Dynamic energy budget of endemic and critically endangered bivalve Pinna nobilis: A mechanistic model for informed conservation

Reconstructing the Evolutionary History of Pinna nobilis: New Genetic Signals from the Past of a Species on the Brink of Extinction

Pinna nobilis, commonly known as the noble pen shell, is a marine bivalve endemic to the Mediterranean Sea. Unfortunately, due to a multifactorial disease that began affecting its populations in 2016, the species is currently facing the threat of extinction. To gain insights into the evolutionary history of P. nobilis before the mass mortality event (MME), and to obtain a comprehensive understanding of how evolutionary processes led to the adaptation of the species into the Mediterranean Sea, phylogenetic and phylogeographic analyses were carried out. The dataset analysed includes 469 sequences of COI gene fragment both from GenBank and the present study (100). The analysis performed evidenced that P. nobilis diverged about 2.5 mya, after the entrance of its ancestor into the Mediterranean Sea following the Zanclean flood (5.33 mya). Moreover, our results suggest that the starting point of colonisation was the central part of the western Mediterranean basin, with the eastern basin being populated subsequently. From a conservational viewpoint, these results provide important hints for present and future restocking plans, helping to reconstruct the pre-existing genetic variability in sites where the species became extinct.

A predictive timeline of wildlife population collapse

Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals' behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.

A Dynamic Energy Budget Model for Kuruma Shrimp Penaeus japonicus: Parameterization and Application in Integrated Marine Pond Aquaculture

Individual growth models can form the basis of population dynamics assessment and ecosystem model construction. In order to provide a basic module for an ecosystem model of an integrated marine aquaculture pond, an individual growth model was constructed for kuruma shrimp (Penaeus japonicus) based on dynamic energy budget (DEB) theory. The model was first parameterized based on a covariation method using the Add-my-Pet (AmP) procedure. The parametric estimation model underestimated the ultimate abdominal length for female shrimp, and the predicted values of other zero-variate parameters were generally consistent with observed values. The relative errors of the predicted and observed values of the univariate data set within three geographical regions showed acceptable goodness of fit. Parameter estimation achieved an overall goodness of fit with a mean relative error of 0.048 and a symmetric mean squared error of 0.066. A DEB model was constructed using the estimated parameters, and the goodness-of-fit indicators (R square, mean bias and absolute and relative root mean square error) showed that the model was able to reproduce the growth of kuruma shrimp in terms of total length and wet weight with high accuracy. The results provide data to support the subsequent development of integrated aquaculture management at the ecosystem level.

Dynamic energy budget modeling of Atlantic surfclam, Spisula solidissima, under future ocean acidification and warming

A dynamic energy budget (DEB) model integrating pCO₂ was used to describe ocean acidification (OA) effects on Atlantic surfclam, Spisula solidissima, bioenergetics. Effects of elevated pCO₂ on ingestion and somatic maintenance costs were simulated, validated, and adapted in the DEB model based upon growth and biological rates acquired during a 12-week laboratory experiment. Temperature and pCO₂ were projected for the next 100 years following the intergovernmental panel on climate change representative concentration pathways scenarios (2.6, 6.0, and 8.5) and used as forcing variables to project surfclam growth and reproduction. End-of-century water warming and acidification conditions resulted in simulated faster growth for young surfclams and more energy allocated to reproduction until the beginning of the 22nd century when a reduction in maximum shell length and energy allocated to reproduction was observed for the RCP 8.5 scenario.

Multidimensional scaling for animal traits in the context of dynamic energy budget theory

The method of multidimensional scaling (MDS) has long existed, but could only recently be applied to animal traits in the context of dynamic energy budget (DEB) theory. The application became possible because of the following: (i) the Add-my-Pet (AmP) collection of DEB parameters and traits (approximately 280) recently reached 3000 animal species with 45000 data sets of measurements; (ii) we found a natural distance measure for species based on their traits as a side result of our research on parameter estimation in DEB context; and (iii) we developed plotting code for visualization that allows labelling of taxonomic relationships. Traits, here defined as DEB parameters or any function of these parameters, have different dimensions, which hamper application of many popular distance measures since they (implicitly) assume that all traits have the same dimensions. The AmP collection follows the workflow that measured data determine parameters and parameters determine trait values. In this way we could fill up the species traits table completely, which we could not do by using measured values only, as data availability varies considerably between species and is typically poor. The goodness of fit of predictions for all data sets is generally excellent. This paper discusses links between the MDS method and parameter estimation and illustrates the application of MDS for the AmP collection to five taxa, three ectothermic and two endothermic, which we consider to be 'complete', in the sense that we expect that it will be difficult to find more species with data in the open literature. This application of MDS shows links between traits and taxonomy that supplements our efforts to find patterns in the co-variation of parameter values. Knowledge about metabolic performance is key to conservation biology, sustainable management and environmental risk assessment, which are seen as interlinked fields.