Habitat Heterogeneity Determines Climate Impact on Zooplankton Community Structure and Dynamics

<div><p>Understanding and predicting species distribution in space and time and consequently community structure and dynamics is an important issue in ecology, and particularly in climate change research. A crucial factor determining the composition and dynamics of animal populations is habitat heterogeneity, i.e., the number of structural elements in a given locality. In the marine pelagic environment habitat heterogeneity is represented by the distribution of physical oceanographic parameters such as temperature, salinity and oxygen that are closely linked to atmospheric conditions. Little attention has been given, however, to the role of habitat heterogeneity in modulating the response of animal communities to external climate forcing. Here we investigate the long-term dynamics of <i>Acartia</i> spp., <i>Temora longicornis</i>, and <i>Pseudocalanus acuspes</i>, three dominant zooplankton species inhabiting different pelagic habitats in the Central Baltic Sea (CBS). We use the three copepods as indicator species for changes in the CBS zooplankton community and apply non-linear statistical modeling techniques to compare spatial population trends and to identify their drivers. We demonstrate that effects of climate variability and change depend strongly on species-specific habitat utilization, being more direct and pronounced at the upper water layer. We propose that the differential functional response to climate-related drivers in relation to strong habitat segregation is due to alterations of the species’ environmental niches. We stress the importance of understanding how anticipated climate change will affect ecological niches and habitats in order to project spatio-temporal changes in species abundance and distribution.</p></div

Summary of final Generalized Additive Models of species-specific responses to predation and hydro-climatic drivers in spring and summer.

<p>Adjusted R², estimated degrees of freedom (edf), significance (P-value), and individual explained deviance (excluding other significant effects) of the various covariates are provided. The covariate that explains most is indicated in bold. Note that for the <i>Acartia</i> spp. spring model the BSI and temperature smoother are presented for each basin separately but explained deviance is given for all three combined.</p><p>Covariates: BSI = Baltic Sea Index, T = Temperature, S = Salinity, PI = Predation Index.</p><p>Basins: BB = Bornholm Basin, GD = Gdansk Deep, GB = Gotland Basin.</p

Observed and predicted long-term trends based on the best performing Generalized Additive Model (GAM).

<p>Spring and summer biomass anomalies of <i>Acartia</i> spp. (green boxes), significantly differed between the Bornholm Basin (BB), the Gdansk Deep (GD), and the Gotland Basin (GB), while trends for <i>Temora longicornis</i> (red boxes), and <i>Pseudocalanus acuspes</i> (blue boxes) were not basin-specific and rather consistent within the entire Central Baltic Sea (CBS) region. Open circles (BB), triangles (GD) or crosses (GB) represent the observed values in each basin, while the continuous lines indicate the predicted trends from the GAM based on basin-specific smoothers or a single smoother fore the entire CBS region. The shaded areas indicate the pointwise 95% CI.</p

Statistical model results of <i>Acartia</i> spp., <i>T. longicornis</i>, and <i>P. acuspes</i>.

<p>Partial plots of significant covariates in the final spring and summer GAMs are presented for each basin separately or together depending on the significance and model performance. Values on the y-axis indicate the effect that the term on the x-axis has on the biomass anomaly. The solid lines indicate the smoothed (non-) parametric trend, shaded areas indicate the pointwise 95% CI.</p