Metabolic approaches to understanding climate change impacts on seasonal host‐macroparasite dynamics

Climate change is expected to alter the dynamics of infectious diseases around the globe. Predictive models remain elusive due to the complexity of host–parasite systems and insufficient data describing how environmental conditions affect various system components. Here, we link host–macroparasite models with the Metabolic Theory of Ecology, providing a mechanistic framework that allows integrating multiple nonlinear environmental effects to estimate parasite fitness under novel conditions. The models allow determining the fundamental thermal niche of a parasite, and thus, whether climate change leads to range contraction or may permit a range expansion. Applying the models to seasonal environments, and using an arctic nematode with an endotherm host for illustration, we show that climate warming can split a continuous spring‐to‐fall transmission season into two separate transmission seasons with altered timings. Although the models are strategic and most suitable to evaluate broad‐scale patterns of climate change impacts, close correspondence between model predictions and empirical data indicates model applicability also at the species level. As the application of Metabolic Theory considerably aids the a priori estimation of model parameters, even in data‐sparse systems, we suggest that the presented approach could provide a framework for understanding and predicting climatic impacts for many host–parasite systems worldwide.     

Theoretical framework of population genetics with somatic mutations taken into account: application to copy number variations in humans

Traditionally, population genetics focuses on the dynamics of frequencies of alleles acquired by mutations on germ-lines, because only such mutations are heritable. Typical genotyping experiments, however, use DNA from some somatic tissues such as blood, which harbors somatic mutations at the current generation in addition to germ-line mutations accumulated since the most recent common ancestor of the sample. This common practice may sometimes cause erroneous interpretations of polymorphism data, unless we properly understand the role of somatic mutations in population genetics. We here introduce a very basic theoretical framework of population genetics with somatic mutations taken into account. It is easy to imagine that somatic mutations at the current generation simply add individual-specific variations, as errors in mutation detection do. Our theory quantifies this increment under various conditions. We find that the major contribution of somatic mutations plus errors is to very rare variants, particularly to singletons. The relative contribution is markedly large when mutations are deleterious. Because negative selection also increases rare variants, it is important to distinguish the roles of these mutually confounding factors when we interpret the data, even after correcting for demography. We apply this theory to human copy number variations (CNVs), for which the composite effect of somatic mutations and errors may not be negligible. Using genome-wide CNV data, we demonstrate how the joint action of the two factors, selection and somatic mutations plus errors, shapes the observed pattern of polymorphism.     

Mean growth rate when rare is not a reliable metric for persistence of species

The coexistence of many species within ecological communities poses a long‐standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, , is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on and show that it fails to capture the effect of temporal random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in , since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as increases.     

Natural history of model organisms: The secret (group) life of Drosophila melanogaster larvae and why it matters to developmental ecology

1. Model organisms such as Drosophila melanogaster have been key tools for advancing our fundamental and applied knowledge in biological and biomedical sciences. However, model organisms have become intertwined with the idea of controlled and stable laboratory environments, and their natural history has been overlooked.
2. In holometabolous insects, lack of natural history information on larval ecology has precluded major advances in the field of developmental ecology, especially in terms of manipulations of population density early in life (i.e., larval density). This is because of relativistic and to some extent, arbitrary methodologies employed to manipulate larval densities in laboratory studies. As a result, these methodologies render comparisons between species impossible, precluding our understanding of macroevolutionary responses to population densities during development that can be derived from comparative studies.
3. We recently proposed a new conceptual framework to address this issue, and here, we provide the first natural history investigation of Drosophila melanogaster larval density under such framework. First, we characterized the distribution of larval densities in a wild population of D. melanogaster using rotting apples as breeding substrate in a suburban area in Sweden.
4. Next, we compiled the commonly used methodologies for manipulating larval densities in laboratory studies from the literature and found that the majority of laboratory studies identified did not manipulate larval densities below or above the densities observed in nature, suggesting that we have yet to study true life history and physiological responses to low and high population densities during D. melanogaster development.
5. This is, to our knowledge, the first direct natural history account of larval density in nature for this model organism. Our study paves the way for a more integrated view of organismal biology which re‐incorporates natural history of model organisms into hypothesis‐driven research in developmental ecology.

