Long-term supratidal rockpool invertebrate community, Discovery Bay, Jamaica.

The rockpool cluster offers unique characteristics making it a model system for general questions in ecology: (1) all rockpools share biotic history (any species can reach any rockpool); (2) they form a strong gradient of conditions from benign to harsh; (3) 1-day sampling across all rockpools ensures census consistency; (4) rockpools respond to changing conditions within a short (days) time frame; (5) they are easy to manipulate (note: the data are from an unmanipulated rockpool subset), and (6) they may act as a single metacommunity that exhibits consistent species distribution patterns on a broader scale (unpublished). Consequently, the rockpools continue generating insights, with the first publications in 1996. The data represent an intensive rockpool metacommunity monitoring project, making them of considerable value to our understanding of tropical coastal metacommunity dynamics and general ecological processes. The dataset covers surveys of invertebrate fauna in 49, primarily supratidal, rockpools on a fossil coral reef over 25 years. All rockpools occur within a 73 × 47 m array of rocks at a distance of less than 2 m from the nearest neighbor. About 200 other rockpools occur on the same area. They are in a sheltered bay (Discovery Bay, Jamaica) between 0 and 5 m from the ocean. Typically, rockpools are 5-30 cm deep and 40 cm across on average, with elevation from a few centimeters to 300 cm above sea level. Rockpools may drain excess water from precipitation or waves into other rockpools, which allows organisms to disperse passively downstream. Of the 49 rockpools in the survey, 35 are subject to occasional drying up, while the others appear permanent. Most collections (1989-2004) were annual censuses of invertebrate populations, exceeding a total of 475,000 invertebrates counted, with only minor record gaps. In all cases, species level taxonomic information consists of detailed photographs. In some cases, notes are included with the taxonomic data where species identification could not be matched to information available in the literature. Samples from 2005 to 2019 still require organism identification. Abiotic parameters were measured the day before biotic sampling took place as the process of biotic sampling can impact abiotic parameters through stirring, oxygenation and filtering (temperature, pH, turbidity, dissolved oxygen, light intensity, salinity, alkalinity, and nutrients). The cumulative richness in the metacommunity consist of 78 freshwater, marine, and brackish water taxa, with a mean richness per rockpool of 5.5 distinct species. Regarding taxonomic makeup, ostracods dominated in both diversity and number, followed by copepods, and insects. There are no copyright restrictions on the data set; please cite this data paper when using these data in publications.

Examining the relative influence of dispersal and competition on co-occurrence and functional trait patterns in response to disturbance.

Disturbance gradients are particularly useful for understanding the relative influences of competition and dispersal. Shortly after disturbance, plant composition should be influenced more strongly by dispersal than competition; over time, this should reverse, with competition becoming more important. As such, we predicted that plant functional traits associated with high dispersal ability would be over-represented shortly after a disturbance event occurs, while those associated with high competitive ability would have increased representation as time progresses. Additionally, it has been suggested that competitive interactions may contribute to negative co-occurrence patterns; if this is the case, negative co-occurrence patterns should also increase as time-since-disturbance increases. Here, we examine how functional trait and co-occurrence patterns change over time following a herbicide-based disturbance, compared to undisturbed vegetation, in a temperate, old-field grassland dominated by herbaceous perennials. In our study system, negative co-occurrence patterns were most pronounced in disturbed plots one year after herbicide application, consistent with several lines of evidence that dispersal can strongly impact both composition and co-occurrence patterns. Over three years post-disturbance, co-occurrence patterns in disturbed plots decreased, becoming more similar to control plots. This pattern is inconsistent with the expectation that competition contributes to negative co-occurrence patterns, at least over three growing seasons. More pronounced negative co-occurrence patterns were associated with higher species evenness among plots. Functional traits related to increased dispersal (mean seed mass, and proportion of stoloniferous/rhizomatous species) and competitive ability (mean species height, and mean specific leaf area) did not differ significantly across treatments, with the exception of mean height in the third-year post-disturbance; however, the overall trajectory of this trait was inconsistent with theoretical expectations. Overall, co-occurrence patterns changed across the gradient of time-since disturbance, but not as expected; functional trait patterns (trait means, functional diversity measures) were not responsive to our experimental disturbance gradient.

A comparative evaluation of five common pairwise tests of species association.

Researchers have long viewed patterns of species association as key to understanding the processes that structure communities. Community-level tests of species association have received the most attention; however, pairwise species associations may offer greater opportunity for linking patterns to specific mechanisms. Although several tests of pairwise association have been developed, there remain gaps in our understanding of their performance. Consequently, it is unclear whether these methods reliably detect patterns of association, or if any one method is superior. We maximized association patterns for single species pairs in synthetic community matrices and examined how accurately five pairwise association tests found that pair, while not finding others (i.e., type I and II error rates). All tests are more likely to miss patterns of association than to falsely detect them. When we maximized association for a species pair that included one or more rare or common species, tests were frequently unable to identify that pair as significantly associated. Consequently, these tests are best suited for identifying significant associations between pairs of species that occur in an intermediate number of samples; for such pairs, three of the five tests considered here detected 100% of the pairs for which we maximized associations.

The Influence of Matrix Size on Statistical Properties of Co-Occurrence and Limiting Similarity Null Models.

Null models exploring species co-occurrence and trait-based limiting similarity are increasingly used to explore the influence of competition on community assembly; however, assessments of common models have not thoroughly explored the influence of variation in matrix size on error rates, in spite of the fact that studies have explored community matrices that vary considerably in size. To determine how smaller matrices, which are of greatest concern, perform statistically, we generated biologically realistic presence-absence matrices ranging in size from 3-50 species and sites, as well as associated trait matrices. We examined co-occurrence tests using the C-Score statistic and independent swap algorithm. For trait-based limiting similarity null models, we used the mean nearest neighbour trait distance (NN) and the standard deviation of nearest neighbour distances (SDNN) as test statistics, and considered two common randomization algorithms: abundance independent trait shuffling (AITS), and abundance weighted trait shuffling (AWTS). Matrices as small as three × three resulted in acceptable type I error rates (p < 0.05) for both the co-occurrence and trait-based limiting similarity null models when exclusive p-values were used. The commonly used inclusive p-value (≤ or ≥, as opposed to exclusive p-values; < or >) was associated with increased type I error rates, particularly for matrices with fewer than eight species. Type I error rates increased for limiting similarity tests using the AWTS randomization scheme when community matrices contained more than 35 sites; a similar randomization used in null models of phylogenetic dispersion has previously been viewed as robust. Notwithstanding other potential deficiencies related to the use of small matrices to represent communities, the application of both classes of null model should be restricted to matrices with 10 or more species to avoid the possibility of type II errors. Additionally, researchers should restrict the use of the AWTS randomization to matrices with fewer than 35 sites to avoid type I errors when testing for trait-based limiting similarity. The AITS randomization scheme performed better in terms of type I error rates, and therefore may be more appropriate when considering systems for which traits are not clustered by abundance.

An unusual erysipelas-like presentation.

A 61-year-old man presented with erysipelas-like cutaneous leishmaniasis.