Policy-driven monitoring and evaluation: Does it support adaptive management of socio-ecological systems?

Strategies for integrating scientific evidence in water policy and law in the face of uncertainty

Understanding how human actions and environmental change affect water resources is crucial for addressing complex water management issues. The scientific tools that can produce the necessary information are ecological indicators, referring to measurable properties of the ecosystem state; environmental monitoring, the data collection process that is required to evaluate the progress towards reaching water management goals; mathematical models, linking human disturbances with the ecosystem state to predict environmental impacts; and scenarios, assisting in long-term management and policy implementation. Paradoxically, despite the rapid generation of data, evolving scientific understanding, and recent advancements in systems modeling, there is a striking imbalance between knowledge production and knowledge utilization in decision-making. In this paper, we examine the role and potential capacity of scientific tools in guiding governmental decision-making processes and identify the most critical disparities between water management, policy, law, and science. We demonstrate how the complex, uncertain, and gradually evolving nature of scientific knowledge might not always fit aptly to the legislative and policy processes and structures. We contend that the solution towards increased understanding of socio-ecological systems and reduced uncertainty lies in strengthening the connections between water management theory and practice, among the scientific tools themselves, among different stakeholders, and among the social, economic, and ecological facets of water quality management, law, and policy. We conclude by tying in three knowledge-exchange strategies, namely - adaptive management, Driver-Pressure-Status-Impact-Response (DPSIR) framework, and participatory modeling - that offer complementary perspectives to bridge the gap between science and policy.

Monitoring for the adaptive management of rivers

Monitoring for adaptive management (AM) involves collection of data with the aim of reducing uncertainty about links between human pressures (e.g. water abstraction from rivers), consequent stressors (e.g. low river flows) and environmental state (e.g. biodiversity). 'Surveillance monitoring' involves documenting trends in state, without the aim of understanding relationships between state, stressors, and pressures. Critics have highlighted that surveillance monitoring dominates monitoring investments but is not supporting AM. Decision-makers continue to be disappointed by monitoring data that are unsuitable for AM, yet designers of monitoring programs tend to make decisions that reinforce rather than reimagine the status quo. We argue that a structured, collaborative approach to objective-setting is required to break the status quo. We collaborated with regional management authorities to develop monitoring objectives and implementation strategies to support AM of New Zealand's rivers. Our collaborative approach discouraged 'failure fearing' and encouraged reimagining 'what could be' as opposed to 'what is.' Seventeen monitoring objectives were identified based on the AM requirements of national policy and regional authorities. Several objectives-particularly those arising from national policy-stretch the limits of what environmental science can currently provide. There were also strong trade-offs among objectives. We offer practical implementation strategies for overcoming the technical challenges of, and reducing trade-offs among, monitoring objectives. These strategies point to a monitoring program that contrasts strongly with one aimed at surveillance. Monitoring for AM is more complex than monitoring for surveillance, so strong leadership is required for successful implementation.

Spatial and temporal dynamics of habitat quality in response to socioeconomic and landscape patterns in the context of urbanization: A case in Zhengzhou City, China

With the rapid development of urbanization, the habitat quality (HQ) in urban areas has been eroded. This phenomenon is destroying the balance of ecosystems, triggering the reduction of biodiversity and the decay of ecosystem service functions. The study of the relationship between urbanization and HQ in Zhengzhou City is beneficial for the reference of sustainable urban ecological planning and management. Based on landscape classification data and socioeconomic data for three years, this study analyzes the spatial correlations between socioeconomic and landscape pattern factors and HQ, compares the dynamic changes in the explanatory power of different factors, and explores the joint effects between multiple factors. The results show that: (1) The overall value of HQ index in Zhengzhou City decreased by .10 during 2000–2020, mainly occurring in suburban areas, with a small amount of HQ improvement occurring in the core areas of ecological protection, such as mountains and river channels. (2) The spatial autocorrelation of all influencing factors with HQ increased during this period, while the negative impact from socio-economic sources was stronger than the positive impact from landscape patterns. (3) Intensive human activities lead to a single habitat type, which reduces HQ; rich landscape types and complex landscape composition can enhance HQ. Improving the connectivity of blue-green landscapes helps to attenuate the negative effects of urbanization on HQ. (4) Changes of HQ in the study area and the development of multi-factor effects on HQ are driven by the Zhengzhou Metropolitan Area Plan. Urban development policies and management can build idyllic complexes at the edge of urban development, preserving pristine blue-green patches to avoid their homogenized distribution and thus slowing the decline of HQ. The above results provide new ideas for the development of sustainable urban ecology.

An Integrated Landscape–Seascape Approach in the Making: Facilitating Multi-Stakeholder Partnership for Socio-Ecological Revitalisation in Eastern Coastal Taiwan (2016–2021)

Over the past decade, integrated landscape (–seascape) approaches—IL(S)As—have been gaining prominence as holistic, collaborative, and tangible solutions to biodiversity conservation and sustainability challenges. On-the-ground implementation of IL(S)As, however, is a complex task. The Xinshe “Forest–River–Village–Ocean” Eco-Agriculture Initiative (the Xinshe Initiative), established in October 2016 and facilitated by the authors, is an ILSA aimed at the socio-ecological revitalisation of the Xinshe ridge-to-reef landscape–seascape in eastern coastal Taiwan. The objective of this paper is to summarise and demonstrate our experiences with facilitating the Xinshe Initiative over the five-year period (2016–2021). This is a case study participatory action research based on mixed qualitative methods of data collection and analysis. Research findings reveal the importance of: (1) locally sensitive boundary setting and checking by the means of inclusive and participatory processes; (2) various facilitation tools and engagement strategies for the continuity of multi-stakeholder interest and engagement; (3) five socio-ecological perspectives of the Satoyama Initiative for determining environmental and socio-economic objectives; (4) regular, consistent, and locally sensitive monitoring and evaluation tools for the effectiveness of adaptive co-management; and (5) enabling conditions (relational, knowledge, and political resources) for promoting the Xinshe ILSA-related experiences “from -scape to scale”.

Understanding the effectiveness of policy instruments to encourage adoption of farming practices to improve water quality for the Great Barrier Reef

Governments in Australia and internationally are experimenting with policy instruments to facilitate the adoption of farming practices with reduced environmental impacts. The Great Barrier Reef (Australia) is one such case, where sustained efforts over 20 years have yielded insufficient progress towards targets to reduce the impacts of agriculture on water quality in downstream marine ecosystems. We present a critical review of policy instruments as implemented in Great Barrier Reef catchments. We catalogue the evolving mix of policy instruments employed in reef programs, and examine evidence of the effectiveness of agricultural extension, financial incentives, and direct regulation of farming practices. There is little robust evidence to assess instrument effectiveness, in part due to the evolving mix of the instruments employed, weak program evaluation and heterogeneity of agricultural enterprises. We identify the need to improve the understanding of instrument fit to landholders and enterprises. We recommend a modelling approach to clarify pathways to impact and guide improved policy evaluation.

What is the deal with the Green Deal: Will the new strategy help to improve European freshwater quality beyond the Water Framework Directive?

Agricultural land use covers almost half of the EU territory and reducing nutrient and pesticide losses to freshwaters is central to existing EU policy. However, the progress of improving freshwater quality and reducing eutrophication is slow and lags behind targets. The Green Deal is a key element of the EU plans to implement the United Nation's Sustainable Development Goals. Here, we discuss the opportunities that the Green Deal and associated strategies may provide for the achievement of the water quality goals of the Water Framework Directive in agricultural landscapes. We welcome Green Deal's aspirational stated goals. However, the reliance of mitigation of diffuse agricultural pollution on the reform of the Common Agricultural Policy represents grave risks for practical implementation and the achievement of the Green Deal objectives. We also argue that the new strategies should be targeted at tackling and understanding the sources of water quality problems along the full pollution continuum. To maximise the opportunities for tackling diffuse pollution from agricultural land use and achieving the delayed water quality targets, we stress that a range of targeted new instruments will be needed to close the gaps in the pollution continuum 'from source to impact'. These gaps include: (I) smart and standardised monitoring of the impacts of proposed eco-schemes and agri-environment-climate measures, (ii) active restoration of agricultural streams and ditches and their floodplains to reduce secondary pollution sources, (iii) options to draw down nutrient levels to or below the agronomic optimum that reduce legacy sources, (iv) integrating farm-scale and catchment-scale analysis of trade-offs in reducing different pollutants and their combined effects, and finally (v) accounting for emerging pressures to freshwater quality due to climate change. Incorporation of the pollution continuum framework into tackling diffuse agricultural pollution will ensure that the European water-related policy goals are achieved.

