Tropical Marginal Seas: Priority Regions for Managing Marine Biodiversity and Ecosystem Function

Tropical marginal seas (TMSs) are natural subregions of tropical oceans containing biodiverse ecosystems with conspicuous, valued, and vulnerable biodiversity assets. They are focal points for global marine conservation because they occur in regions where human populations are rapidly expanding. Our review of 11 TMSs focuses on three key ecosystems—coral reefs and emergent atolls, deep benthic systems, and pelagic biomes—and synthesizes, illustrates, and contrasts knowledge of biodiversity, ecosystem function, interaction between adjacent habitats, and anthropogenic pressures. TMSs vary in the extent that they have been subject to human influence—from the nearly pristine Coral Sea to the heavily exploited South China and Caribbean Seas—but we predict that they will all be similarly complex to manage because most span multiple national jurisdictions. We conclude that developing a structured process to identify ecologically and biologically significant areas that uses a set of globally agreed criteria is a tractable first step toward effective multinational and transboundary ecosystem management of TMSs.

The marginal willingness-to-pay for attributes of a hypothetical HIV vaccine

This paper estimates the marginal willingness-to-pay for attributes of a hypothetical HIV vaccine using discrete choice modeling. We use primary data from 326 respondents from Bangkok and Chiang Mai, Thailand, in 2008–2009, selected using purposive, venue-based sampling across two strata. Participants completed a structured questionnaire and full rank discrete choice modeling task administered using computer-assisted personal interviewing. The choice experiment was used to rank eight hypothetical HIV vaccine scenarios, with each scenario comprising seven attributes (including cost) each of which had two levels. The data were analyzed in two alternative specifications: (1) best-worst; and (2) full-rank, using logit likelihood functions estimated with custom routines in Gauss matrix programming language. In the full-rank specification, all vaccine attributes are significant predictors of probability of vaccine choice. The biomedical attributes of the hypothetical HIV vaccine (efficacy, absence of VISP, absence of side effects, and duration of effect) are the most important attributes for HIV vaccine choice. On average respondents are more than twice as likely to accept a vaccine with 99% efficacy, than a vaccine with 50% efficacy. This translates to a willingness to pay US$383 more for a high efficacy vaccine compared with the low efficacy vaccine. Knowledge of the relative importance of determinants of HIV vaccine acceptability is important to ensure the success of future vaccination programs. Future acceptability studies of hypothetical HIV vaccines should use more finely grained biomedical attributes, and could also improve the external validity of results by including more levels of the cost attribute.

Middle to late Holocene chironomid-inferred July temperatures for the central Northwest Territories, Canada

We analyzed subfossil chironomids, sediment organic matter and sediment particle size data from a 1.11-m-long freeze core collected from Carleton Lake (unofficial name), located approximately 120 km north of the modern treeline. This well-dated core spans the last ca. 6,500 years. Two chironomid transfer functions were applied to infer mean July air temperatures. Our results indicated that the chironomid-inferred temperatures from this lake sediment record did not pass a significance test, suggesting that other factors in addition to temperature may have been important in structuring the chironomid community through time. Although not statistically significant, the chironomid-inferred temperatures from this site do follow a familiar pattern, with highest inferred temperatures occurring during the Holocene Thermal Maximum (~6–4 cal kyr BP), followed by a long-term cooling trend, which is reversed during the last 600 years. The largest change in the chironomid assemblage, which occurred between ca. 4,600 and 3,900 cal yr BP is possibly related to the well-documented northward advance and subsequent retreat of treeline in this region.

mfx: Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs

Estimates probit, logit, Poisson, negative binomial, and beta regression models, returning their marginal effects, odds ratios, or incidence rate ratios as an output.

Efficient Marginal Likelihood Computation for Gaussian Process Regression

In a Bayesian learning setting, the posterior distribution of a predictive model arises from a trade-off between its prior distribution and the conditional likelihood of observed data. Such distribution functions usually rely on additional hyperparameters which need to be tuned in order to achieve optimum predictive performance; this operation can be efficiently performed in an Empirical Bayes fashion by maximizing the posterior marginal likelihood of the observed data. Since the score function of this optimization problem is in general characterized by the presence of local optima, it is necessary to resort to global optimization strategies, which require a large number of function evaluations. Given that the evaluation is usually computationally intensive and badly scaled with respect to the dataset size, the maximum number of observations that can be treated simultaneously is quite limited. In this paper, we consider the case of hyperparameter tuning in Gaussian process regression. A straightforward implementation of the posterior log-likelihood for this model requires O(N^3) operations for every iteration of the optimization procedure, where N is the number of examples in the input dataset. We derive a novel set of identities that allow, after an initial overhead of O(N^3), the evaluation of the score function, as well as the Jacobian and Hessian matrices, in O(N) operations. We prove how the proposed identities, that follow from the eigendecomposition of the kernel matrix, yield a reduction of several orders of magnitude in the computation time for the hyperparameter optimization problem. Notably, the proposed solution provides computational advantages even with respect to state of the art approximations that rely on sparse kernel matrices.

Sediment accumulation rates in subarctic lakes: insights into age-depth modeling from 22 dated lake records from the Northwest Territories, Canada

Age-depth modeling using Bayesian statistics requires well-informed prior information about the behavior of sediment accumulation. Here we present average sediment accumulation rates (represented as deposition times, DT, in yr/cm) for lakes in an Arctic setting, and we examine the variability across space (intra- and inter-lake) and time (late Holocene). The dataset includes over 100 radiocarbon dates, primarily on bulk sediment, from 22 sediment cores obtained from 18 lakes spanning the boreal to tundra ecotone gradients in subarctic Canada. There are four to twenty-five radiocarbon dates per core, depending on the length and character of the sediment records. Deposition times were calculated at 100-year intervals from age-depth models constructed using the ‘classical’ age-depth modeling software Clam. Lakes in boreal settings have the most rapid accumulation (mean DT 20 ± 10 years), whereas lakes in tundra settings accumulate at moderate (mean DT 70 ± 10 years) to very slow rates, (>100 yr/cm). Many of the age-depth models demonstrate fluctuations in accumulation that coincide with lake evolution and post-glacial climate change. Ten of our sediment cores yielded sediments as old as c. 9,000 cal BP (BP = years before AD 1950). From between c. 9,000 cal BP and c. 6,000 cal BP, sediment accumulation was relatively rapid (DT of 20 to 60 yr/cm). Accumulation slowed between c. 5,500 and c. 4,000 cal BP as vegetation expanded northward in response to warming. A short period of rapid accumulation occurred near 1,200 cal BP at three lakes. Our research will help inform priors in Bayesian age modeling.