Biogeographic Patterns in Life-History Traits of the Yellow Clam, Mesodesma mactroides, in Sandy Beaches of South America - Fiori, Sandra Marcela (2006)
Demographic and life-history attributes of the yellow clam, Mesodesma mactroides, were analyzed along exposed sandy beaches of the Atlantic coast of South America, from Brazil (32ºS) to Argentina (41ºS), covering most of its geographical range (24?41ºS). Population features varied markedly within this range and exhibited systematic geographical patterns of variation. Abundance and growth/mortality rates significantly decreased from northern (Brazil and Uruguay) to southern (Argentina) populations. Snapshot information at the edge of its northern geographical range suggests a large-scale unimodal distribution pattern. Northern populations also had an extended or quasi-continuous recruitment season, whereas Argentinean populations had seasonal recruitment that became negligible at the southernmost edge of the range (41ºS). Maximum individual sizes increased nonlinearly with latitude. This result, when considered together with density patterns, provided the second large-scale evidence of scaling of population density to body size in a sandy-beach population. Lifespan increased with latitude, ranging between 3 and 7 years. Length frequency distribution analysis revealed marked intra-annual growth patterns for two populations located 7 grades latitude apart. Variations in water temperature explained large-scale differences in the demography and population dynamics of the yellow clam, and the high plasticity over latitudinal gradients leads to an adjustment of the phenotype environment relationship. Long-term studies in Uruguayan beaches suggest that wide population fluctuations are the result of intertwined forces of environmental, density-dependent, and human-induced factors operating together at different spatiotemporal scales. As this species with planktonic larvae is structured as a metapopulation, future studies should incorporate a number of hierarchical scales to better understand macroscale variations in demographic patterns and life-history traits