Cloud-Based Environmental Monitoring to Streamline Remote Sensing Analysis for Biologists

Timely, policy-relevant monitoring data are essential for evaluating the effectiveness of environmental policies and conservation measures. Satellite and aerial imagery can fill data gaps at low cost but are often underused for ongoing environmental monitoring. Barriers include a lack of expertise or computational resources and the lag time between image acquisition and information delivery. Online image repositories and cloud computing platforms are increasingly used by researchers because they offer near-real-time, centralized access to local-to-global-scale data sets and analytics with minimal in-house computational requirements. We aim to broaden knowledge of these open access resources for biologists whose work routinely informs policy and management. To illustrate potential applications of cloud-based environmental monitoring (CBEM), we developed an adaptable approach to detect changes in natural vegetative cover in an agricultural watershed. The steps we describe can be applied to identify opportunities and caveats for applying CBEM in a wide variety of monitoring programs.

Collaborations in Environmental Initiatives for an Effective “Adaptive Governance” of Social–Ecological Systems: What Existing Literature Suggests

Moving from the scientific literature on the evaluation of environmental projects and programs, this study identifies how and under which conditions collaborations in environmentally sustainable projects are considered effective for the adaptive governance of SES. The method adopted is a systematic literature review based on the quantitative and qualitative analysis of 56 articles selected through specific queries on the SCOPUS database and published from 2004 to 2020. Results of the quantitative analysis identify conditions able to evaluate collaborations, highlighting the need to adopt a transdisciplinary approach analysing both social and ecological challenges and assessing both social and ecological results. Moreover, they suggest preferring using primary data involving multi-sector and multi-scale actors and enlarging the geographical context to the most vulnerable countries. The results of the qualitative analysis provide specific recommendations for collaborations being effective when related to communication, equity, foresight, and respect, which need to be further strengthened by all actors. Multiplicity in visions and approaches should be seen as a resource able to stimulate creativity in social arrangements and environmental practices, making collaborations in environmental projects instrumental for the effectiveness of adaptive governance of SES.

Impact of Regional Green Development Strategy on Environmental Total Factor Productivity: Evidence from the Yangtze River Economic Belt, China

Chinese government policy officially identify the Yangtze River Economic Belt (YREB) as one of regional green development strategies firstly in 2014. This strategy can be regarded as quasi-natural experiment, this paper aims to test its impact on regional environmental total factor productivity (TFP). First, slack-based measure model is used to calculate the environmental TFP from 2005 to 2017 at provincial level. Second, based on Chinese official statistics, differences-in-differences (DID) method is applied to construct an evaluation model of policy effect, combining with the kernel matching in propensity score matching (PSM) method. The results show that environmental TFP of YREB has significant spatial differences, with characteristic of high-east and low-west, its average level is 11.69 percentage points higher than the national average. YREB strategy promotes regional economic growth, but it does no effect on the regional environmental TFP yet. Modelling suggests that YREB strategy may play a role in the short term. From the significance of the control variables, infrastructure construction level is positively correlated with environmental TFP, while per capita GDP, financial development and energy consumption intensity have negative effect on environmental TFP. Based on this, policymakers should focus on green development, promoting industrial transformation, and enhancing environmental protection.

Air quality during the COVID-19: PM2.5 analysis in the 50 most polluted capital cities in the world

On December 31, 2019, the Chinese authorities reported to the World Health Organization (WHO) the outbreak of a new strain of coronavirus that causes a serious disease in the city of Wuhan, China. This outbreak was classified as SARS-CoV2 and is the cause of the COVID-19 disease. On March 11, 2020, the WHO declares it a Pandemic and today it is considered the greatest challenge in global health that humanity has faced since World War II and it is estimated that between 40 and 60% of the population worldwide will catch the virus. This has caused enormous challenges in countries around the world in social, economic, environmental and obviously health issues. These challenges are mainly due to the effects of the established quarantines in almost all capitals and major cities around the world, from Asia, Europe to America. However, these lockdown which began worldwide from January 23, have had a significant impact on the environment and on the air quality of cities as recently reported by NASA (National Aeronautics and Space Administration) and ESA (European Space Agency), with reductions according to them of up to 30% in some of the epicenters such as the case of Wuhan. Knowing that air pollution causes approximately 29% of lung cancer deaths, 43% of COPD deaths, and 25% of ischemic heart disease deaths, it is important to know the effects of quarantines in cities regarding air quality to take measures that favor populations and urban ecosystems when the emergency ends. Therefore, this paper describes the behavior of PM_2.5 emissions particulate matter from the 50 most polluted capital cities in the world according to the WHO, measured before-after the start of the quarantine. Likewise, the impact at the local and global level of this emissions behavior, which averaged 12% of PM_2.5 decrease in these cities.

