Simulated pressures and ecosystem responses
|Contributing Authors:||Sonia Kéfi, Florian Schneider, Angeles G. Mayor, Alain Danet, Marina Rillo, Simon Benateau, Jacob Keizer, Ana Vasques, Susana Bautista, Paco Rodriguez, Alejandro Valdecantos, Jaime Baeza, Ramón Vallejo, Max Rietkerk, Mara Baudena, Mart Verwijmeren, Koen Siteur, Rubén Díaz-Sierra|
|Source document:||S. Kéfi, A. Vasques, F. Schneider, M. Rietkerk, A.G. Mayor, M. Verwijmeren, R. Diaz-Sierra and M. Baudena. 2016. Response of Mediterranean drylands to increasing pressures. CASCADE Project Deliverable 6.1, 54 pp
Computer modelling for understanding tipping points in ecosystems
The CASCADE modelling group explains how computer modelling can be used to understand tipping points in ecosystems [13:27]
The development of mathematical models, informed and improved by the empirical studies at the CASCADE study sites, allowed further investigation of how Mediterranean drylands cope with various levels of environmental stress.
This section of CASCADiS presents those models which focused on two axes of improvement of current dryland models relevant to study dryland resilience:
- the way external pressures are incorporated in dryland models; we focused on three types of external pressures: grazing, fire and drought;
- the way vegetation (the ‘biotic component’) is modelled; we incorporated species, functional groups and species-species interactions in dryland vegetation models.
We investigated how the additional ecological mechanisms included affected the response of the ecosystem to stress. We especially looked for shift behaviors and identified the conditions that favored the emergence of catastrophic shifts at the ecosystem scale.
Incorporating external pressures into dryland models
Grazing is one of the main causes of desertification of drylands worldwide and a possible cause of degradation in four of the CASCADE study sites. Understanding how and why different types of grazing and different levels of grazing pressures affect dryland resilience is of great importance to inform dryland management and help preventing desertification. We developed a model for vegetation dynamics in drylands, which incorporated an important aspect of grazing typically ignored in dryland models: its spatial component. Indeed, plant species adapted against grazing can provide refugia from large herbivores to neighboring plants (a phenomenon is known as associational resistance).
Fire is the main driver of degradation in two of the CASCADE study sites. Because of the long history of fire in the Mediterranean basin, most Mediterranean plant species are well adapted to fire, but global changes have led to an intensification of the fire regime in the last decades. It is however unclear how these changes in fire regimes will affect dryland vegetation dynamics. We developed two different models, each mapped to one of the two CASCADE study sites of Varzea (Portugal) and Ayora (Spain), to study the effect of fire on vegetation succession. The models include several functional groups, reflecting the different species strategies toward fire.
For more details see »Dryland response to fire
Besides grazing and fire, a common stressor in all drylands is drought. Global climate models project changes in rainfall intermittency in arid and semiarid regions with more confidence than possible changes in annual and seasonal rainfall volumes. For the semi-arid Mediterranean area, an increase in meteorological drought frequency is predicted (medium confidence), together with an increase in heavy precipitation events (high confidence). it is unknown if and exactly how these projected changes in rainfall intermittency are going to affect the productivity and functioning of semiarid ecosystems. We addressed the question of how rainfall intermittency influences drylands ecosystem dynamics with two separate studies.
For more details see »Dryland response to changes in rainfall intermittency
Modelling vegetation in drylands
A number of model studies performed aimed at better understanding the role of species interactions in drylands, in particular how different stressors (drought, grazing) affect plant-plant interactions and how that, in turn, affects species coexistence and ecosystem dynamics. Facilitation between plants is known to be an important mechanism driving vegetation dynamics in dryland, but we lack understanding of how interactions between plants change in response to combined effects of drought and consumer pressure.
The models developed suggest that the relative importance of facilitative vs competitive plant-plant interactions varies along stress gradients, thereby driving the possibility for species coexistence. In particular, facilitation via associational resistance allows species coexistence under a range of environmental conditions. When space is explicitly taken into account, the ecosystem exhibits catastrophic shift to desertification once a threshold of aridity passed.
With different plant functional groups (e.g. a nurse and a protégée), this catastrophic shift is more complex than usually found in models: before vegetation extinction, there is a zone of tristability between a desert state, coexistence between the two species and the nurse alone. This creates the possibility of different types of catastrophic shifts among these three states.
In summary, our results highlight the importance of the role of the spatial aspect of the external pressure, demographic stochasticity, rainfall intermittency and rate of environmental change, the way species interact with each other (facilitation/competition), and the relevance of different types of ecological feedbacks for our understanding of the species composition and the dynamics of dryland ecosystems. The deliverable concludes on the main results of these models and possible implications.
For more details see »Summary conclusions.
Those model, combined with socio-economic analysis, could help build management strategies to help prevent dryland degradation. We provide the codes and information necessary to run these models to promote the dissemination of this work.
For more details see »Sharing the models.