Chinook salmon depth distributions on the continental shelf are shaped by interactions between location, season, and individual condition.

BACKGROUND: Ecological and physical conditions vary with depth in aquatic ecosystems, resulting in gradients of habitat suitability. Although variation in vertical distributions among individuals provides evidence of habitat selection, it has been challenging to disentangle how processes at multiple spatio-temporal scales shape behaviour. METHODS: We collected thousands of observations of depth from > 300 acoustically tagged adult Chinook salmon Oncorhynchus tshawytscha, spanning multiple seasons and years. We used these data to parameterize a machine-learning model to disentangle the influence of spatial, temporal, and dynamic oceanographic variables while accounting for differences in individual condition and maturation stage. RESULTS: The top performing machine learning model used bathymetric depth ratio (i.e., individual depth relative to seafloor depth) as a response. We found that bathymetry, season, maturation stage, and spatial location most strongly influenced Chinook salmon depth. Chinook salmon bathymetric depth ratios were deepest in shallow water, during winter, and for immature individuals. We also identified non-linear interactions among covariates, resulting in spatially-varying effects of zooplankton concentration, lunar cycle, temperature and oxygen concentration. CONCLUSIONS: Our results suggest Chinook salmon vertical habitat use is a function of ecological interactions, not physiological constraints. Temporal and spatial variation in depth distributions could be used to guide management decisions intended to reduce fishery impacts on Chinook salmon. More generally, our findings demonstrate how complex interactions among bathymetry, seasonality, location, and life history stage regulate vertical habitat selection.

Real-world exhaust temperature and engine load distributions of on-road heavy-duty diesel vehicles in various vocations.

Real-world vehicle and engine activity data were collected from 90 heavy-duty vehicles in California, United States, most of which have engine model year 2010 or newer and are equipped with selective catalytic reduction (SCR). The 90 vehicles represent 19 different groups defined by a combination of vocational use and geographic region. The data were collected using advanced data loggers that recorded vehicle speed, position (latitude and longitude), and more than 170 engine and aftertreatment parameters (including engine load and exhaust temperature) at the frequency of one Hz. This article presents plots of real-world exhaust temperature and engine load distributions for the 19 vehicle groups. In each plot, both frequency distribution and cumulative frequency distribution are shown. These distributions are generated using the aggregated data from all vehicle samples in each group.

Real-world exhaust temperature profiles of on-road heavy-duty diesel vehicles equipped with selective catalytic reduction.

On-road heavy-duty diesel vehicles are a major contributor of oxides of nitrogen (NOx) emissions. In the US, many heavy-duty diesel vehicles employ selective catalytic reduction (SCR) technology to meet the 2010 emission standard for NOx. Typically, SCR needs to be at least 200°C before a significant level of NOx reduction is achieved. However, this SCR temperature requirement may not be met under some real-world operating conditions, such as during cold starts, long idling, or low speed/low engine load driving activities. The frequency of vehicle operation with low SCR temperature varies partly by the vehicle's vocational use. In this study, detailed vehicle and engine activity data were collected from 90 heavy-duty vehicles involved in a range of vocations, including line haul, drayage, construction, agricultural, food distribution, beverage distribution, refuse, public work, and utility repair. The data were used to create real-world SCR temperature and engine load profiles and identify the fraction of vehicle operating time that SCR may not be as effective for NOx control. It is found that the vehicles participated in this study operate with SCR temperature lower than 200°C for 11-70% of the time depending on their vocation type. This implies that real-world NOx control efficiency could deviate from the control efficiency observed during engine certification.

Fine-scale spatial genetic structure of a fungal parasite of coffee scale insects.

The entomopathogenic fungus Lecanicillium lecanii persists in a highly dynamic network of habitat patches (i.e., a metapopulation) formed by its primary host, the green coffee scale Coccus viridis. Lecanicillium lecanii is an important biological control of both C. viridis and the coffee rust, Hemileia vastatrix. Successfully managing this biocontrol agent will depend on an increased understanding of the characteristics of its dispersal, as migration between occupied and unoccupied patches is essential for the persistence of this metapopulation. In the present study, we employ a population genetics approach, and show that in our study system, a coffee farm in the Soconusco region of southern Mexico, L. lecanii is characterized by clear spatial genetic structure among plots within the farm but a lack of apparent structure at smaller scales. This is consistent with dispersal dominated by highly localized transport, such as by insects or rain splash, and less dependence on longer distance dispersal such as wind transport. The study site was dominated by a few multi-locus microsatellite genotypes, and their identities and large-scale locations persist across both study years, suggesting that local epizootics (outbreaks) are initiated each wet season by residual propagules from the previous wet season, and not by long-distance transport of propagules from other sites. The index of association, a measure of linkage disequilibrium, indicates that epizootics are primarily driven by asexual, clonal reproduction, which is consistent with the apparent lack of a teleomorph in the study site and the presence of only a single mating type across the site (MAT-1-2-1). Although the same predominant clonal genotypes were found across years, a drastic difference in genotypic diversity was witnessed across two sites between the two years, suggesting that interclonal selection was occurring. In light of the dispersal limitation of L. lecanii, spatial structure may be an essential axis of management to ensure the persistence of L. lecanii and preserve the ecosystem services provided by this versatile biocontrol agent in this and similar coffee farms.

Population responses to environmental change in a tropical ant: the interaction of spatial and temporal dynamics.

Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.

Ecological complexity in a coffee agroecosystem: spatial heterogeneity, population persistence and biological control.

BACKGROUND: Spatial heterogeneity is essential for the persistence of many inherently unstable systems such as predator-prey and parasitoid-host interactions. Since biological interactions themselves can create heterogeneity in space, the heterogeneity necessary for the persistence of an unstable system could be the result of local interactions involving elements of the unstable system itself. METHODOLOGY/PRINCIPAL FINDINGS: Here we report on a predatory ladybird beetle whose natural history suggests that the beetle requires the patchy distribution of the mutualism between its prey, the green coffee scale, and the arboreal ant, Azteca instabilis. Based on known ecological interactions and the natural history of the system, we constructed a spatially-explicit model and showed that the clustered spatial pattern of ant nests facilitates the persistence of the beetle populations. Furthermore, we show that the dynamics of the beetle consuming the scale insects can cause the clustered distribution of the mutualistic ants in the first place. CONCLUSIONS/SIGNIFICANCE: From a theoretical point of view, our model represents a novel situation in which a predator indirectly causes a spatial pattern of an organism other than its prey, and in doing so facilitates its own persistence. From a practical point of view, it is noteworthy that one of the elements in the system is a persistent pest of coffee, an important world commodity. This pest, we argue, is kept within limits of control through a complex web of ecological interactions that involves the emergent spatial pattern.