Environmental Management Decisions Research Articles

GIS Application in Environmental Management: A Review

The role of environmental management is extremely important in human life because of its contribution to environmental protection and strategies. In modern society, nevertheless, facing the challenges in land, water, and air quality management in reality is unavoidable. Understanding the information on variability and features of environmental issues is necessary to support decision-makers in establishing environmental management planning. Spatial information and data should be considered as basic initial knowledge of environmental management. Among various technologies, Geographic Information Systems (GIS) is known as one of the most popular tools to store, analyze, and visualize data relating to geographically referenced information which can mitigate these challenges more effectively and accurately. The main purpose of this paper is to emphasize how GIS applications in environmental management, discuss the challenges of GIS technology in environmental management, and provide recommendations for future research directions. Many articles over the last decades were reviewed to highlight the application of GIS in environmental management. These results indicated GIS applications support land, water, air quality, and waste management. Moreover, it is a useful tool to monitor and assess environmental quality and in environmental planning and decision-making. For the limitation of GIS application, it is obvious that accuracy assessment and sensitivity analysis should be noticed and assessed although GIS application may strongly support decision-making in environmental management. Emerging GIS technologies and tendencies could help address these challenges. In future, GIS should be integrated along with new technologies and different decision-making algorithms in further steps for developing and supporting spatial decision-support systems more efficiently.

Reconstructing migratory network nodes to improve environmental management and conservation decisions: A case study of the common quail Coturnix coturnix as a biosensor

Public health risks are related to environmental management practices, and are essential to the understanding of ecosystem dynamics. The expansion of urbanized areas affects migratory bird networks and can impact the population sizes of migratory species and, in parallel, increase the risk of diseases carried by migratory species spreading into urban areas. Taking the European population of the common quail as a case study, we reconstructed its migratory network between Europe and the Maghreb using quail recoveries from the Italian Bird Ringing Scheme. We showed that soils at the central European migratory node have been degraded through urbanization and reforestation, decreasing the number of successful migrations over this area. Conceptual models incorporating the One Health approach, natural and social capital, landscape infrastructure, and ecosystem services could explain the relationships between climate warming and extensively developed, intensively developed, and urbanized ecosystems. Failed migratory flights of quail over central Europe highlight not only the problems of infrastructure design and their impact on ecosystems services, but also on One Health parameters. The damage to migratory network nodes presents a global threat to biodiversity and can increase the spread of diseases. To address this challenge we propose: i) improvements in land quality; ii) transboundary migration monitoring programmes; and iii) management plans for migratory birds – the overall aim being to optimize infrastructures to improve the quality of human life. Lessons drawn from a better understanding of the migratory networks of quail in relation to different ecosystems provide useful tools to improve infrastructure management and political decision making processes.

Extraction of Rocky Desertification Information in the Karst Area Based on the Red-NIR-SWIR Spectral Feature Space

The complex topography, severe surface fragmentation and landscape heterogeneity of the karst region of southwest China make it extremely difficult to extract information on rocky desertification in the region. In order to overcome the disadvantages of the surface parameter-based feature space approach, which is difficult to construct and apply, this study uses the reflectance of Landsat 8 Operational Land Imager (OLI) in the red (Red), near-infrared (NIR) and shortwave infrared (SWIR) bands as the feature variables, and establishes a two-dimensional SWIR-NIR, Red-NIR and SWIR-Red reflectance spectral feature space. The three models of perpendicular rocky desertification index 1 (PRDI1), perpendicular rocky desertification index 2 (PRDI2) and perpendicular rocky desertification index 3 (PRDI3) were also constructed based on the variation of the degree of rocky desertification in each spectral feature space. The accuracy of the rocky desertification extracted by these three index models was verified and compared with the karst rocky desertification index (KRDI) and rocky desertification difference index (RSDDI), which are constructed based on the surface parameter feature space. The results show that: (1) The waveband reflectance-based feature space model provides a new method for large-scale rocky desertification information extraction, characterized by easy data acquisition, simple index calculation and good stability, and is conducive to the monitoring and quantitative analysis of rocky desertification in karst areas. (2) The overall accuracy and Kappa coefficient of PRDI1 are 0.829 and 0.784, respectively, both higher than other index models, showing the best applicability, accuracy and effectiveness in rocky desertification information extraction. (3) According to the results extracted from PRDI1, the total area of rocky desertification in Huaxi District of Guizhou province is 320.44 km2, with the more serious grades of rocky desertification, such as severe and moderate, mainly distributed in the southwestern, western and southeastern areas of Huaxi District. This study provides important information on the total area and spatial distribution of different degrees of rocky desertification in the study area, and these results can be used to support the local government’s ecological and environmental management decisions. The method proposed in this study is a scientific and necessary complement to the characteristic spatial methods based on different surface parameters, and can provide important methodological support for the rapid and efficient monitoring of karstic rocky desertification over large areas.

