A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models

We consider the estimation of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods

Parasite infections in a social carnivore: Evidence of their fitness consequences and factors modulating infection load

There are substantial individual differences in parasite composition and infection load in wildlife populations. Few studies have investigated the factors shaping this heterogeneity in large wild mammals or the impact of parasite infections on Darwinian fitness, particularly in juveniles. A host's parasite composition and infection load can be shaped by factors that determine contact with infective parasite stages and those that determine the host's resistance to infection, such as abiotic and social environmental factors, and age. Host–parasite interactions and synergies between coinfecting parasites may also be important. We test predictions derived from these different processes to investigate factors shaping infection loads (fecal egg/oocyte load) of two energetically costly gastrointestinal parasites: the hookworm Ancylostoma and the intracellular Cystoisospora, in juvenile spotted hyenas (Crocuta crocuta) in the Serengeti National Park, in Tanzania. We also assess whether parasite infections curtail survival to adulthood and longevity. Ancylostoma and Cystoisospora infection loads declined as the number of adult clan members increased, a result consistent with an encounter‐reduction effect whereby adults reduced encounters between juveniles and infective larvae, but were not affected by the number of juveniles in a clan. Infection loads decreased with age, possibly because active immune responses to infection improved with age. Differences in parasite load between clans possibly indicate variation in abiotic environmental factors between clan den sites. The survival of juveniles (<365 days old) to adulthood decreased with Ancylostoma load, increased with age, and was modulated by maternal social status. High‐ranking individuals with low Ancylostoma loads had a higher survivorship during the first 4 years of life than high‐ranking individuals with high Ancylostoma loads. These findings suggest that high infection loads with energetically costly parasites such as hookworms during early life can have negative fitness consequences

Even obligate symbioses show signs of ecological contingency: Impacts of symbiosis for an invasive stinkbug are mediated by host plant context

Many species interactions are dependent on environmental context, yet the benefits of obligate, mutualistic microbial symbioses to their hosts are typically assumed to be universal across environments. We directly tested this assumption, focusing on the symbiosis between the sap‐feeding insect Megacopta cribraria and its primary bacterial symbiont Candidatus Ishikawaella capsulata. We assessed host development time, survival, and body size in the presence and absence of the symbiont on two alternative host plants and in the insects\u27 new invasive range. We found that association with the symbiont was critical for host survival to adulthood when reared on either host plant, with few individuals surviving in the absence of symbiosis. Developmental differences between hosts with and without microbial symbionts, however, were mediated by the host plants on which the insects were reared. Our results support the hypothesis that benefits associated with this host–microbe interaction are environmentally contingent, though given that few individuals survive to adulthood without their symbionts, this may have minimal impact on ecological dynamics and current evolutionary trajectories of these partners

Interplay between topography, fog and vegetation in the central South Arabian mountains revealed using a novel Landsat fog detection technique

In the central South Arabian mountains of Yemen and Oman, monsoon fog interception by the endemic cloud forest is essential for ecosystem functions and services. Yet, we know little about the local factors affecting fog distributions and their cumulative effects on vegetation. To examine these relationships, we developed a novel method of high-resolution fog detection using Landsat data, and validated the results using occurrence records of eight moisture-sensitive plant species. Regression tree analysis was then used to examine the topographic factors influencing fog distributions and the topoclimatic factors influencing satellite-derived vegetation greenness. We find that topography affects fog distributions. Specifically, steep windward slopes obstruct the inland movement of fog, resulting in heterogenous fog densities and hotspots of fog interception. We find that fog distributions explain patterns of vegetation greenness, and overall, that greenness increases with fog density. The layer of fog density describes patterns of vegetation greenness more accurately than topographic variables alone, and thus, we propose that regional vegetation patterns more closely follow a fog gradient, than an altitudinal gradient as previously supposed. The layer of fog density will enable an improved understanding of how species and communities, many of which are endemic, range-restricted, and in decline, respond to local variability in topoclimatic conditions

Social learning within and across predator species reduces attacks on novel aposematic prey

