Francesco Gonella’s research while affiliated with Ca' Foscari University of Venice and other places

Like many Mediterranean areas, the Italian island of Sicily faces multiple environmental pressures such as soil loss, fire hazards, and extreme meteorological events, all of which negatively impact local food systems. In response to these threats, a re-thinking of local agriculture and natural resource management is increasingly needed. Agroecology is recognized as a robust proposal for building more resilient food systems grounded in farmers’ knowledge and practices. However, agroecological farming experiences struggle to operate and survive in Sicily due to unfavorable political-cultural, environmental, and socio-economic conditions. Learning from small-scale farmers about the ways they perceive, understand, and overcome structural limits and environmental constraints is key for a transition to agroecology in the study area. Understanding its potentials and limits is essential for planning and identifying transformative actions. We approached the problem by adopting a participatory action research methodology involving selected groups of farmers in Western Sicily. We applied a co-creative approach and developed a systemic analysis of the socio-ecological narratives to identify possible leverage points for a transition to agroecology in the study area. We identified a local potential for shifting the current system of water and fire hazards management to new systems of participatory land stewardship. To be effective, these systems should support agroecological farmers’ income by altering social practices related to food and reducing the influence of dominant agribusiness actors. Our findings indicate that implementing solutions based on the circulation of local ecological knowledge within systems of participatory guarantees can favor the development of solidarity economies and mutualistic relations between farmers, scientists, and communities. Our work suggests that scientists’ facilitation and knowledge co-creation might be of key importance in structuring local, more sustainable food systems.

Nature-based solutions to ecological challenges have continued to draw significant attention, and are connected to the increased establishment of protected areas as a means for climate and ecological crisis mitigation. This study presents an innovative approach that combines spatial and statistical analysis of land cover change and drivers to evaluate land use management and effectiveness of 22 designated protected areas (PAs) across the tropical coastal regions of sub-Saharan Africa. While the results provided insight into land use management and conservation priorities, it highlighted (1) the use of these protected areas for food production is prevalent, irrespective of its designation. Nevertheless, there is evidence of a decline in cropland in some of the protected areas, suggesting a shift in policy towards conservation land use. (2) The occurrence of forest loss suggests that conservation is weak in most of the protected areas, while wetland conservation efforts are stronger due to their land cover expansion. (3) Population density (human factor) is the most significant driver of land cover change in these protected areas, followed by elevation (natural environment), precipitation (climate), nighttime light (socio-economic), and slope (natural environment). (4) In terms of Ecosystem value, only 15 of the 22 protected areas exhibited an increase in their total ecosystem service value according to land cover change, indicating sustainable land use and measures effectiveness in these protected areas. However, based on an individual land cover assessment, most protected areas showed signs of loss, especially in forests. Given the projected population growth in Africa, a regular assessment of protected areas should be initiated to enable effective and timely management decisions. Additionally, policies to improve the management effectiveness of African protected areas through funding should be a top priority, while taking into consideration the livelihoods of the indigenous people in the area in order to find a sustainable balance.

Ecological interactions are fundamental at the cellular scale, addressing the possibility of a description of cellular systems that uses language and principles of ecology. In this work, we use a minimal ecological approach that encompasses growth, adaptation and survival of cell populations to model cell metabolisms and competition under energetic constraints. As a proof-of-concept, we apply this general formulation to study the dynamics of the onset of a specific blood cancer—called Multiple Myeloma. We show that a minimal model describing antagonist cell populations competing for limited resources, as regulated by microenvironmental factors and internal cellular structures, reproduces patterns of Multiple Myeloma evolution, due to the uncontrolled proliferation of cancerous plasma cells within the bone marrow. The model is characterized by a class of regime shifts to more dissipative states for selectively advantaged malignant plasma cells, reflecting a breakdown of self-regulation in the bone marrow. The transition times obtained from the simulations range from years to decades consistently with clinical observations of survival times of patients. This irreversible dynamical behavior represents a possible description of the incurable nature of myelomas based on the ecological interactions between plasma cells and the microenvironment, embedded in a larger complex system. The use of ATP equivalent energy units in defining stocks and flows is a key to constructing an ecological model which reproduces the onset of myelomas as transitions between states of a system which reflects the energetics of plasma cells. This work provides a basis to construct more complex models representing myelomas, which can be compared with model ecosystems.