The cleaner the environment, the happier the people: Integrating a nationwide public survey and environmental quality monitoring data in South Korea

Environmental studies are eager to prove the contribution of environmental quality (EQ) to happiness, given the recent interest of society in life quality and human well-being. Despite advances in empirical studies testing the relationship between EQ and life satisfaction (LS) at a global, national, and local scale, there is no comprehensive analysis of EQ, satisfaction with the environment (SE), and LS using various EQ parameters. This study tests this relationship by implementing a 5-year public survey on awareness and attitudes towards the evnironment with nationwide air and water quality data. Ordered probit models proved that NO2, PM10, and the comprehensive air-quality index concentrations are related to satisfaction with air quality, combined with the impacts of respondents’ pro-environmental attitude, property, and size of the residential area, whereas SO2, O3, and CO concentrations were ineffective. Total phosphorous was the only water quality parameter significant to satisfaction with water. Structural equation modelling proved that LS was affected by objective EQ through both direct and indirect paths via SE. We estimated the marginal effects of EQ improvement on SE. Understanding the relationship between EQ, SE, and LS can support decision-making in environmental management and public health programmes at the individual to policy levels. This study provides an improved approach and observations on this topic.

Clean manufacturing structure and its impact on water quality: A case study of Northeast China

Manufacturing structures that emit high levels of pollution may put tremendous pressure on water environment. Although studies have explored the relationship between industrial structure and the environment across industries, few literatures discuss the relationship between the cleanliness of manufacturing structures and water quality on a macro scale. This paper presents an indicator of clean manufacturing structures based on a dataset of 43,112 valid enterprise cases, and a water quality indicator based on data from 558 cases of chemical oxygen demand. Taking Northeast China as the study area, spatio-temporal diversity and evolution were analysed, and the mechanism of the effect of clean manufacturing structures on water quality was investigated. The empirical results indicate a significant negative correlation between the cleanliness level of these structures and chemical oxygen demand concentration. Through spatial autocorrelation analysis, we found a significant negative correlation between the spatial distribution of clean manufacturing structures and that of water quality, especially in the central city linkage zone, the West Liao River Basin, and the Yalu River Basin in Northeast China. Improvement of water quality requires optimising the clean structure of manufacturing industries and reducing the proportion of regional high-pollution industries. In addition, spatial lag model results proved that per capita gross domestic product and population density are also significantly correlated with water quality. This study reveals how clean manufacturing structures affect water quality, and the findings can support decision-making in economic and environmental management at the macro scale.

How to establish detection limits for environmental microplastics analysis

Establishing analytical detection limits is crucial. Common methods to do so are suitable only for variables with continuous distributions. Because count data for microplastic particles is a discrete variable following the Poisson distribution, currently-used approaches for estimating the detection limit in microplastics analysis are inadequate. Here we evaluate detection limits with techniques for low-level discrete observations to develop proper approaches for estimating the minimum detectable amount (MDA) in microplastic particle analysis, using blank sample data from an interlaboratory calibration exercise for clean water (representing drinking water), dirty water (ambient water), sediment (porous media) and fish tissue (biotic tissues). Two MDAs are applicable: MDAA to evaluate analytical methods, estimated with replicate blank data; and MDAB for individual sample batches, calculated with a single blank count. For illustrative purposes, this dataset's overall MDAA values were 164 counts (clean water), 88 (dirty water), 192 (sediment), and 379 (tissue). MDA values should be reported on a laboratory-specific basis and for individual size fractions, as this provides more useful information about capabilities of individual laboratories. This is due to wide variation in blank levels, as noted by MDAB values (i.e., among different laboratories) from 14 to 158 (clean water), 9 to 86 (dirty water, 9 to 186 (sediment), and 9 to 247 (tissue). MDA values for fibers were considerably greater than for non-fibers, suggesting that separate MDA values should be reported. This study provides a guideline for estimation and application of microplastics MDA for more robust data to support research activities and environmental management decisions.

