Periodic Reporting for period 1 - Resilience (Pathways of resilience and evasion of tipping in ecosystems)
Reporting period: 2023-04-01 to 2024-09-30
There is an urgent need to understand the catastrophic effects that global environmental and climate change can have on the Earth, its components, and ecosystems. One critical concern is the potential for sudden, irreversible tipping of ecosystems. Recent discoveries suggest that tipping points might be avoided or even reversed through the spatial pattern formation of vegetation, thereby creating pathways to resilience. Many, yet undiscovered, resilience pathways may exist in ecosystems that are particularly prone to tipping. Moreover, this resilience could be further enhanced by the unexplored link between spatial pattern formation and community assembly.
The goal of the RESILIENCE project is to fundamentally advance our understanding of tipping points and critical transitions in ecosystems, and to reveal how these transitions can be avoided or even reversed through spatial pattern formation.
RESILIENCE aims to develop a new theoretical framework for emerging resilience through spatial pattern formation and to apply this theory to real-world, tipping-prone biomes that are undergoing rapid global change, with a focus on savannas and tundra ecosystems. A focus of our theoretical approach is developing a novel mathematical connection between the origins of pattern formation and the resilience these patterns confer once they emerge.
Empirically, our approach will involve analyzing existing and new data from in situ observations, as well as drone- and satellite-based remote sensing. This research will identify the conditions and spatial patterns that enable ecosystems to evade or even reverse tipping. By identifying these conditions and patterns, we will also shed light on how human interventions can help prevent or reverse tipping, revealing that ecosystems thought to be highly vulnerable to tipping may actually be more resilient than previously believed.
The goal of the RESILIENCE project is to fundamentally advance our understanding of tipping points and critical transitions in ecosystems, and to reveal how these transitions can be avoided or even reversed through spatial pattern formation.
RESILIENCE aims to develop a new theoretical framework for emerging resilience through spatial pattern formation and to apply this theory to real-world, tipping-prone biomes that are undergoing rapid global change, with a focus on savannas and tundra ecosystems. A focus of our theoretical approach is developing a novel mathematical connection between the origins of pattern formation and the resilience these patterns confer once they emerge.
Empirically, our approach will involve analyzing existing and new data from in situ observations, as well as drone- and satellite-based remote sensing. This research will identify the conditions and spatial patterns that enable ecosystems to evade or even reverse tipping. By identifying these conditions and patterns, we will also shed light on how human interventions can help prevent or reverse tipping, revealing that ecosystems thought to be highly vulnerable to tipping may actually be more resilient than previously believed.
In the first months of the reporting period, the consortium focused on recruitment and preparatory work, which included literature reviews, identifying model developments and field locations, and setting up collaborative projects both within and outside the RESILIENCE consortium.
Key outcomes and highlights from the first reporting period include several manuscripts that are either in preparation or currently under review. These manuscripts analyze state-of-the-art methodologies relevant to RESILIENCE (e.g. spatial models for pattern formation in savanna ecosystems) and introduce new models to better understand the interactions between different types of bifurcations. Recent advancements in ecosystem modeling have been made by applying a novel approach using multi-component systems, leading to valuable new mathematical insights into the mechanisms driving the appearance and dynamics of patterns in ecosystems.
In addition to the theoretical work, the RESILIENCE project conducted two field expeditions to collect data in Arctic locations and to expand the monitoring of permafrost thaw disturbances. These expeditions also serve as preparation for upcoming field campaigns scheduled for 2025 and 2026.
Key outcomes and highlights from the first reporting period include several manuscripts that are either in preparation or currently under review. These manuscripts analyze state-of-the-art methodologies relevant to RESILIENCE (e.g. spatial models for pattern formation in savanna ecosystems) and introduce new models to better understand the interactions between different types of bifurcations. Recent advancements in ecosystem modeling have been made by applying a novel approach using multi-component systems, leading to valuable new mathematical insights into the mechanisms driving the appearance and dynamics of patterns in ecosystems.
In addition to the theoretical work, the RESILIENCE project conducted two field expeditions to collect data in Arctic locations and to expand the monitoring of permafrost thaw disturbances. These expeditions also serve as preparation for upcoming field campaigns scheduled for 2025 and 2026.
The research focuses on understanding how savanna and tundra ecosystems may transition into desert or shrubland ecosystems due to ongoing global environmental changes, such as climate shifts, invasive species, and human impacts like overgrazing and land misuse. The primary goal is to unravel the mechanisms behind vegetation pattern formation and the adaptations that enable ecosystems to resist or avoid tipping into these less resilient states.
Key elements of the research involve understanding how ecosystems respond to change at various levels—individual plants, populations, and entire communities—and how these responses contribute to ecological resilience. A first highlight is the development of a mathematical framework for understanding Turing patterns and saddle-node bifurcations, which can predict whether a tipping point in ecosystems can be avoided. This approach has broader applications beyond ecosystems, with potential implications for understanding other dynamic systems, such as the progression of cancer tumors.
The research is important for two main scientific communities:
1. Ecologists: The work introduces new concepts like spatial plasticity in vegetation patterns and front instabilities, which could help reverse ecosystem degradation and guide the design of better management practices. These concepts are particularly relevant for understanding how ecosystems cope with water stress and how spatial patterning can buffer against community shifts or loss of biodiversity.
2. Mathematicians: The study offers new mathematical models to analyze interactions between Turing patterns and saddle-node bifurcations, presenting new challenges and opportunities for mathematical research.
The research aims to:
• Improve understanding of the mechanisms behind spatial patterning in tundra ecosystems and their vulnerability to climate change.
• Enhance knowledge of ecological resilience, particularly in ecosystems experiencing rapid warming, such as savanna and tundra.
• Inform climate change impact assessments at various scales, with the goal of influencing policy and contributing to future climate impact reports.
The research will also provide valuable hypotheses for further experiments and promote knowledge exchange between scientific communities and policymakers.
Key elements of the research involve understanding how ecosystems respond to change at various levels—individual plants, populations, and entire communities—and how these responses contribute to ecological resilience. A first highlight is the development of a mathematical framework for understanding Turing patterns and saddle-node bifurcations, which can predict whether a tipping point in ecosystems can be avoided. This approach has broader applications beyond ecosystems, with potential implications for understanding other dynamic systems, such as the progression of cancer tumors.
The research is important for two main scientific communities:
1. Ecologists: The work introduces new concepts like spatial plasticity in vegetation patterns and front instabilities, which could help reverse ecosystem degradation and guide the design of better management practices. These concepts are particularly relevant for understanding how ecosystems cope with water stress and how spatial patterning can buffer against community shifts or loss of biodiversity.
2. Mathematicians: The study offers new mathematical models to analyze interactions between Turing patterns and saddle-node bifurcations, presenting new challenges and opportunities for mathematical research.
The research aims to:
• Improve understanding of the mechanisms behind spatial patterning in tundra ecosystems and their vulnerability to climate change.
• Enhance knowledge of ecological resilience, particularly in ecosystems experiencing rapid warming, such as savanna and tundra.
• Inform climate change impact assessments at various scales, with the goal of influencing policy and contributing to future climate impact reports.
The research will also provide valuable hypotheses for further experiments and promote knowledge exchange between scientific communities and policymakers.