松栎林天然更新模拟与不确定性分析

森林天然更新的复杂性和不确定性是森林生态系统动态预测中的关键问题。本研究引入贝叶斯技术和全局敏感性分析,构建基于竞争、气候和地形3类因子的秦岭松栎林天然更新模型。备选模型形式以泊松(Poisson)模型、负二项(negative binomial,NB)模型、零膨胀泊松(zero-inflated Poisson,ZIP)模型和零膨胀负二项(zero-inflated negative binomial,ZINB)模型为基础。同时,根据模型参数传递的不确定性量化分析结果,阐释影响森林更新小概率事件的主导因子。结果表明: ZINB模型在油松和锐齿栎更新模拟中均优于其他模型。林分总断面积、光截留、坡位和生长季最低温是影响松栎林中油松天然更新的最关键因子;而林分总断面积、坡向与海拔的组合、年均温和最热季节降水量则是影响松栎林中锐齿栎天然更新的关键因子。油松更新模拟中,各类因子对模型输出的不确定性贡献率从小到大依次为: 竞争因子(25%)＜气候因子(29%)＜地形因子(46%);锐齿栎更新模拟中为: 气候因子(12%)＜竞争因子(24%)＜地形因子(64%)。油松天然更新数量对生长季最低温和最干季节降水量为正响应,对最干季节均温为负响应;锐齿栎天然更新数量对年均温、生长季最低温和最热季节降水量为正响应,对最干季节均温为负响应。基于贝叶斯技术的ZINB模型可以量化森林更新的影响因子,并解释参数传递的不确定性,是预测森林天然更新的有力工具。     

微生境对黄梅秤锤树野生种群叶片功能性状的影响

植物功能性状可以反映植物应对环境变化的适应策略。本文以黄梅秤锤树(Sinojackia huangmeiensis)当前唯一野生种群为对象, 比较了3种微生境(湖边、种群中心、耕地边)中该物种的叶片功能性状均值、种内变异和叶片生态化学计量特征的差异, 分析了黄梅秤锤树对湖岸带微生境变化的响应及其适应策略。结果表明: (1) 3种微生境中土壤C、N、P含量没有显著性差异(P > 0.05), 但土壤C∶N和C∶P具有显著性差异(P < 0.05), 土壤类型和养分条件有所不同。(2)黄梅秤锤树叶片功能性状的比较用单因素方差分析和贝叶斯方差分析得出的结果一致, 均为叶长、叶面积和比叶面积在中心区域显著高于湖边(P < 0.05), 而耕地边与湖边和中心区域均没有显著差异(P > 0.05); 叶N含量在湖边显著高于中心区域和耕地边(P < 0.05), 而中心区域和耕地边间没有显著差异(P > 0.05); 叶宽、叶长/叶宽、叶干物质含量、叶C和叶P含量在3种微生境间都没有显著性差异(P > 0.05)。(3)黄梅秤锤树叶片的N∶P在湖边显著高于中心区域和耕地边(P < 0.05), C∶N在湖边显著小于中心区域和耕地边(P < 0.05), N∶P和C∶N在中心区域和耕地边没有显著性差异(P > 0.05), C∶P在3种微生境间都没有显著性差异(P > 0.05)。(4)黄梅秤锤树叶片功能性状的总体变异程度在0.02-0.28之间, 其中叶片C和N含量在湖边和中心区域的种内变异程度显著较低, 表明3种生境中湖边和中心区域黄梅秤锤树种群的稳定性相对较差。(5)湖边黄梅秤锤树主要通过增加叶N含量促进生长; 中心区域黄梅秤锤树主要通过增加叶面积和比叶面积以及提高叶N的利用效率来提高光捕获能力促进生长; 耕地边黄梅秤锤树的叶N含量和叶面积、比叶面积都处于中等水平, 通过性状之间的共同作用使植株生长达到最佳水平。以上结果表明, 由于微地形、水位波动和土壤环境条件的差异, 黄梅秤锤树对3种生境中的适应策略有所不同, 并且不是通过单一性状调整来适应环境的变化, 而是通过多种性状之间的权衡达到更好的适应效果。     

A layover in Europe: Reconstructing the invasion route of asexual lineages of a New Zealand snail to North America

Non‐native invasive species are threatening ecosystems and biodiversity worldwide. High genetic variation is thought to be a critical factor for invasion success. Accordingly, the global invasion of a few clonal lineages of the gastropod Potamopyrgus antipodarum is thus both puzzling and has the potential to help illuminate why some invasions succeed while others fail. Here, we used SNP markers and a geographically broad sampling scheme (N = 1617) including native New Zealand populations and invasive North American and European populations to provide the first widescale population genetic assessment of the relationships between and among native and invasive P. antipodarum. We used a combination of traditional and Bayesian molecular analyses to demonstrate that New Zealand populations harbour very high diversity relative to the invasive populations and are the source of the two main European genetic lineages. One of these two European lineages was in turn the source of at least one of the two main North American genetic clusters of invasive P. antipodarum, located in Lake Ontario. The other widespread North American group had a more complex origin that included the other European lineage and two New Zealand clusters. Altogether, our analyses suggest that just a small handful of clonal lineages of P. antipodarum were responsible for invasion across continents. Our findings provide critical information for prevention of additional invasions and control of existing invasive populations and are of broader relevance towards understanding the establishment and evolution of asexual populations and the forces driving biological invasion.     

