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This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

This study aims to illustrate how collaborative platforms may leverage active community for climate change adaptation to implement biodiversity preservation policies.

This study adopts the Dynamic Performance Governance methodological framework to analyze the causal relationships affecting biodiversity preservation policy outcomes.

Active community reduces harmful factors for biodiversity (i.e. biological threats and anthropogenic pressure), limiting the risk of extinction of perennial plants. Stakeholders’ prior knowledge is an enabling condition of climate adaptation processes as it triggers the adoption of prescriptions and cultural changes in a community.

The study provides methodological guidance to define measures to deliver material information to support environmental performance governance. It elaborates an inventory of short- and long-term performance indicators integrating natural-science targets into accounting measures that can support policymakers operating in other contexts to implement climate change adaptation policies.

As a response to the study findings, social implications provide insights into how active community in collaborative platforms for climate change may support stakeholders to address natural resources imbalances, define strategies to share the burden among them and intervene on multiple policy domains (e.g. financial, environmental and social).

Climate change adaptation challenges are conceptualized as “super wicked problems,” and the collaborative platforms designed to address them are rendered as complex adaptive systems. This makes the paper go beyond traditional environmental governance, demonstrating that stakeholders’ interactions within collaborative platforms harness active community specialized knowledge.

This paper aims to explore how environmental employment can promote desistance among criminalised children. Research demonstrates that being immersed in and interacting with the natural environment has a positive impact upon well-being and behaviour, including reduced aggressive and violent behaviours. However, how exposure to the natural environment might promote desistance amongst children with persistent criminal involvement is unclear.

This paper examines, through semi-structured interviews and participant observations, the experiences of n = 23 criminalised children aged 16–18 employed in outdoor work at a UK social enterprise.

The findings demonstrate how working in the natural environment can provide a safe space for children, where they can build positive relationships, learn valuable skills and reconnect with the world outside of the high-pressure, conflict-driven spaces in which they typically occupy.

This research highlights the relevance of the setting in which child rehabilitation takes place and the potential role of natural environments in providing places and opportunities which support pro-social identity development and desistance for children.

The purpose of this paper is to investigate the impact of near-wall treatment approaches, which are crucial parameters in predicting the flow characteristics of open channels, and the influence of different vegetation covers in different layers.

Ansys Fluent, a computational fluid dynamics software, was used to calculate the flow and turbulence characteristics using a three-dimensional, turbulent (k-e realizable), incompressible and steady-flow assumption, along with various near-wall treatment approaches (standard, scalable, non-equilibrium and enhanced) in the vegetated channel. The numerical study was validated concerning an experimental study conducted in the existing literature.

The numerical model successfully predicted experimental results with relative error rates below 10%. It was determined that nonequilibrium wall functions exhibited the highest predictive success in experiment Run 1, standard wall functions in experiment Run 2 and enhanced wall treatments in experiment Run 3. This study has found that plant growth significantly alters open channel flow. In the contact zones, the velocities and the eddy viscosity are low, while in the free zones they are high. On the other hand, the turbulence kinetic energy and turbulence eddy dissipation are maximum at the solid–liquid interface, while they are minimum at free zones.

This is the first study, to the best of the author’s knowledge, concerning the performance of different near-wall treatment approaches on the prediction of vegetation-covered open channel flow characteristics. And this study provides valuable insights to improve the hydraulic performance of open-channel systems.

Population growth and urbanization pose several threats to terrestrial ecosystems, especially in forest ecological zones worldwide. This study examines the drivers of average willingness to pay (WTP) to restore urban forests in a developing country.

It utilizes survey data of households and employs a robust Heckman two-step estimator with bootstrapping to address the research objective.

The study underscores the role of income, gender, education and perception of the health benefits of forests as the underlying determinants of restoration bids by respondents. These drivers have a positive and statistically significant effect on forest restoration. Education and gender appear to be the most effective by magnitude, followed by the perception of health benefits, then income. Attention is therefore drawn to relevant economic, sociocultural and psychological factors towards the goal of forestry to improve well-being in urban centres.

