Search

Caretta caretta (Loggerhead Sea Turtle) is a globally threatened sea turtle species that nests on United States Atlantic coast beaches. While several environmental factors influence egg incubation and hatching success, maternal identity may also play an important role and has been overlooked. New molecular advances, such as ongoing genetic capture-recapture using eggshells, allow the identification of individual females using fresh eggshells, which can then be used to track nesting and hatching success across individual females. Across 2 consecutive nesting seasons, we monitored 170 nests for environmental conditions as part of a larger Georgia Department of Natural Resources monitoring program. Mothers had been identified using molecular data and classified as either neophytes or remigrants. We identified 34 of the nests as belonging to neophyte Loggerhead mothers, which exhibited a 61% hatching success rate, compared to only 46% success for remigrant mothers (P < 0.01). Further analysis suggested no differences in environmental parameters between neophyte and remigrant nests. Thus, while it is possible that different-aged mothers make different nesting-site choices that could affect the nest environment, it is likely that Loggerhead reproductive biology, such as maternal investment, may change over time. More data are required to fully investigate maternal effects on hatching success and to elucidate the mechanisms, both within this species and across multiple species of sea turtles. [ABSTRACT FROM AUTHOR]

Unlike landmark methods for estimating object asymmetry, continuous symmetry measures (CSM) can be used to measure the symmetry distance (ds) of inconsistent objects, such as plant leaves. Inconsistent objects have no homologous landmarks, no consistent topology, no quantitative consistency, and sometimes no matching points. When CSM is used in conjugation with LAMINA Leaf Shape Determination software, one can quickly and efficiently process a large number of scanned leaves. LAMINA automatically generates equally-spaced points around the perimeter of each leaf and the resulting x-y coordinates are normalized to average centroid size prior to estimating ds using a fold, average, unfold algorithm. We estimated shape asymmetry of leaves of three species of flowering plants: Ligustrum sinense (Chinese Privet), Rubus cuneifolius (blackberry), and Perilla frutescens (Perilla), as well as individual leaves from a few species of oaks (Quercus) and maples (Acer). We found that 100 to 200 equally-spaced points worked well for all three of the main species. Measurement error accounted for a small proportion of the asymmetry variation. Nevertheless, measurement error was great enough to generate some negative size scaling after normalization to average centroid size. [ABSTRACT FROM AUTHOR]