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Variation in aggregate descriptors of rocky shore communities: a test of synchrony across spatial scales
- Arribas, Lorena P., Gutiérrez, Jorge L., Bagur, María, Soria, Sabrina A., Penchaszadeh, Pablo E., Palomo, M. Gabriela
- Marine biology 2019 v.166 no.4 pp. 44
- algae, biomass, climate, climate change, geographical distribution, macroinvertebrates, models, mussels, prediction, secondary productivity, species diversity, temporal variation, time series analysis
- Rocky shore communities usually show complex patterns of compositional variation in space and time. Yet, this does not rule out the possibility of observing coherent temporal trends in aggregate community variables (e.g., biomass and number of species or individuals within functional groups or whole communities) due to broad-scale, seasonal, or interannual environmental controls that operate independently of local species composition. The goal of this study was to evaluate whether five aggregate community variables (mussel density, mussel biomass, algal biomass, macroinvertebrate density, and species density) show synchronous patterns of short-term, temporal variation (2 years) across eight rocky shore sites located in the Southwestern Atlantic and within two biogeographic regions (Warm Temperate Southwestern Atlantic and Magellanic). The study predictions were (1) that synchrony will increase as the spatial scale of analysis becomes smaller and, (2) that pairs of nearby sites will be more synchronized than pairs of distant ones. These predictions were weakly, if at all, supported by the data. Synchrony in aggregate community descriptors rarely occurred across the studied rocky shore sites. It can be observed at any spatial scale, and it can even fail to happen among sites located a few hundred meters apart. This suggests that local processes are overarching sources of short-term variability at the regional level, highlights the caution needed in generalizing from spatially limited time series data, and also underscores the potential limitations of climate envelope models to predict how aggregate community variables and related ecosystems functions (e.g., primary and secondary production) will respond to global climate change.