A framework for assessment and monitoring of small mammals in a lowland tropical forest

Development projects in tropical forests can impact biodiversity.Assessment and monitoring programs based on the principles of adaptive management assist managers to identify and reduce suchimpacts. The small mammal community is one important component ofa forest ecosystem that may be impacted by development projects. In 1996, a natural gas exploration project was initiated in a Peruvian rainforest. The Smithsonian Institution's Monitoring andAssessment of Biodiversity program cooperated with Shell Prospecting and Development Peru to establish an adaptive management program to protect the region's biodiversity. In thisarticle, we discuss the role of assessing and monitoring small mammals in relation to the natural gas project. We outline theconceptual issues involved in establishing an assessment andmonitoring program, including setting objectives, evaluating the results and making appropriate decisions. We also summarizethe steps taken to implement the small mammal assessment, provideresults from the assessment and discuss protocols to identifyappropriate species for monitoring.     

Biodiversity and bird surveys in Finnish environmental impact assessments and follow-up monitoring

Environmental Impact Assessments (EIAs) that are applied in the planning phases of large land-use and construction projects are aimed at aiding decision-making and mitigating significant environmental impacts. In light of the global biodiversity crisis, conducting high-quality biodiversity impact assessments is important, as biodiversity information, among other factors, has the potential to influence how projects will be implemented in the end. We investigated the biodiversity and bird surveys conducted and the number of bird species of conservation concern in peat extraction and wind farm projects to which an EIA was applied to in 1995–2016 in Finland and compared whether these factors differed between the project types and between implemented and unimplemented projects. We also studied the availability of follow-up monitoring data of biodiversity impacts within the two project types. The number of nationally threatened breeding birds was significantly lower in implemented than in unimplemented peat extraction projects. The overall probability of being implemented was significantly negatively associated with the year the EIA began for both project types. All permitted peat extraction projects and 22% of wind farm projects conducted post-construction biodiversity monitoring; however, only some projects enabled before-after comparisons. Our results are in line with earlier findings that demonstrate the difficulty of showing the direct impacts of biodiversity information on EIA decision-making and to what extent it is related to project approval or rejection. The role of follow-up monitoring in the EIA and project development could also be strengthened.     

Sampling design for long-term regional trends in marine rocky intertidal communities

Probability-based designs reduce bias and allow inference of results to the pool of sites from which they were chosen. We developed and tested probability-based designs for monitoring marine rocky intertidal assemblages at Glacier Bay National Park and Preserve (GLBA), Alaska. A multilevel design was used that varied in scale and inference. The levels included aerial surveys, extensive sampling of 25 sites, and more intensive sampling of 6 sites. Aerial surveys of a subset of intertidal habitat indicated that the original target habitat of bedrock-dominated sites with slope ≤30° was rare. This unexpected finding illustrated one value of probability-based surveys and led to a shift in the target habitat type to include steeper, more mixed rocky habitat. Subsequently, we evaluated the statistical power of different sampling methods and sampling strategies to detect changes in the abundances of the predominant sessile intertidal taxa: barnacles Balanomorpha, the mussel Mytilus trossulus, and the rockweed Fucus distichus subsp. evanescens. There was greatest power to detect trends in Mytilus and lesser power for barnacles and Fucus. Because of its greater power, the extensive, coarse-grained sampling scheme was adopted in subsequent years over the intensive, fine-grained scheme. The sampling attributes that had the largest effects on power included sampling of “vertical” line transects (vs. horizontal line transects or quadrats) and increasing the number of sites. We also evaluated the power of several management-set parameters. Given equal sampling effort, sampling more sites fewer times had greater power. The information gained through intertidal monitoring is likely to be useful in assessing changes due to climate, including ocean acidification; invasive species; trampling effects; and oil spills.     

Serial Correlation and Inter-annual Variability in Relation to the Statistical Power of Monitoring Schemes to Detect Trends in Fish Populations

