The 10kTrees website: A new online resource for primate phylogeny

The comparative method plays a central role in efforts to uncover the adaptive basis for primate behaviors, morphological traits, and cognitive abilities. 1 - 4 The comparative method has been used, for example, to infer that living in a larger group selects for a larger neocortex, 5 , 6 that primate territoriality favors a longer day range relative to home range size, 7 and that sperm competition can account for the evolution of primate testes size. 8 , 9 Comparison is fundamental for reconstructing behavioral traits in the fossil record, for example, in studies of locomotion and diet. 10 - 13 Recent advances in comparative methods require phylogenetic information, 2 , 14 - 16 but our knowledge of phylogenetic information is imperfect. In the face of uncertainty about evolutionary relationships, which phylogeny should one use? Here we provide a new resource for comparative studies of primates that enables users to run comparative analyses on multiple primate phylogenies Importantly, the 10,000 trees that we provide are not random, but instead use recent systematic methods to create a plausible set of topologies that reflect our certainty about some nodes on the tree and uncertainty about other nodes, given the dataset. The trees also reflect uncertainty about branch lengths.     

Probabilistic Forecast and Uncertainty Assessment of Hydrologic Design Values Using Bayesian Theories

Researches on hydrologic extreme events have great significance in reducing and avoiding the severe losses and impacts caused by natural disasters. When forecasting hydrologic design values of the hydrologic extreme events of interest by the conventional hydrologic frequency analysis (HFA) model, the results cannot take uncertainties and risks into account. In this article, in order to overcome conventional HFA model's disadvantages and to improve hydrologic design values’ forecast results, an improved HFA model named AM-MCMC-HFA is proposed by employing the AM-MCMC algorithm (adaptive Metropolis-Markov chain Monte Carlo) to HFA process. Differing with conventional HFA model, which is seeking single optimal forecast result, the AM-MCMC-HFA model can not only get the optimal but also the probabilistic forecast results of hydrologic design values. By applying to two obviously different hydrologic series, the performances of the model proposed have been verified. Analysis results show that four factors have great influence on hydrologic design values’ reliability, and also indicate that AM-MCMC-HFA has the ability of assessing the uncertainties of parameters and hydrologic design values. Therefore, by using the AM-MCMC-HFA model, hydrologic designs tasks can be operated more reasonably, and more rational decisions can be made by governmental decision-makers and public in practice.     

Prioritizing Biosecurity Risks Using a Participatory Decision-Making Tool

A decision framework called Deliberative Multi-Criteria Evaluation (DMCE) was developed and deployed to prioritize biosecurity risks using a variety of subjective and objective information. To aid stakeholders in the prioritization of Emergency Plant Pest (EPP) species risk, we presented them with outputs from a Stella-based bio-economic pest risk model, and probable ecological and socioeconomic impacts. The stakeholder participants weighted the consequence criteria they deemed to have the highest expected impact. The methodology featured an uncertain set of parameters, multiple iterations of criteria weighting along with real-time sensitivity analysis. Of the five criteria, economic cost was weighted the highest at 26% while landscape amenity was weighted the lowest at the 10–12% range. The increased understanding and support gained by stakeholders through the DMCE process provided a greater likelihood of the sanctioning of the policies concerned and progress toward desired outcomes.     

The risk of establishment of aquatic invasive species: joining invasibility and propagule pressure

Invasive species are increasingly becoming a policy priority. This has spurred researchers and managers to try to estimate the risk of invasion. Conceptually, invasions are dependent both on the receiving environment (invasibility) and on the ability to reach these new areas (propagule pressure). However, analyses of risk typically examine only one or the other. Here, we develop and apply a joint model of invasion risk that simultaneously incorporates invasibility and propagule pressure. We present arguments that the behaviour of these two elements of risk differs substantially--propagule pressure is a function of time, whereas invasibility is not--and therefore have different management implications. Further, we use the well-studied zebra mussel (Dreissena polymorpha) to contrast predictions made using the joint model to those made by separate invasibility and propagule pressure models. We show that predictions of invasion progress as well as of the long-term invasion pattern are strongly affected by using a joint model.     

No substitute for real data: A cautionary note on the use of phylogenies from birth–death polytomy resolvers for downstream comparative analyses

The statistical estimation of phylogenies is always associated with uncertainty, and accommodating this uncertainty is an important component of modern phylogenetic comparative analysis. The birth–death polytomy resolver is a method of accounting for phylogenetic uncertainty that places missing (unsampled) taxa onto phylogenetic trees, using taxonomic information alone. Recent studies of birds and mammals have used this approach to generate pseudoposterior distributions of phylogenetic trees that are complete at the species level, even in the absence of genetic data for many species. Many researchers have used these distributions of phylogenies for downstream evolutionary analyses that involve inferences on phenotypic evolution, geography, and community assembly. I demonstrate that the use of phylogenies constructed in this fashion is inappropriate for many questions involving traits. Because species are placed on trees at random with respect to trait values, the birth–death polytomy resolver breaks down natural patterns of trait phylogenetic structure. Inferences based on these trees are predictably and often drastically biased in a direction that depends on the underlying (true) pattern of phylogenetic structure in traits. I illustrate the severity of the phenomenon for both continuous and discrete traits using examples from a global bird phylogeny.     

