Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery

The U.S. Environmental Protection Agency (EPA) initiated the Environmental Monitoring and Assessment Program (EMAP) in 1988. The wetland component (EMAP-Wetlands) is designed to provide quantitative assessments of the current status and long-term trends in the ecological condition of wetland resources. EMAP-Wetlands will develop a wetland monitoring network and will identify and evaluate indicators that describe and quantify wetland condition. The EMAP-Wetlands network will represent a probability sample of the total wetland resource. The EMAP sample is based on a triangular grid of approximately 12,600 sample points in the conterminous U.S. The triangular grid adequately samples wetland resources that are common and uniformly distributed in a region, such as the prairie pothole wetlands of the Midwest. However, the design is flexible and allows the base grid density to be increased to adequately sample wetland resources, such as the coastal wetlands of the Gulf of Mexico, which are distributed linearly along the coast. The Gulf sample network required a 49-fold increase in base grid density. EMAP-Wetlands aggregates the 56 U.S. Fish and Wildlife Service’s (FWS) National Wetland Inventory (NWI) categories (Cowardin et al. 1979) into 12 functionally similar groups (Leibowitz et al. 1991). Both the EMAP sample design and aggregated wetland classes are suitable for global inventory and assessment of wetlands.

Most Great River ecosystems (GREs) are extensively modified and are not receiving adequate protection to prevent further habitat degradation and loss of biotic integrity. In the United States, ecological monitoring and assessment of GREs has lagged behind streams and estuaries, and the management of GREs is hampered by the lack of unbiased data at appropriate spatial scales. Properties of GREs that make them challenging to monitor and assess include difficult sample logistics and high habitat diversity. The U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) has developed a comprehensive, regional-scale, survey-based monitoring approach to assessment of streams and estuaries, but has not yet conducted research on applying these tools to GRE monitoring. In this paper we present an overview of an EMAP research project on the Upper Missouri River (UMR). We summarize the assessment objectives for the study, the design for selecting sample locations, the indicators measured at these sites and the tools used to analyze data. We present an example of the type of statements that can be made with EMAP monitoring data. With modification, the set of methodologies developed by EMAP may be well suited for assessment of GREs in general.

Ecosystem variables importance in the presence and abundance of a globally invasive fish

Riparian restoration is an important objective for landscape managers seeking to redress the widespread degradation of riparian areas and the ecosystem services they provide. This study investigated the long-term outcomes of ‘one-off’ restoration activities undertaken in the Upper Murrumbidgee Catchment, NSW, Australia. The objective of the restoration was to protect and enhance riparian vegetation and control erosion, and consequently reduce sediment and nutrient delivery into the Murrumbidgee River. To evaluate the outcomes 10 years after restoration, rapid riparian vegetation and geomorphological assessments were undertaken at 29 sites spanning the four different restoration methods used (at least five replicates per treatment), as well as at nine comparable untreated sites. We also trialed the use of aerial imagery to compare width of riparian canopy vegetation and projective foliage cover prior to restoration with that observed after 10 years. Aerial imagery demonstrated the width of riparian canopy vegetation and projective foliage cover increased in all restored sites, especially those with native plantings. The rapid assessment process indicated that 10 years after riparian restoration, the riparian vegetation was in a better condition at treated sites compared to untreated sites. Width of riparian canopy vegetation, native mid-storey cover, native canopy cover and seedling recruitment were significantly greater in treated sites compared to untreated sites. Geomorphological condition of treated sites was significantly better than untreated sites, demonstrating the importance of livestock exclusion to improve bank and channel condition. Our findings illustrate the value of ‘one-off’ restoration activities in achieving long-term benefits for riparian health. We have demonstrated that rapid assessments of the vegetation and geomorphological condition can be undertaken post-hoc to determine the long-term outcomes, especially when supported with analysis of historical aerial imagery.

Section 305(b) of the United States' Clean Water Act (CWA) requires states to assess the overall quality of waters in the states, while Section 303(d) requires states to develop a list of the specific waters in their state not attaining water quality standards (a.k.a impaired waters). An integrated, efficient and cost-effective process is needed to acquire and assess the data needed to meet both these mandates. A subset of presentations at the 2002 Environmental Monitoring and Assessment Program (EMAP) Symposium provided information on how probability data, tools and methods could be used by states and other entities to aid in development of their overall assessment of condition and list of impaired waters. Discussion identified some of the technical and institutional problems that hinder the use of EMAP methods and data in the analysis to identify impaired waters as well as development needs to overcome these problems.