We studied the effects of inter-annual variability and serial correlation on the statistical power of monitoring schemes to detect trends in biomass of bream (Abramis brama) in Lake Veluwemeer (The Netherlands). In order to distinguish between 'true' system variability and sampling variability we simulated the development of the bream population, using estimates for population structure and growth, and compared the resulting inter-annual variabilities and serial correlations with those from field data. In all cases the inter-annual variability in the field data was larger than in simulated data (e.g. for total biomass of all assessed bream sigma = 0.45 in field data, and sigma = 0.03-0.14 in simulated data) indicating that sampling variability decreased statistical power for detecting trends. Moreover, sampling variability obscured the inter-annual dependency (and thus the serial correlation) of biomass, which was expected because in this long-lived population biomass changes are buffered by the many year classes present. We did find the expected serial correlation in our simulation results and concluded that good survey data of long-lived fish populations should show low sampling variability and considerable inter-annual serial correlation. Since serial correlation decreases the power for detecting trends, this means that even when sampling variability would be greatly reduced, the number of sampling years to detect a change of 15%.year(-1) in bream populations (corresponding to a halving or doubling in a six-year period) would in most cases be more than six. This would imply that the six-year reporting periods that are required by the Water Framework Directive of the European Union are too short for the existing fish monitoring schemes.     

A cost-precision model for marine environmental monitoring,based on time-integrated averages

Ongoing marine monitoring programs are seldom designed to detect changes in the environment between different years, mainly due to the high number of samples required for a sufficient statistical precision. We here show that pooling over time (time integration) of seasonal measurements provides an efficient method of reducing variability, thereby improving the precision and power in detecting inter-annual differences. Such data from weekly environmental sensor profiles at 21 stations in the northern Bothnian Sea was used in a cost-precision spatio-temporal allocation model. Time-integrated averages for six different variables over 6 months from a rather heterogeneous area showed low variability between stations (coefficient of variation, CV, range of 0.6–12.4%) compared to variability between stations in a single day (CV range 2.4–88.6%), or variability over time for a single station (CV range 0.4–110.7%). Reduced sampling frequency from weekly to approximately monthly sampling did not change the results markedly, whereas lower frequency differed more from results with weekly sampling. With monthly sampling, high precision and power of estimates could therefore be achieved with a low number of stations. With input of cost factors like ship time, labor, and analyses, the model can predict the cost for a given required precision in the time-integrated average of each variable by optimizing sampling allocation. A following power analysis can provide information on minimum sample size to detect differences between years with a required power. Alternatively, the model can predict the precision of annual means for the included variables when the program has a pre-defined budget. Use of time-integrated results from sampling stations with different areal coverage and environmental heterogeneity can thus be an efficient strategy to detect environmental differences between single years, as well as a long-term temporal trend. Use of the presented allocation model will then help to minimize the cost and effort of a monitoring program.     

The effectiveness of the mitigation hierarchy in environmental impact studies on marine ecosystems: A case study in France

While the development of maritime economic activity is increasingly encouraged, the consideration of its impacts constitutes a real challenge. The limitations of the implementation of the mitigation hierarchy have been widely discussed in scientific literature, yet data on marine biodiversity offset practices remains scarce. In this study, we investigated the use of Environmental Impact Assessments (EIAs) as suitable instruments to achieve the No Net Loss objective. Drawing on a French approach developed for the initial assessment of the European Marine Strategy Framework Directive, we examined the pressures and impacts related to various marine development projects and the effectiveness of the mitigation hierarchy in limiting these. An analysis of 55 recent French environmental impact studies showed that only 7% of the proposed measures had the aim of offsetting predicted degradation of sites of remarkable biodiversity. This can be partly explained by the lack of a clear definition of ‘significant impact’, which varies greatly depending on what is impacted, in turn allowing socio-economic activities to benefit more easily from offset. Furthermore, offsetting does not always constitute the final step of the mitigation hierarchy, highlighting the need to reinforce avoidance and reduction steps. Although we acknowledge the role of EIA in mitigating the negative impacts of development projects, synergies with other European marine environmental policies such as the Marine Strategy Framework Directive (MSFD) and the Maritime Spatial Planning directive (MSP) should be developed in order to improve current practices.     

The threshold between natural recovery and the need for artificial restoration in degraded lands in Fujian Province, China

Whether to use artificial restoration or to allow natural recovery of degraded land has been an important topic in restoration ecology because of the need to determine the most appropriate way to restore degraded lands that have suffered from serious soil erosion. To identify the threshold between a need for artificial restoration and the possibility of natural recovery, we analyzed the vegetation cover, soil fertility parameters, erosion modulus, and runoff coefficient in 32 plots with different vegetation covers in China’s Fujian province from 1999 to 2009. In our study, 20 % vegetation cover appeared to be the threshold between natural recovery and artificial restoration. When vegetation cover dropped below 20 %, it was difficult to stabilize the original ecological structure and functions based on natural recovery mechanisms, and artificial restoration was needed. By monitoring sites to detect when vegetation cover is approaching this threshold, local managers could determine whether natural or assisted recovery represents the most appropriate strategy for ecological restoration.     