To make adaptive foraging decisions, predators need to gather information about the profitability of prey. As well as learning from prey encounters, recent studies show that predators can learn about prey defences by observing the negative foraging experiences of conspecifics. However, predator communities are complex. While observing heterospecifics may increase learning opportunities, we know little about how social information use varies across predator species. Social transmission of avoidance among predators also has potential consequences for defended prey. Conspicuous aposematic prey are assumed to be an easy target for naive predators, but this cost may be reduced if multiple predators learn by observing single predation events. Heterospecific information use by predators might further benefit aposematic prey, but this remains untested. Here we test conspecific and heterospecific information use across a predator community with wild-caught blue tits (Cyanistes caeruleus) and great tits (Parus major). We used video playback to manipulate social information about novel aposematic prey and then compared birds' foraging choices in 'a small-scale novel world' that contained novel palatable and aposematic prey items. We expected that blue tits would be less likely to use social information compared to great tits. However, we found that both blue tits and great tits consumed fewer aposematic prey after observing a negative foraging experience of a demonstrator. In fact, this effect was stronger in blue tits compared to great tits. Interestingly, blue tits also learned more efficiently from watching conspecifics, whereas great tits learned similarly regardless of the demonstrator species. Together, our results indicate that social transmission about novel aposematic prey occurs in multiple predator species and across species boundaries. This supports the idea that social interactions among predators can reduce attacks on aposematic prey and therefore influence selection for prey defences.Peer reviewe

Life history alterations upon oral and hemocoelic bacterial exposure in the butterfly Melitaea cinxia

Life history strategies often shape biological interactions by specifying the parameters for possible encounters, such as the timing, frequency, or way of exposure to parasites. Consequentially, alterations in life-history strategies are closely intertwined with such interaction processes. Understanding the connection between life-history alterations and host-parasite interactions can therefore be important to unveil potential links between adaptation to environmental change and changes in interaction processes. Here, we studied how two different host-parasite interaction processes, oral and hemocoelic exposure to bacteria, affect various life histories of the Glanville fritillary butterfly Melitaea cinxia. We either fed or injected adult butterflies with the bacterium Micrococcus luteus and observed for differences in immune defenses, reproductive life histories, and longevity, compared to control exposures. Our results indicate differences in how female butterflies adapt to the two exposure types. Orally infected females showed a reduction in clutch size and an earlier onset of reproduction, whereas a reduction in egg weight was observed for hemocoelically exposed females. Both exposure types also led to shorter intervals between clutches and a reduced life span. These results indicate a relationship between host-parasite interactions and changes in life-history strategies. This relationship could cast restrictions on the ability to adapt to new environments and consequentially influence the population dynamics of a species in changing environmental conditions.Peer reviewe

Bayesian Classification and Regression Trees for Predicting Incidence of Cryptosporidiosis

Background Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. Methodology/Principal Findings We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR) model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. Conclusions/Significance A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control

Behavior of QQ-Plots and Genomic Control in Studies of Gene-Environment Interaction

Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in GE work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in GE GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in GE GWAS can alleviate this problem

Artificial selection for increased dispersal results in lower fitness

Dispersal often covaries with other traits, and this covariation was shown to have a genetic basis. Here, we wanted to explore to what extent genetic constraints and correlational selection can explain patterns of covariation between dispersal and key life-history traits-lifespan and reproduction. A prediction from the fitness-associated dispersal hypothesis was that lower genetic quality is associated with higher dispersal propensity as driven by the benefits of genetic mixing. We wanted to contrast it with a prediction from a different model that individuals putting more emphasis on current rather than future reproduction disperse more, as they are expected to be more risk-prone and exploratory. However, if dispersal has inherent costs, this will also result in a negative genetic correlation between higher rates of dispersal and some aspects of performance. To explore this issue, we used the dioecious nematode Caenorhabditis remanei and selected for increased and decreased dispersal propensity for 10 generations, followed by five generations of relaxed selection. Dispersal propensity responded to selection, and females from high-dispersal lines dispersed more than females from low-dispersal lines. Females selected for increased dispersal propensity produced fewer offspring and were more likely to die from matricide, which is associated with a low physiological condition in Caenorhabditis nematodes. There was no evidence for differences in age-specific reproductive effort between high- and low-dispersal females. Rather, reproductive output of high-dispersal females was consistently reduced. We argue that our data provide support for the fitness-associated dispersal hypothesis