Insects, Journal Year: 2024, Volume and Issue: 15(11), P. 842 - 842
Published: Oct. 28, 2024
Current methods for studying the effects of climate change on plants and pollinators can be grouped into two main categories. The first category involves using species distribution models (SDMs) to generate habitat suitability maps, followed by applying scenarios predict future separately. second constructing interaction matrices between then either randomly removing or selectively generalist specialist species, as a way estimate how might affect plant–pollinator network. primary limitation approach is that it examines plant pollinator distributions separately, without considering their interactions within context pollination weakness does not accurately impacts, arbitrarily selects remove knowing which will truly shift, decline, increase in due change. Therefore, new needed bridge gap these while avoiding specific limitations. In this context, we introduced an innovative requires creation binary maps pollinators, based SDMs, both current periods. This step aligns with mentioned earlier. To assess network framework, consider co-overlapping geographic matrix. For purpose, developed Python program overlays generating matrices. These represent potential interactions, ‘0’ indicating no overlap ‘1’ where coincide same cell. As result, each cell study area, construct present means cell, analyze at least networks co-overlap. By comparing topology over time, infer fine spatial scale. We applied our methodology Chile case study, 187 171 resulting 2906 networks. evaluated could across cell-by-cell basis. Our findings indicated effect likely manifest more significantly through extinctions, rather than major changes topology.
Language: Английский