Effective monitoring of agriculture: a response

The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. We welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on our earlier paper, "Monitoring the World's Agriculture" (Sachs et al., Nature, 2010, 466, 558-560). In this response, we address their three main critiques labeled as 'the passive approach', 'the problem with uniform metrics' and 'the problem with composite metrics'. We expand on specific research questions at the core of the network design, on the distinction between key universal and site-specific metrics to detect change over time and across scales, and on the need for composite metrics in decision-making. We believe that simultaneously measuring indicators of the three pillars of sustainability (environmentally sound, social responsible and economically viable) in an effectively integrated monitoring system will ultimately allow scientists and land managers alike to find solutions to the most pressing problems facing global food security.     

A framework for assessment and monitoring of arthropods in a lowland tropical forest

By applying principles of adaptive management, and by using the valuable information that arthropods provide from assessment and monitoring programs, managers can identify and reduce possible impacts on biodiversity in development projects. In 1996, the Smithsonian Institution's Monitoring and Assessment of Biodiversity program worked together with Shell Prospecting and Development Peru to establish an adaptive management program to protect biodiversity in a natural gas exploration project in a Peruvian rainforest. In this paper, we outlined the conceptual steps involved in establishing an assessment and monitoring program for arthropods, including setting objectives, evaluating the results and making decisions. We also present the results of the assessment using some of groups of arthropods, and summarize the steps taken to identify appropriate groups for monitoring.     

Monitoring Sustainable Forest Management in Different Jurisdictions

The concept of sustainable forest management (SFM) requires forest resource managers to monitor and collect information pertaining to their environmental, economic and social impact. There are increasing expectations from a variety of publics (government, customers, and other stakeholders) that forests be demonstrably well-managed, creating incentives for forest managers to design credible systems for assessing their management performance. It is against this background that local, national and international approaches to regulating forest practices have been evolving. This article reviews the different dimensions of governance as they relate to monitoring and information reporting in the forest sector. Specifically, it discusses the changing role of sovereignty, the effects of globalization and the emergence of civil society stakeholders in forestry-related decision-making. Concepts such as sovereignty and globalization have important implications for monitoring forest practices and for defining SFM. Whether SFM standard creation and enforcement involves a sovereign, shared-sovereignty or civil society approach will affect the level and nature of SFM monitoring. As a result, we need to better consider the concept of monitoring appropriate to the scale and intensity of operations, how monitoring and information reporting standards differ between jurisdictions, and what this means for independently verifying SFM at an inter-jurisdictional level.     

Water quality assessment programs in Australia deciding what to measure,and how and where to use bioindicators

Effective water quality assessment programs require the formulation of common objectives between managers who are making decisions and scientists who are obtaining the information on which those decisions are to be made. The data collected must be apropriate for use in the decision making process. After the objectives have been formulated a number of testable hypotheses can be proposed and evaluated in terms of what information is required for decision making.From a management perspective it is important to know if an impact occurs and what management strategy to adopt to reduce or eliminate the impact. When bioaccumulators are used to indicate environmental quality the organisms proposed need to be fully evaluated before being used. Communities, which are often used to assess levels of impact, have the capacity to assimilate pollutants and they will function under pollutant stress. Thus managers need to make value judgements about when a community structure or function has shifted from acceptable to adverse. Bioassays in which the effects of pollutants on growth, biochemistry and behaviour are measured, give an indication of the sub-lethal effects of a pollutant, but it is difficult to set meaningful levels that are not to be exceeded for use by managers.Difficulties in using chemical and biological data mainly arise from a lack of appreciation of environmental heterogeneity. The data obtained must meet the needs for statistically testing hypotheses. Before programs can be designed to meet statistical needs the potential sources of variability must be considered. Once the minimum differences that are seen as important have been determined, the number of replicates needed can be calculated. Data verification is also needed, as if the validity of data is questioned, so will any decisions that have been made based on those data. Finally programs should be designed to minimize the sampling effort/cost to meet the objectives.     