Courting disaster: How diversification rate affects fitness under risk

Life is full of risk. To deal with this uncertainty, many organisms have evolved bet-hedging strategies that spread risk through phenotypic diversification. These rates of diversification can vary by orders of magnitude in different species. Here we examine how key characteristics of risk and organismal ecology affect the fitness consequences of variation in diversification rate. We find that rapid diversification is strongly favored when the risk faced has a wide spatial extent, with a single disaster affecting a large fraction of the population. This advantage is especially great in small populations subject to frequent disaster. In contrast, when risk is correlated through time, slow diversification is favored because it allows adaptive tracking of disasters that tend to occur in series. Naturally evolved diversification mechanisms in diverse organisms facing a broad array of environmental risks largely support these results. The theory presented in this article provides a testable ecological hypothesis to explain the prevalence of slow stochastic switching among microbes and rapid, within-clutch diversification strategies among plants and animals.     

Quantifying soil organic carbon in complex landscapes: an example of grassland undergoing encroachment of woody plants

The invasion of woody plants into grass‐dominated ecosystems has occurred worldwide during the past century with potentially significant impacts on soil organic carbon (SOC) storage, ecosystem carbon sequestration and global climate warming. To date, most studies of tree and shrub encroachment impacts on SOC have been conducted at small scales and results are equivocal. To quantify the effects of woody plant proliferation on SOC at broad spatial scales and to potentially resolve inconsistencies reported from studies conducted at fine spatial scales, information regarding spatial variability and uncertainty of SOC is essential. We used sequential indicator simulation (SIS) to quantify spatial uncertainty of SOC in a grassland undergoing shrub encroachment in the Southern Great Plains, USA. Results showed that both SOC pool size and its spatial uncertainty increased with the development of woody communities in grasslands. Higher uncertainty of SOC in new shrub‐dominated communities may be the result of their relatively recent development, their more complex above‐ and belowground architecture, stronger within‐community gradients, and a greater degree of faunal disturbance. Simulations of alternative sampling designs demonstrated the effects of spatial uncertainty on the accuracy of SOC estimates and enabled us to evaluate the efficiency of sampling strategies aimed at quantifying landscape‐scale SOC pools. An approach combining stratified random sampling with unequal point densities and transect sampling of landscape elements exhibiting strong internal gradients yielded the best estimates. Complete random sampling was less effective and required much higher sampling densities. Results provide novel insights into spatial uncertainty of SOC and its effects on estimates of carbon sequestration in terrestrial ecosystem and suggest effective protocol for the estimating of soil attributes in landscapes with complex vegetation patterns.     

Emergy as a Life Cycle Impact Assessment Indicator

Founded in thermodynamics and systems ecology, emergy evaluation is a method to associate a product with its dependencies on all upstream environmental and resource flows using a common unit of energy. Emergy is thus proposed as an indicator of aggregate resource use for life cycle assessment (LCA). An LCA of gold mining, based on an original life cycle inventory of a large gold mine in Peru, is used to demonstrate how emergy can be incorporated as an impact indicator into a process‐based LCA model. The results demonstrate the usefulness of emergy in the LCA context. The adaptation of emergy evaluation, traditionally performed outside of the LCA framework, requires changes to the conventional accounting rules and the incorporation of uncertainty estimations of the emergy conversion factors, or unit emergy values. At the same time, traditional LCA boundaries are extended to incorporate the environmental processes that provide for raw resources, including ores. The total environmental contribution to the product, doré, is dominated by mining and metallurgical processes and not the geological processes forming the gold ore. The measure of environmental contribution to 1 gram (g) of doré is 6.8E + 12 solar‐equivalent Joules (sej) and can be considered accurate within a factor of 2. These results are useful in assessing a process in light of available resources, which is essential to measuring long‐term sustainability. Comparisons are made between emergy and other measures of resource use, and recommendations are made for future incorporation of emergy into LCA that will result in greater consistency with existing life cycle inventory (LCI) databases and other LCA indicators.     

Chimpanzees and bonobos distinguish between risk and ambiguity

Although recent research has investigated animal decision-making under risk, little is known about how animals choose under conditions of ambiguity when they lack information about the available alternatives. Many models of choice behaviour assume that ambiguity does not impact decision-makers, but studies of humans suggest that people tend to be more averse to choosing ambiguous options than risky options with known probabilities. To illuminate the evolutionary roots of human economic behaviour, we examined whether our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus), share this bias against ambiguity. Apes chose between a certain option that reliably provided an intermediately preferred food type, and a variable option that could vary in the probability that it provided a highly preferred food type. To examine the impact of ambiguity on ape decision-making, we interspersed trials in which chimpanzees and bonobos had no knowledge about the probabilities. Both species avoided the ambiguous option compared with their choices for a risky option, indicating that ambiguity aversion is shared by humans, bonobos and chimpanzees.