Genetic variation in Plethodon cinereus and Plethodon hubrichti from in and around a contact zone

Climate change poses several challenges to biological communities including changes in the frequency of encounters between closely related congeners as a result of range shifts. When climate change leads to increased hybridization, hybrid dysfunction or genetic swamping may increase extinction risk—particularly in range‐restricted species with low vagility. The Peaks of Otter Salamander, Plethodon hubrichti, is a fully terrestrial woodland salamander that is restricted to ~18 km of ridgeline in the mountains of southwestern Virginia, and its range is surrounded by the abundant and widespread Eastern Red‐backed Salamander, Plethodon cinereus. In order to determine whether these two species are hybridizing and how their range limits may be shifting, we assessed variation at eight microsatellite loci and a 1,008 bp region of Cytochrome B in both species at allopatric reference sites and within a contact zone. Our results show that hybridization between P. hubrichti and P. cinereus either does not occur or is very rare. However, we find that diversity and differentiation are substantially higher in the mountaintop endemic P. hubrichti than in the widespread P. cinereus, despite similar movement ability for the two species as assessed by a homing experiment. Furthermore, estimation of divergence times between reference and contact zone populations via approximate Bayesian computation is consistent with the idea that P. cinereus has expanded into the range of P. hubrichti. Given the apparent recent colonization of the contact zone by P. cinereus, future monitoring of P. cinereus range limits should be a priority for the management of P. hubrichti populations.     

Predictor species: Improving assessments of rare species occurrence by modeling environmental co‐responses

Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co‐occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co‐responses among species. For species from a European peat bog community, our approach consistently performs better than single‐species models and better than conventional multi‐species approaches that include the presence of nontarget species as additional independent variables in regression models. Our approach performs particularly well with rare species and when calibration data are limited. Furthermore, we identify a group of “predictor species” that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices.     

New advances on the Aurignacian in the central Iberian Mediterranean basin

This study aims to obtain a chronological and cultural framework of the Evolved Aurignacian in the central Iberian Mediterranean basin and find agreement between this framework and other sequences of the Iberian southeast. Over the last few years, there has been remarkable progress in the research of the Evolved Aurignacian sites in the Valencian area, making a review of the main characteristics of the technocomplex on a regional scale necessary. The recent fieldwork carried out in Cova de les Malladetes (Valencia) and in Cova de les Cendres (Alicante) have been key to understanding the lithic, osseous and ornament assemblages ascribed to the Evolved Aurignacian. Several Bayesian modelled ages have been constructed from the large dataset of chronological dates obtained at Malladetes and Cendres, as well as in other sites. The Bayesian models have allowed us to chronologically place the characteristics of the analysed assemblages. The present research supports the importance of the Aurignacian as the first technocomplex of the Upper Palaeolithic in this area of the Iberian Peninsula.     

A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

The discovery of rare genetic variants through next generation sequencing is a very challenging issue in the field of human genetics. We propose a novel region‐based statistical approach based on a Bayes Factor (BF) to assess evidence of association between a set of rare variants (RVs) located on the same genomic region and a disease outcome in the context of case‐control design. Marginal likelihoods are computed under the null and alternative hypotheses assuming a binomial distribution for the RV count in the region and a beta or mixture of Dirac and beta prior distribution for the probability of RV. We derive the theoretical null distribution of the BF under our prior setting and show that a Bayesian control of the false Discovery Rate can be obtained for genome‐wide inference. Informative priors are introduced using prior evidence of association from a Kolmogorov‐Smirnov test statistic. We use our simulation program, sim1000G, to generate RV data similar to the 1000 genomes sequencing project. Our simulation studies showed that the new BF statistic outperforms standard methods (SKAT, SKAT‐O, Burden test) in case‐control studies with moderate sample sizes and is equivalent to them under large sample size scenarios. Our real data application to a lung cancer case‐control study found enrichment for RVs in known and novel cancer genes. It also suggests that using the BF with informative prior improves the overall gene discovery compared to the BF with noninformative prior.     

Bayesian modeling of skewed X inactivation in genetically diverse mice identifies a novel Xce allele associated with copy number changes

Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176-kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross (CC) strains. Using published sequence data and applying a Bayesian “Pólya urn” model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20–30 cells contributing to brain. Second, CC founder strain NOD/ShiLtJ has a novel and unique functional allele, Xce^g, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xce^b), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles.     

Strategic Habitat Conservation for Beach Mice: Estimating Management Scenario Efficiencies

The Perdido Key beach mouse (Peromyscus polionotus trissyllepsis), Choctawhatchee beach mouse (P. p. allophrys), and St. Andrew beach mouse (P. p. peninsularis) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well-targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30-m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post-storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km² of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives. © 2020 The Wildlife Society.