Seasonal Dynamics of Dissolved Iron on the Antarctic Continental Shelf: Late-Fall Observations From the Terra Nova Bay and Ross Ice Shelf Polynyas.

Over the Ross Sea shelf, annual primary production is limited by dissolved iron (DFe) supply. Here, a major source of DFe to surface waters is thought to be vertical resupply from the benthos, which is assumed most prevalent during winter months when katabatic winds drive sea ice formation and convective overturn in coastal polynyas, although the impact of these processes on water-column DFe distributions has not been previously documented. We collected hydrographic data and water-column samples for trace metals analysis in the Terra Nova Bay and Ross Ice Shelf polynyas during April-May 2017 (late austral fall). In the Terra Nova Bay polynya, we observed intense katabatic wind events, and surface mixed layer depths varied from ∼250 to ∼600 m over lateral distances <10 km; there vertical mixing was just starting to excavate the dense, iron-rich Shelf Waters, and there was also evidence of DFe inputs at shallower depths in the water column. In the Ross Ice Shelf polynya, wind speeds were lower, mixed layers were <300 m deep, and DFe distributions were similar to previous, late-summer observations, with concentrations elevated near the seafloor. Corresponding measurements of dissolved manganese and zinc, and particulate iron, manganese, and aluminum, suggest that deep DFe maxima and some mid-depth DFe maxima primarily reflect sedimentary inputs, rather than remineralization. Our data and model simulations imply that vertical resupply of DFe in the Ross Sea occurs mainly during mid-late winter, and may be particularly sensitive to changes in the timing and extent of sea ice production.

Compartmental Model Diagrams as Causal Representations in Relation to DAGs.

Compartmental model diagrams have been used for nearly a century to depict causal relationships in infectious disease epidemiology. Causal directed acyclic graphs (DAGs) have been used more broadly in epidemiology since the 1990s to guide analyses of a variety of public health problems. Using an example from chronic disease epidemiology, the effect of type 2 diabetes on dementia incidence, we illustrate how compartmental model diagrams can represent the same concepts as causal DAGs, including causation, mediation, confounding, and collider bias. We show how to use compartmental model diagrams to explicitly depict interaction and feedback cycles. While DAGs imply a set of conditional independencies, they do not define conditional distributions parametrically. Compartmental model diagrams parametrically (or semiparametrically) describe state changes based on known biological processes or mechanisms. Compartmental model diagrams are part of a long-term tradition of causal thinking in epidemiology and can parametrically express the same concepts as DAGs, as well as explicitly depict feedback cycles and interactions. As causal inference efforts in epidemiology increasingly draw on simulations and quantitative sensitivity analyses, compartmental model diagrams may be of use to a wider audience. Recognizing simple links between these two common approaches to representing causal processes may facilitate communication between researchers from different traditions.

Mortality estimates from ovarian age distributions of the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe suggest the need for new analytical approaches.

Mortality estimates are central to understanding tsetse fly population dynamics, but are difficult to acquire from wild populations. They can be obtained from age distribution data but, with limited data, it is unclear whether the assumptions required to make the estimates are satisfied and, if not, how violations affect the estimates. We evaluate the assumptions required for existing mortality estimation techniques using long-term longitudinal ovarian dissection data from 144,106 female tsetse, Glossina pallidipes Austen, captured in Zimbabwe between 1988 and 1999. At the end of the hot-dry season each year, mean ovarian ages peaked, and maximum-likelihood mortality estimates declined to low levels, contrary to mark-recapture estimates, suggesting violations of the assumptions underlying the estimation technique. We demonstrate that age distributions are seldom stable for G. pallidipes at our study site, and hypothesize that this is a consequence of a disproportionate increase in the mortality of pupae and young adults at the hottest times of the year. Assumptions of age-independent mortality and capture probability are also violated, the latter bias varying with capture method and with pregnancy and nutritional status. As a consequence, mortality estimates obtained from ovarian dissection data are unreliable. To overcome these problems we suggest simulating female tsetse populations, using dynamical modelling techniques that make no assumptions about the stability of the age distribution.

Autumn bloom of antarctic pack-ice algae.

An autumn bloom of sea-ice algae was observed from February to June of 1992 within the upper 0.4 meter of multiyear ice in the Western Weddell Sea, Antarctica. The bloom was reliant on the freezing of porous areas within the ice that initiated a vertical exchange of nutrient-depleted brine with nutrient-rich seawater. This replenishment of nutrients to the algal community allowed the net production of 1760 milligrams of carbon and 200 milligrams of nitrogen per square meter of ice. The location of this autumn bloom is unlike that of spring blooms previously observed in both polar regions.