Environmental Management

A series of computer programs designed to predict gross annual soil loss on a watershed basis by application of the Universal Soil Loss Equation (USLE) have been developed. The programs provide an easy-to-use, flexible, and standardized means of organizing base data and applying the USLE to large land areas. The programs can be used to assess and to evaluate the effects of changing land-use patterns and conservation practices on soil losses. Critical or problem areas can be readily identified. The USLE Computer Programs are a useful research tool for investigators involved in water quality management, 208 planning, or conservation research. The package of computer programs consists of three main components: data input, the Main Program, and the Totals Program. Input data include both field base data describing the watershed and corresponding values for the factors in the USLE. The Main Program calculates the average rate of soil loss (tons/ acre/yr) and the total soil loss (tons/yr) for the smallest subunit of the watershed identified as the soil unit. Also calculated is an RKLS factor, which is an indication of the erosive potential of a given soil type, slope, and slope length, under a particular rainfall regime. The Totals Program aggregates soil unit losses into progressively larger units, that is, field, farm, subwatershed, and watershed units. An example of the programs' versatility and use is presented.

Local application of the biosphere reserve concept in Kien Giang, Vietnam was examined to see how it compared with other biosphere reserves both in Vietnam and internationally and from that to assess the level of adoption and what could be limiting processes. This was undertaken mainly through qualitative document analysis, field surveys, and extensive interviews of stakeholders. While the designation the Kien Giang Biosphere Reserve and establishment of the management regulation conformed with the conceptual model and criteria outlined by UNESCO, the practical implementation has been inadequate to achieve the desired outcomes of the biosphere reserve concept. There was limited public awareness and understanding of the biosphere reserve approach because of poorly developed communication channels. Top-down, state-control based on a strong sectoral approach to biosphere reserve planning and management hindered stakeholder and community participation. Weak engagement from the Province as the designated lead agency in biosphere reserve governance limited cross-sectoral collaboration in the delivery of the biosphere reserve mandated functions. External projects were perceived by community stakeholders to have only a temporary impact on biosphere reserve operation because of their small, short-term scale with the project maintaining control over funding and design of individual activities. Without proper investment in public awareness and improvement of Biosphere Reserve governance leadership, the desire for development of strategic public–private partnerships to support implementation remains unfulfilled and the Biosphere Reserve model will, as a consequence, contribute little to the long-term biodiversity conservation and socio-economic development in the region.

A critical step to design wildlife mitigating measures is the identification of roadkill hotspots. However, the effectiveness of mitigations based on roadkill hotspots depends on whether spatial aggregations are recurrent over time, spatially restricted, and most importantly, shared by species with diverse ecological and functional characteristics. We used a functional group approach to map roadkill hotspots for mammalian species along the BR-101/North RJ, a major road crossing important remnants of the Brazilian Atlantic Forest. We tested if functional groups present distinct hotspot patterns, and if they converge into the same road sectors, in that case, favoring optimal mitigating actions. Roadkill rates were monitored and recorded between October/2014 and September/2018 and species were classified into six functional groups based on their home range, body size, locomotion mode, diet, and forest-dependency. Hotspots along the roads were mapped for comparison of spatial patterns between functional groups. Results demonstrated that the roadkill index varied idiosyncratically for each functional group throughout the months and that no group presented seasonality. Seven hotspots were shared by two or more functional groups, highlighting the importance of these road stretches to regional mammal fauna. Two of the stretches are associated with aquatic areas extending from one side of the road to the other, and the remaining are connected to patches of native vegetation on both sides. This work brings a promising approach, yet hardly used in ecological studies on roads to analyze roadkill dynamics, assigning more importance to ecological instead of taxonomical characteristics, normally used to identify spatiotemporal patterns.

Spatial variation in the landscape factors climate, geomorphology, and lithology cause significant differences in water quality issues even when land use pressures are similar. The Physiographic Environment Classification (PEC) classifies landscapes based on their susceptibility to the loss of water quality contaminants. The classification is informed by a conceptual model of the landscape factors that control the hydrochemical maturity of water discharged to streams. In New Zealand, a case study using climatic, topographic, and geological data classified the country into six, 36, and 320 classes at Levels 1 (Climate), 1–2 (Climate + Geomorphology), and 1–3 (Climate + Geomorphology + Lithology), respectively. Variance partitioning analysis applied to New Zealand’s national surface water monitoring network (n = 810 stations) assessed the contributions of PEC classes and land use on the spatial variation of water quality contaminants. Compared to land use, PEC explained 0.6× the variation in Nitrate Nitrite Nitrogen (NNN), 1.0× in Total Kjeldahl Nitrogen (TKN), 1.8× in Dissolved Reactive Phosphorus (DRP), 2.3× in Particulate Phosphorus (PP), 2.6× in E. coli, and 4.3× in Turbidity (TURB). Land use explained more variation in riverine NNN, while landscape factors explained more variation in DRP, PP, E. coli, and TURB. Overall, PEC accounted for 2.1× more variation in riverine contaminant concentrations than land use. The differences in contaminant concentrations between PEC classes (p < 0.05), after adjusting for land use, were consistent with the conceptual model of hydrochemical maturation. PEC elucidates underlying causes of contaminant loss susceptibility and can inform targeted land management across multiple scales.

