Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

Adult B. neritina colonies were collected from 0.5 to 1.5 m in depths at Dog Island, FL (29°49′42.0″ N 84°34′50.9″ W) on 8 June 2021. The experiment itself ran from June untill August, 2021. 

We generated 8–10 clones (fragments) from each of the 27 lab-grown genotypes to distribute across the temperature treatments. In total, there were 248 fragmented clones. Clonal fragments were cut from the tips of the 27 lab-grown genotypes after 23 days. All fragments were cut from tips showing signs of active growth. Each clonal fragment ranged in size from 11 to 124 zooids, with an average size of 54 ± 18 zooids (mean ± SD). Clonal fragments were reattached to ~40 × ~90 mm acetate pieces using non-toxic cyanoacrylate glue immediately after cutting. The fragments were glued at the base of the branch where they were cut so that the growing end was above and off the acetate strip. The clonal fragments grew at 23°C for 8 days to allow recovery (all survived). Following this 8-day period, the size of clonal fragments was measured as the number of zooids, and fragments were randomly distributed across temperature treatments with respect to their size. Although each source colony from which clonal fragments were cut was 23 days old, each fragment was younger since it was taken from the growing distal tips. 

To produce a thermal gradient, temperature was independently applied to 16 glass aquarium tanks (8 L tanks filled with 3 L of FSW) that were each placed in a water bath (plastic tub) filled with 5 L of reverse osmosis water up to the water line in the tank. Aquarium tanks in water baths were housed across two identical incubators (Percival I-36VL). Both incubators were set to 23°C (i.e. the lowest temperature) on a 13:11 h light:dark cycle. Within each incubator, there were eight tanks randomly allocated to one of four target temperatures: 23, 26, 29 or 32°C (i.e. two tanks per target temperature), covering temperatures experienced in the field during their reproductive period and when the experiment was conducted (Figure 1). Although there were four target temperatures, we used the realized temperature measured in each tank as a continuous variable in the analyses, so there were eight independent applications of temperature in each of the two incubators. Since this project was focused on the potential impacts of warming and reproduction, we chose to focus on the upper temperature range instead of the lower temperature range below which colonies do not reproduce. 

Genotypes could not be represented in every tank. Each tank accommodated a maximum of 18 colonies, but there were 27 genotypes. There were 16 tanks in total, but 16 clonal fragments could not be collected from each genotype. Therefore, 13 genotypes were randomly assigned to one incubator and the remaining 14 genotypes were assigned to the other incubator. One clonal fragment from each genotype was placed in each of the eight tanks in one incubator. Therefore, each genotype had at least two clones at each target temperature within an incubator. Colonies within tanks were spaced approximately 2–2.5 cm apart. In cases where there were more than eight clonal fragments for a genotype, the extra clonal fragments were randomly allocated to a tank in the incubator that the genotype was not assigned to. In total, there were 13–17 colonies placed in each tank, totalling 60–63 colonies assigned to each of the four target temperatures. 

Each water bath (aside from those for which 23°C was their target temperature) was heated using a 50-Watt aquarium heater (Hydor) connected to a digital temperature controller (Aqua Logic NEMA 4X, TR115SN). The temperature controllers were programmed to turn the aquarium heater on when the FSW temperature fell below 0.5°C of its target temperature. HOBO Tidbit V2 temperature loggers were placed in each tank to record the water temperature at 15-minute intervals. The realized temperature of each tank was calculated as the median temperature recorded by the loggers between the time that the colonies were placed into their treatments and the end of the experiment (30 days). Water changes for both the glass aquarium tank and water bath, as well as the replenishment of Rhodomonas salina algal food occurred every 3–4 days. Algal food was provided at a density of 100,000 cells/ml at each water change. 

To estimate the effects of temperature on development rate, we assessed colonies for the presence or absence of ovicells at 7, 17, 21 and 30 days under a dissecting microscope, covering the range of age at maturity seen in the field (Burgess & Bueno, 2021). The presence of an ovicell is a key indicator of reproductive maturity since an ovicell is only formed after a mature egg is produced (Ostrovsky, 2013; Ström, 1977). After 30 days growing in the experimental temperatures, each colony was preserved in 70% EtOH. To assess colony survival, we recorded the number of zooids capable of feeding (visible polypide and lophophore), the number of zooids regressed (visible brown body) and the number of zooids dead (clear cystid without polypide), which, when summed, gives the total number of zooids. We also recorded the total number of ovicells in each colony to estimate reproductive capacity, since each ovicell broods a single embryo. We estimated the relative growth rate of each colony using the change in number of zooids (Z) over time (t). Relative growth
rate is in units of zooids zooid−1 day−1.

* adjusted field names to comply with database requirements

NSF Award Abstract:
In marine systems, the production, dispersal, and recruitment of larvae are crucial processes that rebuild depleted adult stocks, facilitate changes in species geographic ranges, and modify the potential for adaptation under environmental stress. Traditionally, the tiny larvae of bottom-associated adults were thought to disperse far from their parents and from each other, making interactions among kin improbable. However, emerging evidence is challenging this view: larval dispersal does not always disrupt kin associations at settlement, and a large fraction of invertebrate diversity on the seafloor contains species in which most larvae disperse short distances. Limited dispersal increases the potential for interactions among kin, which has important consequences for individual fitness across many generations, and therefore the productivity of populations and the potential for adaptation. But when these consequences occur, and how exactly they manifest, remains largely unexplained. The key challenge now is to explain and predict when kin associations are likely to occur, and when they are likely to have positive or negative ecological consequences. Therefore, the key questions addressed by this research are: 1) how and when do kin associations arise and persist, and 2) what are the consequences of living with kin for survival, growth, and reproduction. This concept-driven research combines genomic approaches with experimental approaches in lab and field settings using an experimentally-tractable and representative invertebrate species. The project trains and mentors PhD students and a postdoctoral scholar at Florida State University (FSU). Field and laboratory activities are developed and incorporated into K–12 education programs and outreach opportunities at FSU.

The spatial proximity of relatives has fundamentally important consequences at multiple levels of biological organization. These consequences are likely to be particularly important in a large range of benthic marine systems, where competition, facilitation, and mating depend strongly on the proximity and number of neighbors. However, explaining and predicting the occurrence, magnitude, and direction of such effects remains challenging. Emerging evidence suggest that the ecological consequences of kin structure are unlikely to have a straight-forward relationship with dispersal potential. Therefore, it is crucial to discover new reasons for when kinship structure occurs and why it could have positive, negative, or neutral ecological consequences. This research aims to provide a new understanding of how dispersal and post-settlement processes generate spatial kin structure, how population density and relatedness influence post-settlement fitness, and how the relatedness of mating partners influences the number and fitness of their offspring (inbreeding and outbreeding). The research combines genomic approaches, experimental progeny arrays, and manipulative experiments in field and lab settings to test several hypotheses that are broadly applicable across species. By focusing on an experimentally tractable species to test broadly applicable hypotheses, the project achieves generality and a level of integration that has been difficult to achieve in previous work.