So far, urban scaling theory has proven that urban area, infrastructure, and economic output have a scaling relation with population. But if we consider ecological space as a part of urban infrastructure, would the same scaling characteristics exist? What is the scaling relationship between ecological spaces and economic social development in different stages of urbanization? This paper is based on this question and explores the trade-off between social economic system and ecosystem in 370 cities of China. The results show that the relationship between population and urban ecological space generally follows the scaling theory in terms of different types of ecological spaces and ecosystem services. For every 10-fold increase in population size, the total area of ecological space and ecosystem services increase by approximately 4 times. The manifestation of ecological space following the scaling laws is the aggregation behavior of better network connectivity. There is a trade-off between urban ecological space and socioeconomic development, with flow equilibrium reached at a population of 2 million and efficiency equilibrium reached at a population of 1 million. Starting from type I and type II megapolis, urban development gradually tends to stabilize, and there may even be a trend of slow decline in urban development potential. In the absence of ecological space, virtual network space can serve as a substitute for ecological space. The driving factors affect scaling behavior of ecological space, including connectivity of ecological space, spatial heterogeneity of natural conditions, and disturbance of economic and social activities. This research can help city to expand ecological space, promoting the added value of urban ecological assets and keeping the urban development potential within the optimal threshold range continuously.

Urbanization plays a key role in the human activities causing and feeding climate change. At present, climate change and other environmental issues are directly or indirectly related to the metabolism of cities. However, cities may also play a central role in the fight against climate change. This is the reason why Urban Metabolism (UM) has become a powerful concept to account for and understand the way in which complex systems such as cities use and dispose of material resources, also suggesting measures to change their operational regimes. The rightsizing and optimization of UM is basically a matter of social innovation. It implies changes in the way a city collectively produces and reproduces its physical stocks and provides services to its inhabitants. This article aims at identifying strategies, scenarios, and pathways to slow down urban metabolic processes while improving their efficiency, thus managing a successful transition to an urban (more) circular economy, as well as decreasing the material intensity of the urban economy. The main objectives of the article are the following: 1. The development of a renewed approach for studying Urban Metabolism based on transdisciplinary approaches and methods aimed to model metabolic agents' patterns of practices. 2. The definition of urban patterns of resource use of different agents shaping urban metabolism (households, corporate agents, communities, and public authorities). 3. The exploration of the main policies and administrative tools that cities use to manage environmental problems leading to different urban regulation regimes. 4. A tool for generating future scenarios and roadmaps to reach a low-carbon future. This tool is crucial for engaging experts, stakeholders and the public looking for new solutions.

Collaborative governance is increasingly advocated to address the ecological risk management issues that occur during urban agglomeration developing. However, how to form strong and effective collaboration is still a great challenge among multiple cities in urban agglomeration. By analysing the multiple ecological risk transmission pathways of the case of Pearl River Delta Urban Agglomeration (PRD) in China, this paper aims at deconstructing the complex structure and connection types in urban agglomeration, as well as exploring the inherent mechanism of ecological risk governance to achieve collaboration. Thus, a new Bayesian network model of ecological risk transmission is developed to visualize the key connection notes of risk transmission process. Testing the impacts of (1) number of collaborative cities, (2) spatial distance factor and (3) risk transmission links, we can find the optimal cooperative risk management strategy by reducing the probability of occurrence of key nodes and intervening on the critical path of the risk transmission process. The results show that (1) The current collaborative governance plan in the PRD is mainly formulated by large cities driving small surrounding cities, which is not an optimal strategy. (2) The management effect of ecological risks in urban agglomerations is not necessarily positively correlated with the number of collaborative cities. There are multiple combinations methods under a certain number of collaborative cities and the effects of ecological risk collaborative governance are different. (3) Collaboration governance of urban agglomeration should be based on the overall planning of urban development, and comprehensively consider collaboration number, spatial distance and association between cities.

Air pollution is impacting ecosystem services (ES). This paper proposes an emergy-based method framework to assess the dynamic impacts of near-real-time air pollution on ES at different temporal-spatial scales. The paper presents the cases of Shenzhen, Shanghai, Beijing and Baoding, China, investigates the impacts of air pollution on the ES in 2020. In particular, we compared the reduction in ES evaluated using either average (R1) or near-real-time (R2) air pollution data. The results indicate that the differences between R1 and R2 range from about 9% (for Baoding) to almost 45% (for Shenzhen), thus implying the underestimation of the impacts of air pollution on ES based on average data. The ratios of the reduction in ES to the average ES per hour are near-real-time dynamic, with the values of 0–231.62%, 0–59.42%, 0–50.51%, and 0–35.26% in Shanghai, Baoding, Beijing and Shenzhen respectively. Although the air quality in Shanghai is aggregately better than that in Baoding in 2020, the reduction in ES caused by air pollution in Shanghai is more than twice as that of in Baoding, emphasizing the necessity of investigating the impacts of near-real-time air pollution to properly reveal and assess the potential ecological risks. The ratio of the annual total reduction in ES to the annual total ES, near-real-time reduction in ES to the average ES per hour, and near-real-time reduction in ES to the near-real-time ES in Beijing are 7.22%, 0–50.51% and 0–219.27% respectively, highlighting the significance of near-real-time monitoring of air pollution and ES to reveal the potential or hidden impacts of air pollution on ES, and further to facilitate more high time-efficient and fine ecosystem management and conservation.