ОПЫТ СКРИНИНГОВЫХ ИССЛЕДОВАНИЙ “ЗДОРОВЬЯ” ЭКОСИСТЕМ МОРСКИХ И ПРЕСНОВОДНЫХ АКВАТОРИЙ НА ОСНОВЕ ОПЕРАТИВНОЙ ОЦЕНКИ СОСТОЯНИЯ ОБИТАЮЩИХ В НИХ ДВУСТВОРЧАТЫХ МОЛЛЮСКОВ МЕТОДОМ ФУНКЦИОНАЛЬНОЙ НАГРУЗКИ. ПРОБЛЕМЫ И ПЕРСПЕКТИВЫ РАЗВИТИЯ

The current state of the concept of the health of aquatic ecosystems and the main methods and technologies (mainly instrumental) for its assessment are briefly considered. The data obtained during the study of the health of ecosystems of several recreational areas of the Black Sea, the eastern part of the Gulf of Finland, several channels of the Volga delta are considered. An operational assessment of the health of ecosystems was carried out using innovative biomonitoring technology by testing the health of adult bivalve mollusks living in them by the functional load method based on the analysis of their heart rate, measured using the BioArgus bioelectronic fiber-optic system. It has been established that the functional state of mollusks can serve as an indicator of excess pollution of coastal waters by objects that discharge insufficiently treated domestic wastewater from their local treatment facilities, including household wastewater. It is concluded that, taking into account the rather high rapidity and ease of use, this technology can be effectively used to solve the problems of screening studies and early diagnostics of the state of aquatic ecosystems as well as serve as an information basis for developing regionally oriented, science-based environmental management decisions.

Does local Natural Capital Accounting deliver useful policy and management information? A case study of Dartmoor and Exmoor National Parks

Natural capital accounting provides a systematic framework through which to quantify the benefits of natural assets. National-scale applications have demonstrated the feasibility of developing such accounts and their value as a tool to support environmental policy and management decisions. Building on that success, there have been increasing calls for sub-national organisations (for example, protected area authorities and water companies) to develop their own natural capital accounts. As we document in this paper, recent efforts by local organisations in the UK to produce such accounts have tended to rely on a set of ‘standard practice’ methods, many borrowed directly from national natural capital accounting exercises. In this paper, we review those methods and apply them in producing natural capital accounts for two UK National Parks. Working with the National Park Authorities, we critically assess the usefulness of those accounts to inform local land management. On account of data gaps and significant sensitivity to methodological assumptions, our research shows that these local accounts are considered of limited practical use for land management decision making at a local scale. Through specific illustrative examples, we show that natural capital accounts for local decision-making can be improved through: the inclusion of fit-for-purpose data and valuation methods, the consideration of uncertainties, and the incorporation of ecological information and spatial aspects. We also highlight the need for the development of both standardised guidelines and readily-available tools to quantify and value ecosystem services.

The causal relationship between green finance and geopolitical risk: Implications for environmental management

This study investigates the time-varying causal relationship between geopolitical risk and green finance during the period of 1 March 2012–February 16, 2022. By using the novel time-varying causality testing framework, our findings shed light on the nexus between geopolitical risk and green finance in informing environmental management decisions. First, we find that time heterogeneity does exist in the causal relations between geopolitical risk and green finance. Second, geopolitical risk has a more prolonged impact on the volatility of green bonds and renewable energy than the return. Yet, geopolitical risk tends to influence the return of clean energy more persistently than volatility. Third, we observe that geopolitical risk has a more sustained impact on the return and volatility of renewable energy than clean energy. This might be due to the distinct nature of the production of clean energy and renewable energy, thereby providing implications for effective environmental management. Lastly, this paper demonstrates that the impact of geopolitical risk on the return of European clean energy has diminished since the onset of 2015. The volatility of the European clean energy sector is not affected by global geopolitical risk, underscoring the necessity of promoting the development of this sector to reduce the dependence on fossil fuels and enhance energy independence.