Air quality during the COVID-19: PM2.5 analysis in the 50 most polluted capital cities in the world

On December 31, 2019, the Chinese authorities reported to the World Health Organization (WHO) the outbreak of a new strain of coronavirus that causes a serious disease in the city of Wuhan, China. This outbreak was classified as SARS-CoV2 and is the cause of the COVID-19 disease. On March 11, 2020, the WHO declares it a Pandemic and today it is considered the greatest challenge in global health that humanity has faced since World War II and it is estimated that between 40 and 60% of the population worldwide will catch the virus. This has caused enormous challenges in countries around the world in social, economic, environmental and obviously health issues. These challenges are mainly due to the effects of the established quarantines in almost all capitals and major cities around the world, from Asia, Europe to America. However, these lockdown which began worldwide from January 23, have had a significant impact on the environment and on the air quality of cities as recently reported by NASA (National Aeronautics and Space Administration) and ESA (European Space Agency), with reductions according to them of up to 30% in some of the epicenters such as the case of Wuhan. Knowing that air pollution causes approximately 29% of lung cancer deaths, 43% of COPD deaths, and 25% of ischemic heart disease deaths, it is important to know the effects of quarantines in cities regarding air quality to take measures that favor populations and urban ecosystems when the emergency ends. Therefore, this paper describes the behavior of PM_2.5 emissions particulate matter from the 50 most polluted capital cities in the world according to the WHO, measured before-after the start of the quarantine. Likewise, the impact at the local and global level of this emissions behavior, which averaged 12% of PM_2.5 decrease in these cities.

Advances in forecasting harmful algal blooms using machine learning models: A case study with Planktothrix rubescens in Lake Geneva

The development of anthropic activities during the 20th century increased the nutrient fluxes in freshwater ecosystems, leading to the eutrophication phenomenon that most often promotes harmful algal blooms (HABs). Recent years have witnessed the regular and massive development of some filamentous algae or cyanobacteria in Lake Geneva. Consequently, important blooms could result in detrimental impacts on economic issues and human health. In this study, we tried to lay the foundation of an HAB forecast model to help scientists and local stakeholders with the present and future management of this peri-alpine lake. Our forecast strategy was based on pairing two machine learning models with a long-term database built over the past 34 years. We created HAB groups via a K-means model. Then, we introduced different lag times in the input of a random forest (RF) model, using a sliding window. Finally, we used a high-frequency dataset to compare the natural mechanisms with numerical interaction using individual conditional expectation plots. We demonstrate that some HAB events can be forecasted over a year scale. The information contained in the concentration data of the cyanobacteria was synthesized in the form of four intensity groups that directly depend on the P. rubescens concentration. The categorical transformation of these data allowed us to obtain a forecast with correlation coefficients that stayed above a threshold of 0.5 until one year for the counting cells and two years for the biovolume data. Moreover, we found that the RF model predicted the best P. rubescens abundance for water temperatures around 14°C. This result is consistent with the biological processes of the toxic cyanobacterium. In this study, we found that the coupling between K-means and RF models could help in forecasting the development of the bloom-forming P. rubescens in Lake Geneva. This methodology could create a numerical decision support tool, which should be a significant advantage for lake managers.

