Frontiers in Marine Science (Feb 2022)
Using Geographical Overlaps to Track Temporal Changes in Species Interactions and Community Coexistence Instability
Abstract
Environmental and climatic changes are expected to redistribute species, altering the strengths of species interaction networks; however, long-term and large-scale evaluations remain elusive. One way to infer species interaction networks is by analyzing their geographical overlaps, which provides indices of species interdependence, such as mean spatial robustness (MSR), which represents the geographical impact of a species on other species, and mean spatial sensitivity (MSS), which indicates how a species is influenced by other species. Integrating MSR and MSS further allows us to assess community coexistence stability and structure, with a stronger negative relationship between MSR and MSS (i.e., species are unequally dependent on each other) within a community at a given time suggesting a more stable community. Here, we assessed multidecadal changes in adult marine fish communities using bottom trawl datasets across latitudes from 1982 to 2011 in the Eastern US Continental Shelf, North Sea, and Eastern Bering Sea. Consistent, significant long-term increasing temporal trends of MSR and MSS were found in all three large marine communities. MSR exhibited strong correlations with species’ range sizes, especially in high-latitude communities, while MSS was strongly positively correlated with species’ median proportion of overlap with interacting species. The relationships between MSR and MSS were generally negative, indicating stably coexisting fish communities. However, the negative relationships weakened over time, implying that the coexisting fish communities gradually became unstable. Our findings provide an assessment of changes in spatially geographical aspects of multiple species, for decades and at mid- to high latitudes, to allow the detection of global ecological changes in marine systems by alternative estimation of geographic overlaps of species interaction networks. Such species co-occurrence estimation can help stay vigilant of strategies for accelerating climate change mitigation particularly at coarser spatial scales.
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