Social media are being increasingly used to inform visitor use management in parks and protected areas. We review the state of the scientific literature to understand the ways social media has been, and can be, used to measure visitation, spatial patterns of use, and visitors’ experiences in parks and protected areas. Geotagged social media are a good proxy for actual visitation; however, the correlations observed by previous studies between social media and other sources of visitation data vary substantially. Most studies using social media to measure visitation aggregate data across many years, with very few testing the use of social media as a visitation proxy at smaller temporal scales. No studies have tested the use of social media to estimate visitation in near real-time. Studies have used geotags and GPS tracks to understand spatial patterns of where visitors travel within parks, and how that may relate to other variables (e.g., infrastructure), or differ by visitor type. Researchers have also found the text content, photograph content, and geotags from social media posts useful to understand aspects of visitors’ experiences, such as behaviors, preferences, and sentiment. The most cited concern with using social media is that this data may not be representative of all park users. Collectively, this body of research demonstrates a broad range of applications for social media. We synthesize our findings by identifying gaps and opportunities for future research and presenting a set of best practices for using social media in parks and protected areas.

In the age of climate change, the demand and lack of pure water challenges many communities. Substantial amount of effort is put in every year to manage and restore degraded lakes while the long-term effects of those efforts are only poorly known or monitored. Oxygenation, or aeration, is used extensively for the restoration of eutrophic lakes, although many studies question whether this process improves the status of the lakes in the long-term. The desired effect of oxygenation is based on paradigmatic theories that, in the light of recent literature, might not be adequate when long-term improvements are sought. This article canvasses expert views on the feasibility of the ‘oxygen–phosphorus paradigm’ as well as the future of the management and restoration of eutrophic lakes, based on an international, two-rounded, expert panel survey (Delphi study), employing 200 freshwater experts from 33 nationalities, contacted at three conferences on the topic. The conclusion is that the oxygen-phosphorus paradigm seems to be rather persistent. The experts considered oxygenation to be a valid short-term lake restoration method, but not without harmful side-effects. In addition, experts’ low level of trust in the adequacy of the scientific knowledge on the effects of restorations and in the use of the scientific knowledge as a basis of choice of restoration methods, could be signs of a paradigm shift towards an outlook emphasizing more effective catchment management over short-term restorations. The expert panel also anticipated that reducing external nutrient loads from both point and diffuse sources will succeed in the future.

Soil heavy metal pollution threatens ecological health and food security. It is significant to classify pollution risk management and control zones, which can effectively cope with soil pollution and scientifically carry out soil remediation projects. In this study, based on 665 soil samples collecting from Ningbo (southeast China), single pollution index and Nemerow composite pollution index (NCPI) were measured to assess soil pollution risk, and self-organization mapping model was applied to classify management and control zones. Results showed that the heavy metal pollution in the northwest part was more serious, while the east part was less polluted. Although more than 75% soil samples had negligible risks, the Hg and Cu pollution was greatly influential and notable as their polluted samples accounted for 24.21% and 12.48% respectively. Moreover, about 55.34% soil samples and more than half study region had pollution grades, and NCPI values were obviously high with the center of northwest study area. Results also showed that the study region could be classified into four zones with good spatial variabilities. Specifically, Monitored Zone with High-risk Pollution had the highest NCPI caused by human activities, while Controlled Zone with Severe Pollution had relatively high NCPI caused by industrial and agricultural production. Protected Zone with Ecological Conservation and Restricted Zone with Potential Pollution had low NCPIs attributing to historical or natural factors. Our study implies that the classified zones can provide fundamental and momentous information for establishing appropriate priorities of heavy metal risk management and control.

The coastal waters at many beaches in California and the United States are afflicted with fecal pollution, which poses a health risk for people exposed to the water through recreational activities such as swimming, surfing, and diving. Identifying sources of pollution is complicated by oceanographic transport/mixing processes and the nonconservative behavior of microorganisms exposed to sunlight and hostile marine conditions. This article investigates the variation of fecal indicator bacteria (FIB) concentrations in the surf zone and the adjacent coastal marsh by applying autocorrelation and cross-correlation analyses that illustrate solar and tidal modulations. A steady state bioreactor model was developed to explain solar inactivation in the surf zone, whereas a dynamic model was applied to explain tidally influenced disturbances in the coastal marsh. These models applied to intensive monitoring datasets on FIB and environmental variables have provided insights into the biologic and physical processes controlling coastal water quality, specifically the influence of sunlight and tides on bacterial levels.