Risk assessment, spatial distribution, and source identification of heavy metals in surface soils in Zhijin County, Guizhou Province, China.

Zhijin County is a typical mineral resource-based city in Southwest China. The problem of heavy metals (HM) in the soil in Zhijin County must be considered during regional economic and ecological development. A total of 2436 soil samples (0‒20cm depth) were collected to analyze the soil pH, organic matter content, and HM spatial distribution and sources. The HM concentrations in the surface soil were found to be higher than the national surface soil background values. Absolute principal component sore-multivariate linear regression (APCS-MLR) showed that the HM sources in the surface soil of Zhijin County were industrial and agricultural activities (48.09%), natural sources (34.47%), and atmospheric deposition (17.43%); 65.53% of HM were produced by anthropogenic activities, which were mainly associated with the mineral industry. The impact of anthropogenic pollution decreased in the following order: paddy field (66.45%) > rainfed cropland (65.91%) > barren land (61.98%) > garden land (61.82%) > forest land (59.11%) > grassland (53.31%). The potential ecological risk of surface soil is moderate, while low-risk areas were mainly distributed in mountainous regions in the north, southwest, and east. The study emphasizes the source and risk assessment of HM in the surface soil of Zhijin County. The results can be used for environmental management planning, decision-making, and risk assessment.

A systemic environmental impact assessment on tourism in island and coastal ecosystems

Intense tourism is a common occurrence in environments with very attractive natural traits and that host important ecosystem services, such as islands and coastal environments. However, these activities can cause impacts and loss of ecosystem services, thus requiring assessments about tourism activities and how to manage their complexity. Thus, the objective of the present study was to carry out an environmental impact assessment based on ecosystems in two islands with strong tourist pressure in the state of Santa Catarina, Brazil. The islands analyzed were Anhatomirim and Campeche, and the methodology used was the ecosystem-based Survey of Environmental Aspects and Impacts (SEAI), carried out by means of structured technical visits following a bibliographic analysis of the study area. Results indicated that the analysis model constructed can contribute to decision-making in environmental management, as it enabled a clear and objective identification of the main aspects, environmental impacts, and ecosystem services that are somehow connected. Among the negative impacts observed, the most relevant were water pollution, impaired health of wild animals, loss of biodiversity, and the spread of Covid-19. In turn, the most prominent positive impact was the generation of employment and income. The demand for environmental education projects in the tourist system that involves the two islands is also highlighted. Thus, this investigation was shown to be useful for the identification of the main anthropic elements derived from tourism that affect these ecosystems.

Air-water interactions regulating water temperature of lakes: Direct observations (Agamon Hula, Israel) and analytical solutions

Air-water interactions regulate lake-water temperature by balancing the rate of change of water temperature (stored heat) with the incoming and outgoing heat fluxes, which are functions of water temperature and external forcing. Yet, there is a large knowledge gap in quantifying the thermoregulation of a lake, and especially managed lakes, which is hypothesized to be related to both external environmental forcing and management decisions on lake depth and water inflow. Here we explore the thermoregulation of a restored and managed Mediterranean lake (Agamon Hula, Israel), by direct measurements of all major heat fluxes. We interpret the results with a rigorous analysis of the thermoregulation equation, obtained by formulating the energy balance equation in terms of water temperature. The equation shows how water temperature of a lake shifts toward steady state, scaled by the lake’s response time. Where the steady-state temperature was reached, it was controlled by external environmental forcing and not by lake depth. Whereas the thermal response time to re-attain steady state, following an abrupt change in various environmental conditions, is controlled by water depth. The lake-temperature response to pre-defined oscillations of the environmental forcing showed that the amplitude of water temperature fluctuations and the time delay from steady-state are controlled by the ratio between the environmental forcing’s time period (diurnal, seasonal or other cycles) and the thermal response time of the lake. The summertime measured CO2 fluxes of Agamon Hula revealed the lake acts as a CO2 source to the atmosphere, overpassing similar water bodies from different climates.

