Ecological memory at millennial time-scales: the importance of data constraints,species longevity and niche features

Ecological memory describes how antecedent conditions drive the dynamics of an ecological system. Palaeoecological records are paramount to understand ecological memory at millennial time-scales, but the concept is widely neglected in the literature, and a formal approach is lacking. Here, we fill such a gap by introducing a quantitative framework for ecological memory in palaeoecology, and assessing how data constraints and taxa traits shape ecological memory patterns. We simulate the population dynamics and pollen abundance of 16 virtual taxa with different life and niche traits as a response to an environmental driver. The data is processed to mimic a realistic sediment deposition and sampled at increasing depth intervals. We quantify ecological memory with Random Forests, and assess how data properties and taxa traits shape ecological memory. We find that life-span and niche features modulate the relative importance of the antecedent values of the driver and the pollen abundance over periods of 240 yr and longer. Additionally, we find that accumulation rate and decreasing pollen-sampling resolution inflate the importance of antecedent pollen abundance. Our results suggest that: 1) ecological memory patterns are sensitive to varying accumulation rates. A better understanding on the numerical basis of this effect may enable the assimilation of ecological memory concepts and methods in palaeoecology; 2) incorporating niche theory and models is essential to better understand the nature of ecological memory patterns at millennial time-scales. 3) Long-lived generalist taxa are highly decoupled from the environmental signal. This finding has implications on how we interpret the abundance-environment relationship of real taxa with similar traits, and how we use such knowledge to forecast their distribution or reconstruct past climate.     

Cold and hungry: combined effects of low temperature and resource scarcity on an edge-of-range temperate primate,the golden snub-nose monkey

Both biotic and abiotic factors play important roles in influencing ecological distributions and niche limits. Where biotic and abiotic stressors co-occur in space and time, homeostatic systems face a scenario in which stressors can compound to impose a challenge that is greater than the sum of the separate factors. We studied the homeostatic strategies of the golden snub-nosed monkey Rhinopithecus roxellana, a species living in temperate deciduous forests at the edge of the global distribution range for folivorous primates, to cope with the co-occurrence of cold temperatures and resource scarcity during winter. We discovered that in winter the monkeys experience a dietary energy deficit of 101 kJ mbm⁻¹ d⁻¹ compared with calculated needs, despite increased feeding. This is partly offset by behavioral changes (reduced locomotion and increased resting) and reducing skin temperature by an average of 3.2°C through a cutaneous vasoconstriction to decrease heat loss. However, their major strategy is ingesting surplus energy and accumulating fat reserves when food was not limiting during summer and autumn. Their 14% of body mass lost over the winter represented an energy yield of 102 kJ mbm⁻¹ d⁻¹, which closely matched the calculated winter energy deficit of 101 kJ mbm⁻¹ d⁻¹. However, the latter value assumes that all the 75.41 kJ mbm⁻¹ d⁻¹ of protein ingested in winter was available for energy metabolism. This is almost certainly an over-estimate, suggesting that the study population was in negative energy balance over the study period. Our study therefore suggests that despite its suit of integrated homeostatic responses, the confluence of low temperatures and resource limitation during winter places this edge-of-range primate close the threshold of what is energetically viable. It also provides a framework for quantitative models predicting the vulnerability of temperate primates to global change.     

Colonization history of Galapagos giant tortoises: Insights from mitogenomes support the progression rule

Galapagos giant tortoises (Chelonoidis spp.) are a group of large, long-lived reptiles that includes 14 species, 11 of which are extant and threatened by human activities and introductions of non-native species. Here, we evaluated the phylogenetic relationships of all extant and two extinct species (Chelonoidis abingdonii from the island of Pinta and Chelonoidis niger from the island of Floreana) using Bayesian and maximum likelihood analysis of complete or nearly complete mitochondrial genomes. We also provide an updated phylogeographic scenario of their colonization of the Galapagos Islands using chrono-phylogenetic and biogeographic approaches. The resulting phylogenetic trees show three major groups of species: one from the southern, central, and western Galapagos Islands; the second from the northwestern islands; and the third group from the northern, central, and eastern Galapagos Islands. The time-calibrated phylogenetic and ancestral area reconstructions generally align with the geologic ages of the islands. The divergence of the Galapagos giant tortoises from their South American ancestor likely occurred in the upper Miocene. Their diversification on the Galapagos adheres to the island progression rule, starting in the Pleistocene with the dispersal of the ancestral form from the two oldest islands (San Cristóbal and Española) to Santa Cruz, Santiago, and Pinta, followed by multiple colonizations from different sources within the archipelago. Our work provides an example of how to reconstruct the history of endangered taxa in spite of extinctions and human-mediated dispersal events and provides a framework for evaluating the contribution of colonization and in situ speciation to the diversity of other Galapagos lineages.     