Beginning in 1995, the U.S. Environmental Protection Agency (U.S. EPA), Office of Research and Development has focused much of its ecological research in the Mid-Atlantic as part of the Mid-Atlantic Integrated Assessment (MAIA). The goal of MAIA is to improve the assessability of scientific information in environmental decision-making. Following the Environmental Monitoring and Assessment Program (EMAP) whose goal is to guide monitoring that effectively reflects current ecosystem condition and trends, MAIA's second, current, phase of research under the Regional Vulnerability Assessment (ReVA) program is designed to target risk management activities using available data and models. The papers presented here are from a conference held in May 2003 that presented results of research in this second phase of MAIA. The conference was organized into the following topics: 1. Assessing Current Impacts and Vulnerabilities 2. Forecasting Environmental Condition and Vulnerabilities 3. Developing Management Strategies to Optimize the Future, and 4. Assessing and Responding to Environmental Vulnerability.

Riparian vegetation cover is significantly affected by a river's hydrological conditions. Especially in arid and semiarid areas, low flow will degrade riparian vegetation, and recent, intensive human activities in the Yongding River Basin have caused a sharp decrease in river flow. We analyzed interannual change in riparian vegetation, river flow effects, and land use on vegetation coverage using the 40years (1977-2016) of remote sensing images and river flow, combined with 38years (1980-2018) of land use data. The normalized difference vegetation index (NDVI) was used to determine vegetation cover in five different categories: extremely low, low, medium, high, and extremely high based on the pixel dichotomy model. The weighted average was calculated to obtain vegetation cover trends. We show that riparian vegetation cover from four rivers increased. Compared with 1977, in 2016, combined high and extremely high vegetation covers at the Dongyang, Yang, Sanggan, and Yongding Rivers increased by 20.3%, 26.7%, 50.0%, and 39.2%, respectively. High (R = -0.976, P < 0.01) and extremely high (R = -0.762, P < 0.05) vegetation covers are negatively correlated with flow in the Yongding River. The high vegetation cover of the Sanggan River riparian zone is negatively correlated with river flow (R = -0.683, P < 0.05). In the Dongyang and Sanggan Rivers, land use analysis in the riparian zone showed that change in cultivated land, grassland, and forest were significantly correlated with high and extremely high vegetation cover. The abundant cultivated land and restoration activities are likely responsible for the increase of riparian vegetation cover as river flows decline.

River hydrology largely determines the species composition and spatial distribution of riparian vegetation. However, it is difficult to determine the riparian vegetation spatial pattern that is only influenced by river hydrology due to the complex impacts of other influencing factors in field environments. We investigated the spatial structure of riparian vegetation in the lower basin of the Tarim River in hyper‐arid western China, where distinct geomorphic and climatic features exclude the influences of factors other than river hydrological factors on the spatial structure of riparian vegetation. Landsat 8 Operational Land Imager remotely sensed data were used to identify the different vegetation types and obtain the vegetation leaf area index (LAI) in the study area. Our results showed that the overall vegetation LAI exhibited a negative exponential declining trend with distance from the river, but this relationship was different for the different vegetation types, exhibiting a negative exponential relationship for the Populus woodlands and a Gaussian‐type relationship for the Tamarix shrublands. The average width of the riparian vegetation decreased along the river by a negative power function. The average vegetation LAI decreased linearly along the river. The quantitative data we obtained regarding the river‐induced variation in the riparian vegetation cover with the distance from the river channel would particularly be useful for modelling riparian vegetation dynamics and distributions.

When the U.S. Congress passed the Federal Water Pollution Control Act in 1972, later amended by the Clean Water Act (CWA) of 1977, it tasked the newly created U.S. Environmental Protection Agency (EPA), in cooperation with the states, with periodically assessing the quality of U.S. waters and reporting on progress toward meeting the goals of the CWA. In subsequent decades, reviews by various governmental and nongovernmental organizations consistently have found available water quality data and reporting to be inadequate to evaluate the nation's progress [Shapiro et al., 2008]. In response to these concerns, in 1989 EPA's Office of Research and Development initiated the Environmental Monitoring and Assessment Program (EMAP) to develop and demonstrate scientific tools to monitor the status of, and trends in, U.S. aquatic resources and environmental stressors affecting them.Recent EPA‐led efforts involve monitoring wadeable perennial streams (streams or rivers shallow enough to be wadeable during seasonal low flows), which make up an estimated 90% of the total length of all perennial flowing waters in the United States [EPA, 2006]. Selected results from the first national survey of these streams, the national Wadeable Streams Assessment (WSA) [EPA, 2006; Paulsen et al., 2008], illustrate how such surveys can provide critical information to guide management of this important resource. Nonmonitoring applications of data from the WSA and earlier regional surveys show the wide‐ranging applicability of these rich data sets.

