Dataset Information

Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve.

ABSTRACT: Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a 'reversed manner' may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate between years t and t+1 correlated strongly with the proportion of individuals living in the dangerous top 4 cm layer of the sediment in year t: the more individuals in the top layer, the steeper the population decline. This is consistent with the prediction based on optimal foraging theory that animals with poor prospects should accept greater risks of predation. This study is among the first to document fitness forecasting in animals.

SUBMITTER: van Gils JA

PROVIDER: S-EPMC2657738 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve.

van Gils Jan A JA Kraan Casper C Dekinga Anne A Koolhaas Anita A Drent Jan J de Goeij Petra P Piersma Theunis T

Biology letters 20090201 1

Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a 'reversed manner' may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate betw ...[more]

PMID: 18940769

Similar Datasets

Project description:Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Project description:BackgroundSkulls serve many functions and as a result, are subject to many different evolutionary pressures. In squamates, many fossorial species occupy a unique region of skull morphospace, showing convergence across families, due to modifications related to head-first burrowing. As different substrates have variable physical properties, particular skull shapes may offer selective advantages in certain substrates. Despite this, studies of variation within burrowers have been limited and are typically focused on a single origin of fossoriality. We focused on seven skink genera (Acontias, Typhlosaurus, Scelotes, Sepsina, Feylinia, Typhlacontias, and Mochlus; 39 sp.) from southern Africa, encompassing at least three independent evolutions of semi-fossoriality/fossoriality. We used microCT scans and geometric morphometrics to test how cranial and mandibular shape were influenced by phylogenetic history, size, and ecology. We also qualitatively described the skulls of four species to look at variation across phylogenetic and functional levels, and assess the degree of convergence.ResultsWe found a strong effect of phylogenetic history on cranial and mandibular shape, with size and substrate playing secondary roles. There was a clear gradient in morphospace from less specialized to more specialized burrowers and burrowers in sand were significantly different from those in other substrates. We also created an anatomical atlas for four species with each element described in isolation. Every bone showed some variation in shape and relative scaling of features, with the skull roofing bones, septomaxilla, vomer, and palatine showing the most variation. We showed how broad-scale convergence in traits related to fossoriality can be the result of different anatomical changes.ConclusionsOur study used geometric morphometrics and comparative anatomy to examine how skull morphology changes for a highly specialized and demanding lifestyle. Although there was broad convergence in both shape and qualitative traits, phylogenetic history played a large role and much of this convergence was produced by different anatomical changes, implying different developmental pathways or lineage-specific constraints. Even within a single family, adaptation for a specialized ecology does not follow a singular deterministic path.

Project description:BackgroundMarine lineage diversification is shaped by the interaction of biotic and abiotic factors but our understanding of their relative roles is underdeveloped. The megadiverse bivalve superfamily Galeommatoidea represents a promising study system to address this issue. It is composed of small-bodied clams that are either free-living or have commensal associations with invertebrate hosts. To test if the evolution of this lifestyle dichotomy is correlated with specific ecologies, we have performed a statistical analysis on the lifestyle and habitat preference of 121 species based on 90 source documents.Methodology/principal findingsGaleommatoidea has significant diversity in the two primary benthic habitats: hard- and soft-bottoms. Hard-bottom dwellers are overwhelmingly free-living, typically hidden within crevices of rocks/coral heads/encrusting epifauna. In contrast, species in soft-bottom habitats are almost exclusively infaunal commensals. These infaunal biotic associations may involve direct attachment to a host, or clustering around its tube/burrow, but all commensals locate within the oxygenated sediment envelope produced by the host's bioturbation.Conclusions/significancethe formation of commensal associations by Galeommatoidean clams is robustly correlated with an abiotic environmental setting: living in sediments (P < 0.001). Sediment-dwelling bivalves are exposed to intense predation pressure that drops markedly with depth of burial. Commensal galeommatoideans routinely attain depth refuges many times their body lengths, independent of siphonal investment, by virtue of their host's burrowing and bioturbation. In effect, they use their much larger hosts as giant auto-irrigating siphon substitutes. The evolution of biotic associations with infaunal bioturbating hosts may have been a prerequisite for the diversification of Galeommatoidea in sediments and has likely been a key factor in the success of this exceptionally diverse bivalve superfamily.

Dataset Information

Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve.

Publications

Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets