Using a fisheries ecosystem model with a water quality model to explore trophic and habitat impacts on a fisheries stock: A case study of the blue crab population in the Chesapeake Bay

Recent calls for the development of ecosystem-based fisheries management compel the development of resource management tools and linkages between existing fisheries management tools and other resource tools to enable assessment and management of multiple impacts on fisheries resources. In this paper, we describe the use of the Chesapeake Bay Fisheries Ecosystem Model (CBFEM), developed using the Ecopath with Ecosim (EwE) software, and the Chesapeake Bay Water Quality Model (WQM) to demonstrate how linkages between available modeling tools can be used to inform ecosystem-based natural resource management. The CBFEM was developed to provide strategic ecosystem information in support of fisheries management. The WQM was developed to assess impacts on water quality. The CBFEM was indirectly coupled with the WQM to assess the effects of water quality and submerged aquatic vegetation (SAV) on blue crabs. The output from two WQM scenarios (1985-1994), a baseline scenario representing actual nutrient inputs and another with reduced inputs based on a tributary management strategy, was incorporated into the CBFEM. The results suggested that blue crab biomass could be enhanced under management strategies (reduced nutrient input) when the effective search rate of blue crab young-of-the-year's (YOY's) predators or the vulnerability of blue crab YOY to its predators was adjusted by SAV. Such model linkages are important for incorporating physical and biological components of ecosystems in order to explore ecosystem-based fisheries management options.     

Soil drying in a tropical forest: Three distinct environments controlled by gap size

Soil water and temperature regimes in the tropical moist forest on Barro Colorado Island, Panama, were simulated directly from meteorological data using the model SWEAT. Separate field observations from root-exclusion, litter-removal and control treatments in one small and one large forest gap were used for calibration and validation. After irrigating all treatments to field capacity, soil matric potential and temperature were measured over 17 days at four depths ≤50 mm using the filter-paper technique and bead thermistors. Understorey environments were also simulated under the same initial conditions. The results suggest that three distinct scenarios, controlled by gap size, describe how the above- and below-ground processes controlling soil drying are coupled: (1) in the large gap, root water extraction by surrounding trees is negligible so soil drying is dominated by evaporation from the soil surface. Soil temperature is dominated by direct solar heating and cooling due to evaporation. (2) In the small gap, root water extraction dominates soil drying with soil evaporation playing a minor role. Soil temperature is still dominated by direct sunlight with some cooling due to evaporation. (3) In the understorey, root water extraction dominates soil drying. Soil temperature is dominated by heat conduction from deep soil layers with some evaporation and sensible heat transfer. The contrasting soil drying regimes imposed by variation in canopy structure enhance micro-environmental heterogeneity and the scope for differential germination and seedling establishment in coexisting tropical tree species.     

A new approach to graphical and numerical analysis of links between plant chemotaxonomy and secondary metabolism from HPLC data smoothed by a simplex mixture design

Summary. HPLC analysis of secondary metabolites represents an efficient tool for the studying of plant chemical diversity under different aspects: chemotaxonomy, metabolomics, adaptative responses to ecological factors, etc. Statistical analyses of HPLC databases, e.g. correlation analysis between HPLC peaks, can reliably provide information on the similarity/dissimilarity degrees between the chemical compounds. The similarities, corresponding to positive correlations, can be interpreted in terms of analogies between chemical structures, synchronic metabolisms or co-evolution of two compounds under certain environment conditions, etc. . In terms of metabolism, positive correlations can translate precursor-product relationships between compounds; negative correlations can be indicative of competitive processes between two compounds for a common precursor(s), enzyme(s) or substrate(s). Furthermore, the correlation analysis under a metabolic aspect can help to understand the biochemical origins of an observed polymorphism in a plant species. With the aim of showing this, we present a new approach based on a simplex mixture design, Scheffé matrix, which provides a correlation network making it possible to graphically visualise and to numerically model the metabolic trends between HPLC peaks. The principle of the approach consisted in mixing individual HPLC profiles representative of different phenotypes, then from a complete mixture set, a series of average profiles were calculated to provide a new database with a small variability. Several iterations of the mixture design provided a smoothed final database from which the relationships between the secondary metabolites were graphically and numerically analysed. These relationships were scale-dependent, namely either deterministic or systematic: the first consisted of a monotonic global trend covering the whole variation field of each metabolites’ pair; the second consisted of repetitive monotonic variations which gradually attenuated or intensified along a global trend. This new metabolomic approach was illustrated from 404 individual plants of Astragalus caprinus (Leguminoseae), belonging to four chemical phenotypes (chemotypes) on the basis of flavonoids analysed in their leaves. After smoothing, the relationships between flavonoids were numerically fitted using linear or polynomial models; therefore the co-response coefficients were easily interpreted in terms of metabolic affinities or competitions between flavonoids which would be responsible of the observed chemical polymorphism (the four chemotypes). The statistical validation of the approach was carried out by comparing Pearson correlations to Spearman correlations calculated from the smoothed and the crude HPLC database, respectively. Moreover, the signs of the smoothed relationships were finely supported by analogies and differences between the chemical structures of flavonoids, leading to fluent interpretation in relation to the pathway architecture.     

Using an individual-based model to quantify scale transition in demographic rate functions: Deaths in a coral reef fish

Scientifically informed population management requires quantitatively accurate demographic rate functions that apply at the spatial scale at which populations are actually managed, but practical constraints confine most field measurements of such functions to small study plots. This paper employs an individual-based population growth model to extrapolate the death rate function in a well-studied coral reef fish, the bridled goby Coryphopterus glaucofraenum, from the scale of coral reef “cells” at which it was measured to the larger scale of an entire coral reef. Density dependence in the whole-reef function actually proves stronger than in the local function because high goby density occasionally arises in local patches with few refuges from predators, producing very high mortality there. This IBM-based approach extends the reach of scale transition theory by examining considerably more realistic models than standard analytical methods can presently handle.