A New Model-Based Approach for the Evaluation of the Net Contribution of the European Union Rural Development Program to the Reduction of Water Abstractions in Agriculture

Agriculture is an essential driving force in water resources management and has a central role in the European Union’s Rural Development Programme (RDP). In this study, the solution developed addresses countries characterised by relatively small farms, vast spatial and temporal variability and severe data scarcity. The proposed model-based approach is directly relevant to the evaluation of agricultural policies affecting water abstraction based on multisource data. The evaluation process utilises an entirely spatially distributed, continuous hydrological model. The model provides a gridded output of the main hydrological balance components, as well as vegetation water deficit and irrigation water requirements, on a daily temporal step on a country scale. It provides information at the farm level and facilitates the estimation of water abstractions in agriculture, taking into consideration all the pertinent information included in the Integrated Administration and Control System database that is maintained by RDPs in Europe. Remote sensing data also are used to validate crop patterns. The obtained results were analysed to estimate the net effect of the RDP to the reduction of water abstractions in agriculture. This work produces valuable information concerning the evaluation of agricultural policies and the assessment of land use, and climate change adaptation and mitigation strategies.

The state of water quality strategies in the Mississippi River Basin: Is cooperative federalism working?

There is consensus that the Clean Water Act (CWA) has generally been effective in addressing point source pollution in the US. There is also consensus that non-point source (NPS) pollution, particularly from agriculture, remains a problem. The potential for the CWA framework to affect change is unclear, due to the limited power of the US federal government in addressing NPS, the contentiousness surrounding it, and the lack of funding to implement plans that have been developed. States are critical in improving water quality in the U.S. In the Mississippi River Basin, State-level Nutrient Reduction Strategies are the vehicle chosen by the Environmental Protection Agency to improve water quality. We develop an assessment of the twelve Mississippi River states' strategies. We consider three issues: whether there is science-based support for a choice, with a focus on NPS; if and how updates on progress are available; and whether there is alignment of funding and abatement priorities. We find that the use of best science is limited, the role of livestock in pollution and its abatement is ignored, and the development of Numeric Nutrient Criteria is stalled. Further, several states have not reported on their progress, and there has been little additional funding for pollution reduction. This analysis can inform broader discussions on decentralized approaches to address water quality.

Data summarizing monitoring and evaluation for three European environmental policies in 9 cases across Europe

The data presented in this DiB article provide an overview of Monitoring and Evaluation (M&E) carried out for 3 European environmental policies (the Water Framework Directive, the Natura 2000 network of protected areas, and Agri-Environment Schemes implemented under the Common Agricultural Policy), as implemented in 9 cases (Catalonia (Spain), Estonia, Finland, Flanders (Belgium), Hungary, Romania, Slovakia, Scotland (UK), Sweden). These data are derived from reports and documents about monitoring programs that were publicly-available online in 2017. The literature on M&E to support adaptive management structured the issues that have been extracted and summarized. The data is related to the research article entitled “Policy-driven monitoring and evaluation: does it support adaptive management of socio-ecological systems?” [Stem et al., 2005]. The information provides a first overview of monitoring and evaluation that has been implemented in response to key European environmental policies. It provides a structured overview that permits a comparison of cases and policies and can assist other scholars and practitioners working on monitoring and evaluation.

New Strategies to Improve Co-Management in Enclosed Coastal Seas and Wetlands Subjected to Complex Environments: Socio-Economic Analysis Applied to an International Recovery Success Case Study after an Environmental Crisis

Enclosed coastal seas and wetlands are areas of high ecological value with singular fauna and flora, but several cases of environmental catastrophes in recent decades can easily be referenced in the international literature. The management of these natural territories is complex in developed countries since they are usually subjected to intense human activity with a varied catalog of activities and anthropizing features that alter the balance of the ecosystem. In this article, the concept of the Socio-Ecological System (SES) to diagnose and achieve a sustainable cohabitation between human anthropization and the natural values based on the tool of GIS participatory mapping is proposed as an innovative approach for the management and recovery of these complex areas. The article develops a comprehensive general methodology of spatial GIS diagnosis, planning, and co-management implementation between public and private stakeholders combined with economic tools such as the Willingness to Pay (WTP) and the Cost Transfer Sector (CTS). This innovative approach is applied to the Mar Menor lagoon, which is an international and successful case study of environmental recovery on the Spanish Mediterranean coast. The coastal lagoon suffered an unprecedented eutrophication crisis in 2015, but it managed to recover in the summer of 2018 without the need to implement major structural measures. In this case study, several solutions to redress the current impacts will be developed through a participatory process based on GIS mapping. Lastly, the discussion reflects the concept of self-resilience of an ecosystem based on the unexpected positive turn of the environmental crisis in the lagoon ending.