Developing and applying a benthic index of estuarine condition for the Virginian Biogeographic Province

One of the dilemmas in designing any large-scale macroinvertebrate bioassessment is deciding where to sample within streams. Streams contain a wide variety of habitats with varying macroinvertebrate assemblages, yet consistency in sampling protocol is needed to interpret results across sites in a region. The Environmental Monitoring and Assessment Program (EMAP) conducted large regional probability surveys in the mid-Atlantic (1993–1998) and the western US (2000–2001). In these surveys, 2 macroinvertebrate sample types were collected at each site: pool and riffle in the mid-Atlantic region, and reachwide and riffle in the western US. We analyzed data from sites where both types of samples had been collected (206 mid-Atlantic and 293 western US sites) to examine the effects of sample type on typical metric and multivariate analyses done in bioassessments. Sample types differed in terms of taxon richness measures and assemblage composition, and differences were more pronounced between mid-Atlantic riffle and pool samples than between western US reachwide and riffle samples. Nonetheless, sample-type differences did not obscure the overall pattern in ordination analyses, nor did they influence detection of important environmental gradients. In addition, bioassessments based on Ephemeroptera, Plecoptera, and Trichoptera taxon richness showed that regional assessments differed little with sample type. Our analyses indicate that typical bioassessment methods are relatively robust with respect to sample type in regional surveys. Reachwide sampling could be used with little risk to the quality of assessments in surveys covering large geographic areas where a single targeted habitat may not occur at all sites. Reachwide sampling is also easy to apply consistently at most sites and requires approximately the same effort and cost as single-habitat sampling.

The rapid spread of the exotic zebra mussel (Dreissena polymorpha) concerns aquatic resource managers in the United States and Canada. Since 1990, it has been spreading from the Great Lakes into the Northeast. The zebra mussel cannot colonize equally in northeastern lakes in part because soft water causes ion exchange and reproductive problems when [Ca2+] reaches a lower limit of approximately 12 mg/L, and pH drops below 7.3. We used (1) an alkalinity map to conservatively delineate areas expected to be at low risk for zebra mussel invasion and (2) water chemistry data from 344 lakes sampled in the 1991–1994 Environmental Monitoring and Assessment Program (EMAP) to estimate numbers and surface area of lakes at risk in the Northeast (New England, New York, and New Jersey). These lakes were randomly selected from a target population of 11,080 lakes > 1 and < 10,000 ha using a probability design that allowed inference to all lakes in the region with known confidence. An estimated 25% (2,770 SE = 410...

Many lakes in the Adirondack Mountains, New York, have acidified over the past century due to acidic atmospheric deposition. More recently, most monitored lakes have shown signs of chemical recovery (increase in acid neutralizing capacity) as sulfur deposition levels have declined in response to the Clean Air Act and other emissions control legislation. We used measured and modeled trends in past lakewater acidification and projections of future recovery from acidification to extrapolate results from judgment samples of intensively studied lakes to the population of acid-sensitive Adirondack lakes. Simulations were developed for 70 watersheds using the Model of Acidification of Groundwater in Catchments (MAGIC) to classify lakes according to their sensitivity to change in atmospheric S and N deposition. MAGIC simulations suggested that the modeled Adirondack Long-Term Monitoring Project (ALTM) and Adirondack Effects Assessment Project (AEAP) lakes were largely among the lakes in the population that had acidified most between 1850 and 1990. Most of the modeled ALTM/AEAP lakes were within the top 36% of acid sensitivity, based on model projections of past acidification and future chemical recovery, compared with the 1,829 Adirondack lakes in EPA’s Environmental Monitoring and Assessment Program (EMAP) statistical frame. Results of this research will allow fuller utilization of data from on-going chemical and biological monitoring and process-level studies by providing a basis for regionalization of findings and developing/refining relationships among watershed characteristics, chemical change, and biological responses to changing levels of acidic deposition.

The Committee on Environment and Natural Resources (CENR) has recognized a high priority need to integrate and coordinate federal agencies' efforts in order to enable a comprehensive evaluation of our nation's environmental resources and ecological systems. The federal government spends about $640 million per year collecting data about our forests, agricultural and rangelands, lakes, rivers, estuaries, and coastal marine systems. These efforts have significantly aided the progress in preserving and protecting the environment in recent decades but are not sufficiently coordinated to provide us a truly comprehensive status report or full understanding of the causes and effects of environmental change. This paper describes the Committee on Environment and Natural Resources and its functions, provides a status report on the Environmental Monitoring and Research Initiative, and offers some perspectives on the factors that will make the initiative and its contributing programs a success. In particular, the paper discusses the potential relationship with the Environmental Monitoring and Assessment Program (EMAP).

The National Stream Survey (NSS) and Environmental Monitoring and Assessment Program (EMAP) use variable probability, systematic sampling, and the Horvitz-Thompson estimator to estimate population parameters of ecological interest. A common strategy of variance estimation for systematic sampling is to assume that the population order had been randomized prior to sampling and to estimate variance under this randomized population model. The Yates-Grundy variance estimator is generally recommended for estimating the variance of the Horvitz-Thompson estimator under this model. But design features of NSS and EMAP preclude application of the Yates-Grundy estimator, so use of the Horvitz-Thompson variance estimator is required. Further, because the first-order inclusion probabilities are known only for the sample units and not the entire population, neither the actual pairwise inclusion probabilities (πuv's) nor the Hartley-Rao approximation of the πuv's can be computed. Thus the variance estimator prop...