Using statistical power analysis as a tool when designing a monitoring program: experience from a large-scale Swedish landscape monitoring program

The National Inventory of Landscapes in Sweden (NILS) is a large-scale, sample-based monitoring program that combines aerial photointerpretation with field inventory to follow landscape-scale biophysical conditions and changes. A statistical power analysis was conducted before the NILS program began in 2003 with the aim to determine an appropriate sampling effort and compare some design alternatives. The chosen sampling effort was then evaluated in a second power analysis conducted just before the first 5-year re-inventory rotation started. The latter power analysis revealed which magnitude of actual change might be detected within the future for different central monitoring variables. This article reports results from these power analyses and discusses our experiences in using power analysis as a tool for designing large-scale monitoring programs. The results showed that even quite small changes in the more common variables, such as land cover types and more common plant species, can be detected on the national scale. However, on the regional scale, or for less common variables, changes will be more difficult to detect. The power analyses have revealed the size level of changes that will be possible to detect. The results have also generated incentives for further improvements of NILS, e.g., input to the modification and revision of the variable content, flow and hierarchy, and incentives for launching other complementary monitoring programs connected to NILS. They have also created a basis for a better and more user-oriented communication of results from NILS to different stakeholders.     

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest

Resource exploitation in lowland tropical forests is increasingand causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We proposethe use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests.We established MWPs at 4 sites to: (1) describe and comparecomposition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs),and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similarspecies composition and abundance and that both perform equallywell at detecting rare species. However, MWPs tend to record morespecies, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees 10 cm dbh. The value of MWPs for assessment and monitoringis discussed, along with recommendations for improving the sampling design to increase power.     

Aerial Monitoring of Marine Waterfowl in the Alaskan Beaufort Sea

The purpose of this study was to design and test a monitoring protocol for marine waterfowl in the central Alaskan Beaufort Sea. The study provides an important case-study of how a long-term monitoring program may be affected by unanticipated human disturbances.Because of its overwhelming and widespread abundance, relatively sedentary behavior, ease in counting, and the extensive historical database, the long-tailed duck (Clangula hyemalis) was selected as the focal species. Two null hypotheses were formulated concerning potential changes in the numbers and distribution of long-tailed ducks in relation to disturbance in an industrial study area, compared to a reference study area located about 50 km to the east.A 9-year historical database (1977–1984, 1989) of long-tailed duck densities and other important data recorded during systematic aerial surveys was analyzed retrospectively using multiple regression techniques. The retrospective analyses determined which of several predictor variables recorded were significantly related to long-tailed duck density. Separate analyses were conducted for two periods: (1) the overall period when long-tailed ducks were present in the lagoon study areas, and (2) the shorter adult male molt period. The results of the two analyses indicated that 57% and 68%, respectively, of the total variation in long-tailed duck density during the two periods could be explained by variables recorded during the surveys. Predictor variables representing habitat, day of the year, time of day, amount of ice, and wave height recorded on-transect during surveys were most closely associated with long-tailed duck density. Measurement error during the surveys, and influences outside the study area such as nesting success in tundra habitats and mortality during migration and in over-wintering areas likely also had strong influences on the results, but these factors were not measurable in our study.Based on results of the retrospective analyses, a long-term monitoring protocol consisting of a program of systematic aerial surveys and an analyses of variance and covariance (ANOVA and ANCOVA) statistical procedure was designed and initially tested in 1990 and 1991. This 2-year testing phase resulted in several revisions to the monitoring protocol. Refinements were made to the original sampling procedures, to the survey schedule, and to the recommended statistical analysis procedures. Results of the ANOVA and ANCOVA indicated that there was no evidence of a change in long-tailed duck densities that could be attributable to disturbance (from any source) in the industrial study area relative to a reference area with no industrial development. Other analyses indicated that the sampling and analysis procedures would be adequate to detect long-term trends in long-tailed duck density and localized disturbance effects, but that the monitoring program should be continued well beyond two years to detect statistically significant changes. As a result, additional aerial surveys of both study areas were conducted again during 1999–2001.Results of the revised ANOVA and ANCOVA of the 1990–1991 and 1999–2001 survey data indicated that the density of long-tailed ducks had significantly declined in coastal lagoons along the central Alaskan Beaufort Sea coast during the study period. In addition, disturbances throughout the barrier island-lagoon systems used by these ducks, including both the industrial and the reference study areas, had significantly increased over the same period. However, because unanticipated disturbances from a variety of anthropogenic sources, and not just industry sources, increased in both study areas, the reference study area was not an effective statistical control. As a result, the decline in long-tailed duck density in both study areas was not attributable to industry-related activities. Although the monitoring protocol described here is an effective method to detect statistically significant changes in long-tailed duck distribution and abundance in the nearshore Alaskan Beaufort Sea, many more years of sampling would be necessary to attribute observed changes to industry-related disturbances.     

