and sources in China's forests during 1901-2001

This paper reports the annual carbon (C) balance of China's forests during 1901-2001 estimated using the Integrated Terrestrial Ecosystem C-budget model (InTEC). Annual carbon source and sink distributions are simulated for the same period using various spatial datasets including land cover and leaf area index (LAI) obtained from remote sensing, soil texture, climate, forest age, and nitrogen deposition. During 1901-1949, China's forests were a source of 21.0+/-7.8 Tg C yr(-1) due to disturbances (human activities). Its size increased to 122.3+/-25.3 Tg C yr(-1) during 1950-1987 due to intensified human activities in the late 1950s, early 1960s, 1970s and early 1980s. The forests became large sinks of 176.7+/-44.8 Tg C yr(-1) during 1988-2001, owing to large-scale plantation and forest regrowth in previously disturbed areas as well as growth stimulation by nondisturbance factors such as climatic warming, atmospheric CO(2) fertilization, and N deposition. From 1901 to 2001, China's forests were a small carbon source of 3.32 Pg C, about 32.9+/-22.3 Tg C yr(-1). The overall C balance in biomass from InTEC generally agrees with previous results derived from forest inventories of China's forests. InTEC results also include C stock variation in soils and are therefore more comprehensive than previous results. The uncertainty in InTEC results is still large, but it can be reduced if a detailed forest age map becomes available.     

A multi-scale remote sensing approach for monitoring northern peatland hydrology: present possibilities and future challenges

Remote sensing has the potential to provide quantitative spatially explicit hydrological information across northern peatland complexes. This paper details a multi-scale remote sensing approach for assessing the use of Sphagnum mosses as proxy indicators of near-surface hydrology. Several spectral indices developed from the near infra-red (NIR) and shortwave infra-red (SWIR) liquid water absorption bands, as well as a biophysical index can be correlated with measures of near-surface moisture in the laboratory, in the field and from airborne imagery. Data from all platforms revealed similar patterns in the spectral indices in relation to changes in moisture although the strength of correlations was reduced as the spatial scale increased. The rapid collection of temporally and spatially explicit hydrological data means that the technique has potential practical application for environmental managers and peatland scientists at the local scale. The task of up-scaling the technique for use in operational peatland hydrological monitoring to the global scale is challenging but achievable, and requires further investigation into the heterogeneity of near-surface moisture across Sphagnum patches and the application of novel image processing techniques to improve the spatial resolution of currently available satellite imagery.     

Linking Landscape Characteristics and High Stream Nitrogen in the Oregon Coast Range: Red Alder Complicates Use of Nutrient Criteria

Red alder (Alnus rubra), a nitrogen(N)‐fixing deciduous broadleaf tree, can strongly influence N concentrations in western Oregon and Washington. We compiled a database of stream N and GIS‐derived landscape characteristics in order to examine geographic variation in N across the Oregon Coast Range. Basal area of alder, expressed as a percent of watershed area, accounted for 37% and 38% of the variation in summer nitrate and total N (TN) concentrations, respectively. Relationships between alder and nitrate were strongest in winter when streamflow and landscape connections are highest. Distance to the coast and latitude, potential surrogates for sea salt inputs, and watershed area were also related to nitrate concentrations in an all‐subsets regression analysis, which accounted for 46% of the variation in summer nitrate concentrations. The model with the lowest Akaike's Information Criterion did not include developed or agricultural land cover, probably because few watersheds in our database had substantial levels of these land cover classes. Our results provide evidence, at a regional scale, that background sources and processes cause many Coast Range streams to exceed proposed nutrient criteria, and that the prevalence of a single tree species (N‐fixing red alder) exerts a dominant control over stream N concentrations across this region.     