This paper seeks to add methodological insights to the literature on reforestation and land use changes in the Accra metropolitan area and the local population’s WTP for reforestation in this area. In principle, this is a case study informing about the values people hold for forests in Ghana and Africa, where a knowledge gap exists with respect to their socio-economic valuation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0618

In order to mitigate the effects of climate change, the UK government has set a target of achieving net zero greenhouse gas (GHG) emissions by 2050. Agricultural GHG emissions in 2017 were 45.6 million tonnes of carbon dioxide equivalent (CO₂e; 10% of UK total GHG emissions). Farmland hedgerows are a carbon sink, storing carbon in the vegetation and soils beneath them, and thus increasing hedgerow length by 40% has been proposed in the UK to help meet net zero targets. However, the full impact of this expansion on farm biodiversity is yet to be evaluated in a net zero context. This paper critically synthesises the literature on the biodiversity implications of hedgerow planting and management on arable farms in the UK as a rapid review with policy recommendations. Eight peer-reviewed articles were reviewed, with the overall scientific evidence suggesting a positive influence of hedgerow management on farmland biodiversity, particularly coppicing and hedgelaying, although other boundary features, e.g. field margins and green lanes, may be additive to net zero hedgerow policy as they often supported higher abundances and richness of species. Only one paper found hedgerow age effects on biodiversity, with no significant effects found. Key policy implications are that further research is required, particularly on the effect of hedgerow age on biodiversity, as well as mammalian and avian responses to hedgerow planting and management, in order to fully evaluate hedgerow expansion impacts on biodiversity.

Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.

This chapter compares the current biodiversity practices of higher education institutions (HEIs) and their learning effects of the Global North and South. It particularly explores the HEIs’ strategies targeting biodiversity and ecosystem services preservation. In order to answer the research question, a qualitative content analysis of published sustainability reports of the systematically selected HEIs was performed. The Times Higher Education (THE) was used to select HEIs. The results show that biodiversity reporting and management is still in its early stages in HEIs from both the Global North and South and could benefit from further research and suggestions for improvement. One implication for the HEIs is that they could increase public awareness and knowledge of biodiversity through the integration of this topic into their curricula, more research projects on biodiversity, and operations on and off campus.

With rapid urbanization, cities are facing various ecological and environmental problems. Living in harmony with nature is more important than ever. This paper aims to evaluate the ecosystem and ecological features of Azheke village, a key component of the Hani Rice Terraces World Cultural Heritage in China. The focus is on exploring effective ways to improve the relationship between humans and the natural environment through urban design in order to create a livable and sustainable city that can promote the development of sustainable smart urban ecology design.

This study conducted a systematic literature review to answer the following research questions: (1) How does Azheke design achieve harmony between humans and nature? (2) What are the effective approaches to improve the relationship between humans and nature within urban ecosystems? (3) How can urban design learn and integrate from Azheke’s ecological features to improve the relationship between humans and nature?

Azheke sustains long-term human-nature harmony through traditional ecological knowledge (TEK) and efficient natural resource use. By incorporating biophilic design and nature-based solutions from Azheke, along with biodiversity-friendly urban planning, we can boost urban ecosystem health and create unique Azheke-inspired urban designs.

This research primarily focuses on the human-nature relationship, exploring design strategies based on biodiversity without delving into the interactions between other components of urban ecosystems, such as social-cultural and economic components.

This paper provides a new perspective and strategies for developing sustainable and smart urban ecology design. These findings can provide theoretical references for urban planners, designers and decision-makers.

This study aims to examine whether there exists any relationship between corporate biodiversity reporting decision (CBRD) and corporate environmental performance (CEP).

The primary sample contains 442 firm-year observations over a period of 13 years (2008–2020) for 34 listed Finnish companies. Based on both legitimacy theory and voluntary disclosure theory, 2 logit regression models are estimated to test the CBRD–CEP nexus. CBRD is a dichotomous variable. Three proxies for CEP, namely propensity to emit greenhouse gas (GHG), propensity to consume water and propensity to generate waste are employed.

This study finds that firms having higher propensity to consume water and generate waste are inclined to release biodiversity-related information. The findings support legitimacy theory suggesting that firms with inferior environmental performance may decide on reporting biodiversity information for legitimation purpose.

The study uses Finnish data and hence, the results may lack in generalizability to other national contexts.

The results of this study should be valuable to policy makers for formulating mandatory biodiversity reporting standards to ensure disclosure of standard, extensive and authentic biodiversity-related information by companies. The results should also be valuable to corporate managers and eco-friendly investors.

Corporate biodiversity reporting (CBR) is an under-researched area of environmental accounting literature. Using the Finnish context, this paper extends the existing literature by investigating whether any association exists between CBRD and CEP, which has not been examined before.