No abstract

In mosaic ecosystems, multiple land types coexist as alternative stable states exhibiting distinct spatial patterns. Forest‐grassland mosaics are ecologically valuable, due to their high species richness. However, anthropogenic disturbances threaten these ecosystems. Designating protected areas is one approach to preserving natural mosaics. Such work must account for climate change, yet there are few spatially explicit models of mosaics under climate change that can predict its effects. We construct a spatially explicit simulation model for a natural forest‐grassland mosaic, parameterized for Southern Brazil. Using this model, we investigate how the spatial structure of these systems is altered under climate change and other disturbance regimes. By including local spatial interactions and fire‐mediated forest recruitment, our model reproduces important spatial features of protected real‐world mosaics, including the number of forest patches and overall forest cover. Multiple concurrent changes in environmental conditions have greater impacts on tree cover and spatial structure in simulated mosaics than single changes. This sensitivity reflects the narrow range of conditions under which simulated mosaics persist and emphasizes their vulnerability. Our model predicts that, in protected mosaics, climate change impacts on the fire‐mediated threshold to recruitment will likely result in substantial increases in forest cover under Representative Concentration Pathway (RCP) 8.5, with potential for mosaic loss over a broad range of initial forest cover levels. Forest cover trajectories are similar until 2150, when cover increases under RCP 8.5 outpace those under RCP 2.6. Mosaics that persist under RCP 8.5 may experience structural alterations at the patch and landscape level. Our simple model predicts several realistic aspects of spatial structure as well as plausible responses to likely regional climate shifts. Hence, further model development could provide a useful tool when building strategies for protecting these ecosystems, by informing site selection for conservation areas that will be favourable to forest‐grassland mosaics under future climates.

Simulation models from the early COVID-19 pandemic highlighted the urgency of applying non-pharmacetical interventions (NPIs), but had limited empirical data to use. Here we use data from 2020-2021 to retrospectively model the impact of NPIs. Our model represents age groups and census division in Ontario, Canada, and is parameterised with epidemiological, testing, demographic, travel, and mobility data. The model captures how individuals adopt NPIs in response to reported cases. The model predicts that school/workplace closure and individual NPI adoption together reduced the number of deaths in the best-case scenario for the case fatality rate (CFR) from 174, 411 [CI: 168, 022, 180, 644] to 3, 383 [CI: 3, 295, 3, 483] in the Spring 2020 wave. In the Fall 2020/Winter 2021 wave, the introduction of NPIs in workplaces/schools reduced the number of deaths from 17, 291 [CI: 16, 268, 18, 379] to 4, 167 [CI: 4, 117, 4, 217]. Deaths were several times higher in the worst-case scenario for the CFR. We also estimated that each additional 7 − 11 (resp. 285 − 452) individuals who choose to adhere to NPIs in the first wave prevented one additional infection (resp., death under a best-case scenario). Our results show that the adoption of NPIs prevented a public health catastrophe.

The critical community size (CCS) is the minimum closed population size in which a pathogen can persist indefinitely. Below this threshold, stochastic extinction eventually causes pathogen extinction. Here we use a simulation model to explore behaviour-mediated persistence: a novel mechanism by which the population response to the pathogen determines the CCS. We model severe coronavirus 2 (SARS-CoV-2) transmission and non-pharmaceutical interventions (NPIs) in a population where both individuals and government authorities restrict transmission more strongly when SARS-CoV-2 case numbers are higher. This results in a coupled human-environment feedback between disease dynamics and population behaviour. In a parameter regime corresponding to a moderate population response, this feedback allows SARS-CoV-2 to avoid extinction in the trough of pandemic waves. The result is a very low CCS that allows long term pathogen persistence. Hence, an incomplete pandemic response represents a “sour spot” that not only ensures relatively high case incidence and unnecessarily long lockdown, but also promotes long-term persistence of the pathogen by reducing the CCS. Given the worldwide prevalence of small, isolated populations in which a pathogen with low CCS can persist, these results emphasize the need for a global approach to coronavirus disease 2019 (COVID-19) vaccination.