High-resolution streamflow and weather data (2013–2019) for seven small coastal watersheds in the northeast Pacific coastal temperate rainforest, Canada

Abstract. Hydrometeorological observations of small watersheds of the northeast Pacific coastal temperate rainforest (NPCTR) of North America are important to understand land to ocean ecological connections and to provide the scientific basis for regional environmental management decisions. The Hakai Institute operates a densely networked and long-term hydrometeorological monitoring observatory that fills a spatial data gap in the remote and sparsely gauged outer coast of the NPCTR. Here we present the first 5 water years (October 2013–October 2019) of high-resolution streamflow and weather data from seven small (< 13 km2) coastal watersheds. Measuring rainfall and streamflow in remote and topographically complex rainforest environments is challenging; hence, advanced and novel automated measurement methods were used. These methods, specifically for streamflow measurement, allowed us to quantify uncertainty and identify key sources of error, which varied by gauging location. Average yearly rainfall was 3267 mm, resulting in 2317 mm of runoff and 0.1087 km3 of freshwater exports from all seven watersheds per year. However, rainfall and runoff were highly variable, depending on the location and elevation. The seven watersheds have rainfall-dominated (pluvial) streamflow regimes, streamflow responses are rapid, and most water exports are driven by high-intensity fall and winter storm events. The complete hourly and 5 min interval datasets can be accessed at https://doi.org/10.21966/J99C-9C14 (Korver et al., 2021), and accompanying watershed delineations with metrics can be found at https://doi.org/10.21966/1.15311 (Gonzalez Arriola et al., 2015).

Application of ABB in environmental management accounting: Incorporating MFCA into the budget process

Traditional management accounting methods are difficult to provide the necessary information for environmental economic management decisions. In response to the increasingly urgent need for decision-related information, a new branch of accounting, environmental management accounting, has emerged and is receiving increasing attention. Material Flow Cost Accounting (MFCA) is a useful tool for managing complex resource and waste streams. However, MFCA is mainly used for ex-post accounting and reporting and no efforts are made to use it for forecasting. In this study, we introduce MFCA method into the budgeting process of manufacturing firms, and thus construct an MFCA-ABB (Activity-Based Budget) model. This model is applied to JLC Company which is a fragrant liquor manufacturer in China, in order to forecast and plan for its resource consumption, positive product output, and negative product generation. Based on the forecasts of involved material flows, inefficiencies in the company’s liquor production process are identified; scenario analysis is then conducted to determine the optimal process and the technology adopted. The proposed MFCA-ABB model turns a pure operating budget into an environmental-economic budget, thus achieving both environmental and economic benefits for the company. Besides, this study makes an attempt to apply ABB in environmental management accounting, which suggests the possibility of applying the conventional management accounting tools, after modified, to the environmental-economic management of manufacturing firms in the future.

Geochemistry and Multiomics Data Differentiate Streams in Pennsylvania Based on Unconventional Oil and Gas Activity.

