Food quality influences density-dependent fitness, but not always density-dependent habitat selection, in red flour beetles (Coleoptera: Tenebrionidae)

Density-dependent habitat selection models inherently rely on the negative relationship between population density and mean fitness in different habitats. Habitats differing in quality, such as different food sources or habitat structure, can have different strengths of density-dependent relationships, which can then affect patterns of density dependence in habitat selection. We tested the hypothesis that density dependence in fitness dictates the patterns in density-dependent habitat selection: individuals should prefer higher-quality habitat over lower-quality habitat. We used controlled experiments with red flour beetles (Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae)) to measure density dependence of fitness and to examine density-dependent habitat selection by beetles in wheat (Triticum Linnaeus (Poaceae)), corn (Zea mays Linnaeus (Poaceae)), and soy (Glycine max (Linnaeus) Merrill (Fabaceae)) flour habitats. Despite large differences in fitness between habitats (fitness was the highest in wheat flour, lower in corn flour, and zero in soy flour), beetles showed only weak preference for wheat over corn flour and for corn over soy flour, but showed strong preference for wheat over soy flour. These preferences were the strongest at low density. This study gives insight into the relationship between habitat quality and density-dependent habitat selection in flour beetles.

The influence of complex structure on the spatial dynamics of Atlantic cod (Gadus morhua) in the Gulf of Maine

Atlantic cod (Gadus morhua) in the Gulf of Maine (GOM) is an iconic marine fishery stock that has experienced a substantial distributional shift since the mid-1990s. A geostatistical delta-generalized linear mixed model was utilized to hindcast yearly season-specific distributions of GOM cod. These distributions were calculated using the spring and fall bottom trawl survey data for the stock, along with cell-based bathymetry and bottom temperature data for the study area for the years 1982–2013. The centre of stock distribution (the centre of gravity), spatial extent in latitude and longitude, area occupied and median habitat temperature were estimated annually to quantify changes in the spatial dynamics of GOM cod. Time series of these distributional metrics were then used to evaluate the influences of climate change and density-dependent habitat selection on GOM cod’s distribution. Results showed that the rapid southwestward shift in the stock distribution after the late 1990s could not simply be attributed to decreasing stock abundance or warming bottom temperatures. The observed shift in cod distribution requires further investigation on whether it is possibly a result of other factors, like fluctuating productivity among subpopulations.

Spatial reference points for groundfish

According to density-dependent habitat selection theory, areas of high density can be indicative of high population productivity and have positive individual fitness consequences. Here, we explore six groundfish populations on the Scotian Shelf, Canada, where a decline in areas of high density beyond a certain threshold is associated with disproportionately large declines in Spawning Stock Biomass (SSB). This is evidenced by empirical, concave, positive relationships between high-density areas (HDAs) and SSB. We introduce a methodology to estimate the threshold below which SSB declines increasingly faster per unit of HDA decline. The spatial threshold among these six stocks was remarkably consistent; when stocks lose 70–80% of HDAs, disproportionately large SSB declines are likely to occur. We propose that spatial thresholds could serve as spatial reference points to complement existing SSB limit reference points (LRPs). For some stocks we identify spatial thresholds which correspond to SSB levels that exceed those associated with the designated SSB LRP, suggesting that a review of these SSB LRPs warrants merit. For other stocks, spatial reference points can be used in concert with SSB reference points, strengthening efforts to incorporate a precautionary approach to fisheries management. Our results warrant further research into the general application of HDA as spatial limit and target reference points for fisheries management in addition to other population status indicators within a broad recovery framework.