Remote sensing for land management and planning

The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States.Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners.Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes     

Implications of Land Use Changes on Carbon Dynamics and Sequestration—Evaluation from Forestry Datasets, India

Forests and soils are a major sink of carbon, and land use changes can affect the magnitude of above ground and below ground carbon stores and the net flux of carbon between the land and the atmosphere. Studies on methods for examining the future consequences of changes in patterns of land use change and carbon flux gains importance, as they provide different options for CO₂ mitigation strategies. In this study, a simulation approach combining Markov chain processes and carbon pools for forests and soils has been implemented to study the carbon flows over a period of time. Markov chains have been computed by converting the land use change and forestry data of India from 1997 to 1999 into a matrix of conditional probabilities reflecting the changes from one class at time t to another class time t+1. Results from Markov modeling suggested Indian forests as a potential sink for 0.94 Gt carbon, with an increase in dense forest area of about 75.93 Mha and decrease of about 3.4 Mha and 5.0 Mha in open and scrub forests, if similar land use changes that occurred during 1997–1999 would continue. The limiting probabilities suggested 34.27 percent as dense forest, 6.90 as open forest, 0.4 percent mangrove forest, 0.1 percent scrub and 58 percent as non-forest area. Although Indian forests are found to be a potential carbon sink, analysis of results from transition probabilities for different years till 2050 suggests that, the forests will continue to be a source of about 20.59 MtC to the atmosphere. The implications of these results in the context of increasing anthropogenic pressure on open and scrub forests and their contribution to carbon source from land use change and forestry sector are discussed. Some of the mitigation aspects to reduce greenhouse gas emissions from land use change and forestry sector in India are also reviewed in the study.     

Effect of land-cover change on terrestrial carbon dynamics in the southern United States

Land-cover change has significant influence on carbon storage and fluxes in terrestrial ecosystems. The southern United States is thought to be the largest carbon sink across the conterminous United States. However, the spatial and temporary variability of carbon storage and fluxes due to land-cover change in the southern United States remains unclear. In this study, we first reconstructed the annual data set of land-cover of the southern United States from 1860 to 2003 with a spatial resolution of 8 km. Then we used a spatially explicit process-based biogeochemical model (Terrestrial Ecosystem Model [TEM] 4.3) to simulate the effects of cropland expansion and forest regrowth on the carbon dynamics in this region. The pattern of land-cover change in the southern United States was primarily driven by the change of cropland, including cropland expansion and forest regrowth on abandoned cropland. The TEM simulation estimated that total carbon storage in the southern United States in 1860 was 36.8 Pg C, which likely was overestimated, including 10.8 Pg C in the southeast and 26 Pg C in the south-central. During 1860-2003, a total of 9.4 Pg C, including 6.5 Pg C of vegetation and 2.9 Pg C of soil C pool, was released to the atmosphere in the southern United States. The net carbon flux due to cropland expansion and forest regrowth on abandoned cropland was approximately zero in the entire southern region between 1980 and 2003. The temporal and spatial variability of regional net carbon exchange was influenced by land-cover pattern, especially the distribution of cropland. The land-use analysis in this study is incomplete and preliminary. Finally, the limitations, improvements, and future research needs of this study were discussed.     

REMOTE SENSING OF RIPARIAN BUFFERS: PAST PROGRESS AND FUTURE PROSPECTS1

Riparian buffer zone management is an area of increasing relevance as human modification of the landscape continues unabated. Land and water resource managers are continually challenged to maintain stream ecosystem integrity and water quality in the context of rapidly changing land use, which often offsets management gains. Approaches are needed not only to map vegetation cover in riparian zones, but also to monitor the changes taking place, target restoration activities, and assess the success of previous management actions. To date, these objectives have been difficult to meet using traditional techniques based on aerial photos and field visits, particularly over large areas. Recent advances in remote sensing have the potential to substantially aid buffer zone management. Very high resolution imagery is now available that allows detailed mapping and monitoring of buffer zone vegetation and provides a basis for consistent assessments using moderately high resolution remote sensing (e.g., Landsat). Laser‐based remote sensing is another advance that permits even more detailed information on buffer zone properties, such as refined topographic derivatives and multidimensional vegetation structure. These sources of image data and map information are reviewed in this paper, examples of their application to riparian buffer mapping and stream health assessment are provided, and future prospects for improved buffer monitoring are discussed.     

WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS1

ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA‐ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA‐ECM could be applied in targeting phosphorous critical loading areas.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

Impact of Carbon Storage Through Restoration of Drylands on the Global Carbon Cycle

   Using estimates of land suitable for restoration in woodlands, grasslands, and deserts, as well as estimates of the rate at which restoration can proceed, we estimate that carbon storage in these biomes can range up to 0.8 billion tons of carbon per year (Gt C/yr), for a combination of land management strategies. This corresponds to a reduction in atmospheric buildup of 0.5 Gt C/yr, which represents up to 15% of the average annual atmospheric carbon buildup in the next century, 3.5 Gt C/yr, assuming the IPCC 92d scenario. A global strategy for reducing atmospheric carbon dioxide concentration will require the implementation of multiple options. The advantage of carbon storage in restored drylands is that it comes as a side benefit to programs that are also justifiable in terms of land management.     

Carbon dioxide flux as affected by tillage and irrigation in soil converted from perennial forages to annual crops

Among greenhouse gases, carbon dioxide (CO(2)) is one of the most significant contributors to regional and global warming as well as climatic change. A field study was conducted to (i) determine the effect of soil characteristics resulting from changes in soil management practices on CO(2) flux from the soil surface to the atmosphere in transitional land from perennial forages to annual crops, and (ii) develop empirical relationships that predict CO(2) flux from soil temperature and soil water content. The CO(2) flux, soil temperature (T(s)), volumetric soil water content (theta(v)) were measured every 1-2 weeks in no-till (NT) and conventional till (CT) malt barley and undisturbed soil grass-alfalfa (UGA) systems in a Lihen sandy loam soil (sandy, mixed, frigid Entic Haplustoll) under irrigated and non-irrigated conditions in western North Dakota. Soil air-filled porosity (epsilon) was calculated from total soil porosity and theta(v) measurements. Significant differences in CO(2) fluxes between land management practices (irrigation and tillage) were observed on some measurement dates. Higher CO(2) fluxes were detected in CT plots than in NT and UGA treatments immediately after rainfall or irrigation. Soil CO(2) fluxes increased with increasing soil moisture (R(2)=0.15, P<0.01) while an exponential relationship was found between CO(2) emission and T(s) (R(2)=0.59). Using a stepwise regression analysis procedure, a significant multiple regression equation was developed between CO(2) flux and theta(v), T(s) (CO(2) [Formula: see text] ; R(2)=0.68, P0.01). Not surprisingly, soil temperature was a driving factor in the equation, which accounted for approximately 59% in variation of CO(2) flux. It was concluded that less intensive tillage, such as no-till or strip tillage, along with careful irrigation management will reduce soil CO(2) evolution from land being converted from perennial forages to annual crops.     

Improving National-Scale Carbon Stock Inventories Using Knowledge on Land Use History

National-scale inventories of soil organic carbon (SOC) and forest floor carbon (FFC) stocks have a high uncertainty. Inventories are often based on the interpolation of sampled information, often using a number of covariables to help such interpolation. The rationale for the choice of these covariables is not always documented, despite the fact that many local-scale studies have identified the factors explaining spatial variability of SOC and FFC stocks. These studies indicate, among others the importance of long-term land use history. Despite this, information on the effects of land use history has never been used to explain variability of carbon stocks in national-scale inventories. We designed an alternative method to improve national-scale inventories of SOC and FCC for the Dutch sand area that takes stock of the findings of detailed case studies. Determinants for SOC and FFC stocks derived from landscape-scale case studies were used to map national-scale spatial variability and to calculate national totals. The resulting national-scale spatial distribution was compared with the SOC stock map from the current Dutch greenhouse gas inventory. Using land use history to explain SOC variability decreased the error of the SOC stock estimate in 60 % of the area. The error in FFC stocks decreased in half of the forest area after including soil fertility, tree species, and forest age as explanatory factors. Estimates with reduced uncertainty will make land use and land management a more attractive and acceptable mitigation option to reduce emissions of greenhouse gases for the LULUCF sector.     

Sensitivity of Thermal Habitat of a Trout Stream to Potential Climate Change,Wisconsin, United States1

Abstract: Airborne thermal remote sensing from four flights on a single day from a single‐engine airplane was used to collect thermal infrared data of a 10.47‐km reach of the upper East Branch Pecatonica River in southwest Wisconsin. The study uses a one‐dimensional stream temperature model calibrated with the longitudinal profiles of stream temperature created from the four thermal imaging flights and validated with three days of continuous stream temperature data from instream data loggers on the days surrounding the thermal remote‐sensing campaign. Model simulations were used to quantify the sensitivity of stream thermal habitat to increases in air and groundwater temperature and changes in base flow. The simulations indicate that stream temperatures may reach critical maximum thresholds for brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) mortality, particularly if both air temperature increases and base flow declines. The approach demonstrates that thermal infrared data can greatly assist stream temperature model validation due to its high spatial resolution, and that this spatially continuous stream temperature data can be used to pinpoint spatial heterogeneity in groundwater inflow to streams. With this spatially distributed data on thermal heterogeneity and base‐flow accretion, stream temperature models considering various climate change scenarios are able to identify thermal refugia that will be critical for fisheries management under a changing climate.     

Exploring changes in Ecuadorian land use for food production and their effects on natural resources

A model is used for the dynamic and spatially explicit exploration of near future agricultural land-use changes. In a case study for Ecuador, different plausible scenarios are formulated, taking into account possible developments in national food demand until the year 2010. The protection of nature parks and restrictions due to land degradation are evaluated with respect to their possible spatial impacts on the land-use change dynamics within the country. Under the assumptions of the demand scenarios, agricultural land-use expands significantly, resulting in more use of land in existing agricultural areas and frontier-type expansion into relatively undisturbed natural areas. The patterns of change depend on the increase in demand, competition between land-use types, changes in driving factors of land use, and the area and characteristics of land that is excluded from agricultural use. The modelled land-use dynamics are related to their possible impacts on the natural resource base, specifically soil fertility. The results indicate potential negative effects of land-use changes on the soil nutrient balance and biodiversity. It is argued that spatial and temporal quantification of land-use dynamics at the landscape level can support research and policies aimed at understanding the driving factors of land-use change and the behaviour of complex agro-ecosystems under changing conditions at different scales. In this way, issues dealing with sustainable food production and the management of the natural resource base can be addressed in a more integrated and quantitative manner.     

Development and Validation of an Aquatic Fine Sediment Biotic Index

The Fine Sediment Biotic Index (FSBI) is a regional, stressor-specific biomonitoring index to assess fine sediment (<2 mm) impacts on macroinvertebrate communities in northwestern US streams. We examined previously collected data of benthic macroinvertebrate assemblages and substrate particle sizes for 1,139 streams spanning 16 western US Level III Ecoregions to determine macroinvertebrate sensitivity (mostly at species level) to fine sediment. We developed FSBI for four ecoregion groupings that include nine of the ecoregions. The grouping were: the Coast (Coast Range ecoregion) (136 streams), Northern Mountains (Cascades, N. Rockies, ID Batholith ecoregions) (428 streams), Rockies (Middle Rockies, Southern Rockies ecoregions) (199 streams), and Basin and Plains (Columbia Plateau, Snake River Basin, Northern Basin and Range ecoregions) (262 streams). We excluded rare taxa and taxa identified at coarse taxonomic levels, including Chironomidae. This reduced the 685 taxa from all data sets to 206. Of these 93 exhibited some sensitivity to fine sediment which we classified into four categories: extremely, very, moderately, and slightly sensitive; containing 11, 22, 30, and 30 taxa, respectively. Categories were weighted and a FSBI score calculated by summing the sensitive taxa found in a stream. There were no orders or families that were solely sensitive or resistant to fine sediment. Although, among the three orders commonly regarded as indicators of high water quality, the Plecoptera (5), Trichoptera (3), and Ephemeroptera (2) contained all but one of the species or species groups classified as extremely sensitive. Index validation with an independent data set of 255 streams found FSBI scores to accurately predict both high and low levels of measured fine sediment.