ABSTRACTUnconventional oil and gas (UOG) extraction is increasing exponentially around the world, as new technological advances have provided cost-effective methods to extract hard-to-reach hydrocarbons. While UOG has increased the energy output of some countries, past research indicates potential impacts in nearby stream ecosystems as measured by geochemical and microbial markers. Here, we utilized a robust data set that combines 16S rRNA gene amplicon sequencing (DNA), metatranscriptomics (RNA), geochemistry, and trace element analyses to establish the impact of UOG activity in 21 sites in northern Pennsylvania. These data were also used to design predictive machine learning models to determine the UOG impact on streams. We identified multiple biomarkers of UOG activity and contributors of antimicrobial resistance within the order Burkholderiales. Furthermore, we identified expressed antimicrobial resistance genes, land coverage, geochemistry, and specific microbes as strong predictors of UOG status. Of the predictive models constructed (n = 30), 15 had accuracies higher than expected by chance and area under the curve values above 0.70. The supervised random forest models with the highest accuracy were constructed with 16S rRNA gene profiles, metatranscriptomics active microbial composition, metatranscriptomics active antimicrobial resistance genes, land coverage, and geochemistry (n = 23). The models identified the most important features within those data sets for classifying UOG status. These findings identified specific shifts in gene presence and expression, as well as geochemical measures, that can be used to build robust models to identify impacts of UOG development.IMPORTANCE The environmental implications of unconventional oil and gas extraction are only recently starting to be systematically recorded. Our research shows the utility of microbial communities paired with geochemical markers to build strong predictive random forest models of unconventional oil and gas activity and the identification of key biomarkers. Microbial communities, their transcribed genes, and key biomarkers can be used as sentinels of environmental changes. Slight changes in microbial function and composition can be detected before chemical markers of contamination. Potential contamination, specifically from biocides, is especially concerning due to its potential to promote antibiotic resistance in the environment. Additionally, as microbial communities facilitate the bulk of nutrient cycling in the environment, small changes may have long-term repercussions. Supervised random forest models can be used to identify changes in those communities, greatly enhance our understanding of what such impacts entail, and inform environmental management decisions.

Impacts of natural and human factors on water-related ecosystem services in the Dongting Lake Basin

Correctly identifying and understanding the drivers of ecosystem change and their impacts on ecosystem services (ESs) could provide comprehensive supporting information for ecological governance decisions. This study aimed to identify the key drivers and influencers of natural and human factors on water-related ecosystem services (WESs) in three aspects: spatial heterogeneity contribution, driving relationships, and constraining relationships. The study area included the Dongting Lake Basin, which was divided into 2816 sub-basins as the spatial unit. The WESs of water production, soil conservation, and water purification (output nitrogen) from 2000 to 2020 were quantified, and the impact of environmental factors on WESs and ES enhancement potential were assessed. The results showed that: (1) From 2000 to 2020, the three WESs increased in varying degrees; water production, soil conservation, and nitrogen export increased by 27.60%, 43.20%, and 1.50%, respectively. (2) Precipitation (PRE), slope (Slope), and percentage of ecological land (ELP) were the dominant factors influencing the spatial heterogeneity pattern of water production, soil conservation, and nitrogen output, respectively; PRE, Slope, and ELP had evident nonlinear relationships with the WESs and displayed segmental regression relationship characteristics. (3) Natural and human factors had significant constraining effects on the WESs, even though the driving effects were not significant. (4) Potential measurement results that integrate the driving and limiting effects of factors showed significant heterogeneity, which allows for the screening of efficient ES enhancement measures and locating the implementation space. Therefore, comprehensively considering the effects of multiple drivers and obtaining a multilateral understanding of the impact of the driving factors on ESs will help refine and optimize environmental management decisions.

DETERMINANT DRIVERS FOR THE COMMUNITY STRUCTURE OF BENTHIC MACROINVERTEBRATES IN COASTAL LAGOONS AT THE RESTINGA DE JURUBATIBA NATIONAL PARK, IN THE STATE OF RIO DE JANEIRO STATE (BRAZIL)

This study aimed to characterize and evaluate factors driving the structure of the benthic macroinvertebrate community in coastal lagoons at the Restinga de Jurubatiba National Park. Sixteen lagoons were sampled in July 2010 during the dry season. At each lagoon, three samples were taken in the central region and three samples were taken near the sandbar. At each point, the limnological variables and the benthic community were collected. Richness and abundance were calculated for each sample. The correlations among the environmental parameters were tested using Pearson's correlation. A Principal Component Analysis using environmental variables was performed to visualize the similarity among samples. Simple regressions were used to assess the correlation between macroinvertebrates' metrics and environmental parameters. A redundancy test was performed to link environmental parameters to the community structure of macroinvertebrates. A total of 1,719 macroinvertebrates were identified in 25 taxa groups that were classified as exclusive marine taxa, five as brackish/marine taxa, seven as freshwater taxa, and two taxa as groups with marine and freshwater representatives. The most abundant taxa were Leonereis sp., Heleobia australis, and Kalliapseudidae. Richness and abundance were negatively related to salinity. The redundancy test indicated pH, salinity, coarse grain size, and dissolved oxygen as the environmental variables explaining the macroinvertebrate community structure variation among the lagoons. Understanding the drives and dynamics which guide the macroinvertebrates communities' turnover in coastal lagoons is a relevant tool to subsidize environmental management decisions due to the increasing threats around the park.

