Stephanie Figary

Zooplankton transfer substantial energy in aquatic food webs and are used as indicators of environmental change. Syntheses of zooplankton community dynamics globally require datasets that span a wide range of environmental gradients; however, these datasets are limited due to methodological differences across programs, taxonomic inconsistencies, and a lack of standardized metadata. To reconcile these challenges, we created the Zooplankton International Geospatial (ZIG) dataset, which includes original zooplankton, water physical and chemical variables, and lake morphometric data from 311 inland lakes and reservoirs. ZIG includes waterbodies ranging in size from 0.005 to 82,100 km ² and spanning broad latitudinal (−47.26 to 64.90) and longitudinal ranges (−165.04 to 176.53). Temporal coverage for individual waterbodies ranges between 1 and 60 yr with sampling frequency ranging from annually to weekly. With its extensive coverage and content, we consider ZIG to be a cornerstone for future investigations of global scale lake biodiversity change.

Quantifying the relationship between phytoplankton and zooplankton may offer insight into zooplankton sensitivity to shifting phytoplankton assemblages and the potential impacts of producer-consumer decoupling on the rest of the food web. We analyzed 18 years (2001–2018) of paired phytoplankton and zooplankton samples collected as part of the United States Environmental Protection Agency (U.S. EPA) Great Lakes Biology Monitoring Program to examine both the long-term and seasonal relationships between zooplankton and phytoplankton across all five Laurentian Great Lakes. We also analyzed effects of phytoplankton diversity on zooplankton biomass, diversity, and predator-prey (zooplanktivore/grazer) ratios. Across the Great Lakes, there was a weak positive correlation between total algal biovolume and zooplankton biomass in both spring and summer. The relationship was weaker and not consistently positive within individual lakes. These trends were consistent over time, providing no evidence of increasing decoupling over the study period. Zooplankton biomass was weakly negatively correlated with algal diversity across lakes, whereas zooplankton diversity was unaffected. These relationships did not change when we considered only the edible phytoplankton fraction, possibly due to the high correlation between total and edible phytoplankton biovolume in most of these lakes. Lack of strong coupling between these producer and consumer assemblages may be related to lagging responses by the consumers, top-down effects from higher-level consumers, or other confounding factors. These results underscore the difficulty in predicting higher trophic level responses, including zooplankton, from changes in phytoplankton assemblages.

Background: Taxa Indicator Threshold ANalysis (TITAN) was developed to identify thresholds along environmental gradients where rapid changes in taxa frequency and relative abundance are observed. TITAN determines separate change-points for increasing and decreasing taxa in aggregate, as well as change-points for individual taxa, with associated confidence intervals generated using bootstrapping. However, if TITAN is applied to different classes of observations, additional analyses besides using non-overlapping confidence intervals are needed to establish whether change-points differ between treatments or groups because non-overlapping confidence intervals can indicate significant differences but overlapping confidence intervals do not necessarily mean the null hypothesis cannot be rejected. Methods: To address this, we present a new R package, pTITAN2, which is an extension to the existing TITAN2 package. The pTITAN2 package was developed to enable comparisons of TITAN output between treatments by permutating the observed data between treatments and rerunning TITAN on the permuted data. Results: The pTITAN2 package includes two functions, occurrences and permute. The occurrences function selects the taxonomic codes to be used in a TITAN run while maintaining the most taxonomic details. The permute function is then used to create a list of permuted sets of taxa and environmental gradients. TITAN is then run again on the permuted data and p-value test can be calculated using the observed and permuted TITAN output to test for statistical differences between treatment effects. Conclusions: The package pTITAN2 is an extension of the existing TITAN2 package and enables users to perform the appropriate statistical tests and determine statistical differences without using overlapping confidence intervals.

Theory suggests that in a new habitat, initial levels of genetic or species diversity can influence subsequent community assembly. Nevertheless, empirical investigations of these diversity effects in newly created habitats remain rare at both the genetic and species level, especially for animal systems. To test this theory, we conducted a field experiment in which initial stocking diversity (both intra‐ and interspecific) of freshwater zooplankton in newly constructed pools was manipulated in a 2 × 2 fully factorial design. Zooplankton communities were sampled every 2 weeks from May to August in 2011 and 2012, and once in May of 2013 and 2014. Estimates of overland dispersal were measured in 2012. Despite theoretical predictions, we found no difference in taxonomic richness among stocking treatments after 4 yr. A total of 24 species was recorded in the experimental pool metacommunity, with average cumulative taxonomic richness ranging from 6.1 to 7.6 species per pool. Using dispersal traps, we found that dispersal of zooplankton was rapid, with eight taxa dispersing within 7 d; we found no difference in the number of dispersed propagules based on number of neighboring source pools. Despite theoretical predictions regarding diversity and community assembly, our study suggests that initial diversity may have no effect on early successional community species richness.