     

Socio-ecological correlates of neophobia in corvids

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Between cheap and costly signals: the evolution of partially honest communication

Costly signalling theory has become a common explanation for honest communication when interests conflict. In this paper, we provide an alternative explanation for partially honest communication that does not require significant signal costs. We show that this alternative is at least as plausible as traditional costly signalling, and we suggest a number of experiments that might be used to distinguish the two theories.     

Palaeodistribution modelling does not support disjunct Pleistocene refugia in several Central American plant taxa

Aim We combine evidence from palaeoniche modelling studies of several tree species to estimate the extent of Central American forest during the Last Glacial Maximum (LGM). In particular, we ask whether the distributions of these species are likely to have changed since the LGM, and whether LGM distributions coincide with previously proposed Pleistocene refugia in this area. Location Central American wet and seasonally dry forests. Methods We developed ecological niche models using two simulations of Pleistocene climate and occurrence data for 15 Neotropical plant species. We focused on palaeodistribution models of three ‘focal’ tree species that occur in wet and seasonally dry Central American forests, where recent phylogeographic data suggest Pleistocene differentiation coincident with previously proposed refugia. We added predictions from six wet‐forest and six seasonally dry‐forest obligate plant species to gauge whether Pleistocene range shifts were specific to habitat type. Correlation analyses were performed between projected LGM and present distributions, LGM distributions and previously proposed refugia. We also asked whether modelled palaeodistributions were smaller than their current extents. Results According to our models, the ranges of the study species were not reduced during the LGM, and did not correlate with refugial models, regardless of habitat type. Relative range sizes between present and LGM distributions did not indicate significant range changes since the LGM. However, relative range sizes differed overall between the two palaeoclimate models. Main conclusions Many of the modelled palaeodistributions of study species were not restricted to refugia during the LGM, regardless of forest type. While constrained from higher elevations, most species found suitable habitat at coastal margins and on newly exposed land due to lowered sea levels during the LGM. These results offer no corroboration for Pleistocene climate change as a driver of genetic differentiation in the ‘focal’ species. We offer alternative explanations for genetic differentiation found in plant species in this area.     

基于地质灾害敏感性的生态安全格局关键区识别与修复——以济南市为例

区域生态安全格局构建对提升生态系统服务功能提供了重要路径，同时统筹各种生态要素进行生态保护与修复分区也是新时期做好生态修复的重要举措。以济南市为例，基于现状生态系统类型分布，聚焦生态本底和地质灾害敏感性的特征，基于形态学空间格局分析方法和自然保护区结合进行生态源地提取。采用夏季降水、植被覆盖度、坡度3个地质灾害敏感性因子修正基本生态阻力面。并采用最小成本路径方法（Least-Cost Path method，LCP）提取生态廊道，构建了市域的生态安全格局。采用电路理论进行生态关键区域（生态"夹点"和生态障碍点）的识别，进一步划分生态修复改善区，并对此提出针对性的生态保护修复策略和工程措施。研究表明：1）市域生态源地的个数为35个，面积为567.15 km²，主要类型为林地和草地。空间上主要分布南部山区。生态廊道818.42 km，平均廊道长度为12.99 km，廊道分布存在较为明显的空间分布差异性，整体呈现出"一屏、一带、三轴"的生态安全格局。2）识别的生态修复关键区包含生态"夹点"25处，历城区生态"夹点"分布最为密集。全市亟需修复的生态障碍点共34处，面积为6.90 km²，主要分布章丘区。生态改善区共识别2994.84 km²，近期亟需修复的面积为96.1 km²，主要分布在长清区、历城区、莱芜区。3）通过对比生态修复关键区和现状土地利用类型，因地适宜的制定了生态修复策略与工程措施布置指引方向。研究结果可为济南市国土空间生态修复规划提供一定的技术支撑，同时也可为其他地质灾害敏感性区域的生态修复规划提供指引。