Attributes of reliable long-term landscape-scale studies: Malpractice insurance for landscape ecologists

Monitoring long-term change in forested landscapes is an intimidating challenge with considerable practical, methodological, and theoretical limitations. Current field approaches used to assess vegetation change at the plot-to-stand scales and nationwide forest monitoring programs may not be appropriate at landscape scales. We emphasize that few vegetation monitoring programs (and, thus, study design models) are designed to detect spatial and temporal trends at landscape scales. Based primarily on advice from many sources, and trial and error, we identify 14 attributes of a reliable long-term landscape monitoring program: malpractice insurance for landscape ecologists. The attributes are to: secure long-term funding and commitment; develop flexible goals; refine objectives; pay adequate attention to information management; take an experimental approach to sampling design; obtain peer-review and statistical review of research proposals and publications; avoid bias in selection of long-term plot locations; insure adequate spatial replication; insure adequate temporal replication; synthesize retrospective, experimental, and related studies; blend theoretical and empirical models with the means to validate both; obtain periodic research program evaluation; integrate and synthesize with larger and smaller scale research, inventory, and monitoring programs; and develop an extensive outreach program. Using these 14 attributes as a guide, we describe one approach to assess the potential effect of global change on the vegetation of the Front Range of the Colorado Rockies. This self-evaluation helps identify strengthes and weaknesses in our program, and may serve the same role for other landscape ecologists in other programs.     

Quantifying impact reduction due to avoidance,minimization and restoration for a natural gas pipeline in the Peruvian Andes

We present monitoring methods and quantitative biodiversity data to document components of the mitigation hierarchy. We estimated avoidance, minimization, restoration and impact reduction in quality hectares for the 25 m wide right of way of a 408 km natural gas buried pipeline that crosses 14 Ecological Landscape Units (ELUs) in the tropical Andes of Peru. We found that applying the mitigation hierarchy as part of a comprehensive biodiversity action plan substantially reduced impacts on biodiversity in all habitats studied. Avoidance and right of way minimization contributed to significant impact reduction. We quantified impact reduction during construction and operation on the right of way of the pipeline over a five-year period and found that restoration was the greatest contributor to reducing impacts. We documented that most ELUs have a positive restoration trajectory. We also documented how monitoring over large scale spatial scales, in combination with site-specific monitoring, generated data for management to determine restoration priorities and impact mitigation. A biodiversity action plan that incorporated the mitigation hierarchy and a science-based biodiversity monitoring and assessment program contributed to biodiversity management of the project and played an important role in minimizing and managing impacts.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

浮游动物DNA宏条形码多样性监测采样方法研究

浮游动物是水生生态系统的重要组成部分,对环境因子敏感,是水生生态健康状况的重要指示生物.基于传统形态学的浮游动物调查方法无法鉴定桡足类幼体,难以准确了解浮游动物群落组成.DNA宏条形码技术基于DNA序列差异识别物种,为浮游动物群落组成的准确解析提供了新方法.比较了不同浮游动物采样方法(直接过滤法和网富集法)对浮游动物D...     

Theoretical and practical criteria for the selection of ecosystem monitoring plots in Swiss forests

A great deal of attention has been paid to the selection of nature reserves. These are important from a conservation viewpoint but, for long-term evaluations, it is important to monitor ecosystems. The need for long-term monitoring plots has been recognized for some time in forest ecology. Of the natural ecosystems, forests are some of the most difficult to monitor because of the time-scales involved in the life-spans of the dominant organisms (100 1000 years). The selection of long-term forest ecosystem monitoring plots is a critical process involving decisions that need to remain valid for many years. Traditional sampling theory suggests that some form of systematic or random sampling may be appropriate, but this is usually inappropriate for the selection of ecosystem monitoring plots. Instead, the selection of plots more closely resembles some of the procedures that are used in the selection of nature reserves. In Switzerland, a monitoring programme has been established which uses a number of criteria for the selection of sites. These include site homogeneity, the abundance and sensitivity of the plant communities to change and the presence of pre-existing data series or monitoring equipment. In addition, the human factor is incorporated by selecting sites from throughout the country, with the willingness of the local forest managers to help with the project being an important factor influencing the final choice of plots. In contrast to most inventories, statistical representativeness is not a requirement for the programme, as the plots are treated as a series of case studies.     

Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.