Downscaling Satellite Soil Moisture Using a Modular Spatial Inference Framework

Soil moisture is an important parameter that regulates multiple ecosystem processes and provides important information for environmental management and policy decision-making. Spaceborne sensors provide soil moisture information over large areas, but information is commonly available at coarse resolution with spatial and temporal gaps. Here, we present a modular spatial inference framework to downscale satellite-derived soil moisture using terrain parameters and test the performance of two modeling methods (Kernel-Weighted K-Nearest Neighbor <KKNN> and Random Forest <RF>). We generate monthly and weekly gap-free spatial predictions on soil moisture at 1 km using data from the European Space Agency Climate Change Initiative (ESA-CCI; version 6.1) over two regions in the conterminous United States. RF was the method that performed better in cross-validation when comparing with the reference ESA-CCI data, but KKNN showed a slightly higher agreement with ground-truth information as part of independent validation. We postulate that more heterogeneous landscapes (i.e., high topographic variation) may be more challenging for downscaling and predicting soil moisture; therefore, moisture networks should increase monitoring efforts across these complex landscapes. Future opportunities for development of modular cyberinfrastructure tools for downscaling satellite-derived soil moisture are discussed.

The ‘drive and talk’ as ethnographic method

Anthropologists have long embraced the value of the ‘walk and talk’ ethnographic method, which is an interactive means of generating research insights in situ – on site. In this article, we propose that there is room for an expanded appreciation of the ‘drive and talk’ method. While driving and talking with their interlocutors, researchers can elicit information prompted by features in the landscape and the environment that might be otherwise forgotten or overlooked if the interview context was set in a fixed location. To demonstrate the utility of this approach, this article explains the empirical and phenomenological (sensorial and experiential) insights yielded by driving and talking with interlocutors in a South Australian wine‐growing region. Automobility has the advantage over ambulation when it comes to accessing landscapes at the scale of the farm, which is where environmental management decisions are on heightened display.

Ecosystem services at risk in Italy from coastal inundation under extreme sea level scenarios up to 2050: A spatially resolved approach supporting climate change adaptation.

According to the latest projections of the Intergovernmental Panel on Climate Change, at the end of the century, coastal zones and low-lying ecosystems will be increasingly threatened by rising global mean sea levels. In order to support integrated coastal zone management and advance the basic "source-pathway-receptor-consequence" approach focused on traditional receptors (e.g., population, infrastructure, and economy), a novel risk framework is proposed able to evaluate potential risks of loss or degradation of ecosystem services (ESs) due to projected extreme sea level scenarios in the Italian coast. Three risk scenarios for the reference period (1969-2010) and future time frame up to 2050 under RCP4.5 and RCP8.5 are developed by integrating extreme water-level projections related to changing climate conditions, with vulnerability information about the topography, distance from coastlines, and presence of artificial protections. A risk assessment is then performed considering the potential effects of the spatial-temporal variability of inundations and land use on the supply level and spatial distribution of ESs. The results of the analysis are summarized into a spatially explicit risk index, useful to rank coastal areas more prone to ESs losses or degradation due to coastal inundation at the national scale. Overall, the Northern Adriatic coast is scored at high risk of ESs loss or degradation in the future scenario. Other small coastal strips with medium risk scores are the Eastern Puglia coast, Western Sardinia, and Tuscany's coast. The ESs Coastal Risk Index provides an easy-to-understand screening assessment that could support the prioritization of areas for coastal adaptation at the national scale. Moreover, this index allows the direct evaluation of the public value of ecosystems and supports more effective territorial planning and environmental management decisions. In particular, it could support the mainstreaming of ecosystem-based approaches (e.g., ecological engineering and green infrastructures) to mitigate the risks of climate change and extreme events while protecting ecosystems and biodiversity. Integr Environ Assess Manag 2022;18:1564-1577. © 2021 SETAC.