未来气候变化对四种木姜子地理分布的影响

该文利用最大墒模型(Maxent)和地理信息系统(ArcGIS 10.3)软件对中国木姜子属(Litsea)四种资源植物在我国当代、未来(2061年—2080年)气候条件下的潜在分布区进行预测,并对其适宜区进行分析和划分。结果表明:山鸡椒(Litsea cubeba)适宜区广泛分布在长江以南区域,在未来时段2061年—2080年两种(RCP2.6、RCP8.5)二氧化碳浓度情景下适宜区面积分别减少4.9%和0.5%; 毛豹皮樟(L. coreana)适宜区主要分布在中亚热带及北亚热带区域,分布相对偏北,其在未来2061年—2080年两种二氧化碳浓度情景下适宜区面积分别增加5.6%和4.5%; 华南木姜子(L. greenmaniana)适宜区主要分布在我国南亚热带区域; 毛叶木姜子(L. mollis)适宜区广泛分布在亚热带区域。这两种树种在未来气候RCP2.6情景下适生面积减少1.0%和3.3%,在RCP8.5情景下减少5.6%和8.3%。上述结果说明木姜子属不同种由于生态习性差异对未来的气候变化的响应不尽相同,对这些植物引种栽培须考虑气候变化的影响。     

西双版纳国家级自然保护区蚂蚁-树互作网络空间变异

网络分析(network analysis)可以同时分析群落中的物种多样性和种间关系, 为了解生态群落的稳定性机制提供了新的分析思路和方法。本研究从西双版纳国家级自然保护区的纳板河、勐仑和勐腊(补蚌)三个地点采集了树栖性蚂蚁及树木的种类和数量数据, 对蚂蚁-树组成的二分网络进行了分析, 探讨了3个采样点物种的多样性、网络指标以及群落指标之间的关系。我们采用零模型的方法比较了3个样点的标准化网络参数差异。结果表明: 蚂蚁和树木的物种数以及树的异质性指数(Shannon-Wiener多样性指数、Simpson多样性指数)都呈现出勐仑 > 纳板河 > 补蚌的趋势。树木-蚂蚁的灭绝曲线系数大小关系同样为勐仑 > 纳板河 > 补蚌, 灭绝曲线与树的物种数及异质性指数大小趋势一致, 而与蚂蚁的异质性指数并不吻合。根据Z值的绝对值来看, 网络参数(加权嵌套性、平均连接数、特化水平、模块性、连接度)与群落参数(灭绝曲线系数、生态位重叠)的大小趋势相同, 表现出勐仑 > 纳板河 > 补蚌的趋势。综上所述, 蚂蚁-树互作网络的稳定性(灭绝曲线系数)主要由树的数量和异质性指数决定。网络的加权嵌套性和网络中节点的平均连接数也能促进群落的稳定性。而在一个特化的(数值越大表示专性互作越多)和模块化(具有较多密切互作的节点单元)的网络中, 当低营养级物种灭绝时高营养级物种数量将迅速减少。     

末次盛冰期以来观光木的潜在地理分布变迁

观光木(Tsoongiodendron odorum)是木兰科的古老残遗物种, 目前正面临严峻的生存威胁, 属于极小种群濒危植物。通过生态位模型(ENM)能够重建观光木地理分布格局的历史变迁, 探究气候变化对该物种分布的影响, 并了解其地理分布与气候需求间的关系, 从而为全球变暖背景下观光木的保护提供理论基础。该文基于96条现代分布记录和8个环境变量, 采用最大熵(MaxEnt)模型模拟观光木在末次盛冰期、全新世中期、现代和未来(2061-2080年, RCP 8.5)的潜在分布区, 利用SDM toolbox分析观光木的地理空间变化, 并综合贡献率、置换重要值和Jackknife检验来评估气候因子的重要性。研究结果表明: (1)观光木的高度适生区在南岭地区, 末次盛冰期时没有大尺度向南退缩, 很可能在山区避难所原地存活; (2)在全新世中期和未来两个增温的气候情境下, 观光木的分布区均表现为缩减, 其中未来分布的减幅更大, 表明气候变暖对观光木的生长有一定的负面影响; (3)总体上看, 观光木各个时期的地理分布范围相对稳定, 说明观光木对气候变化有一定的适应能力, 人为活动或自身繁育问题可能是致濒的重要原因, 并建议对广东和广西群体进行优先保护。     

救护白鹤与野生白鹤迁徙路线和活动规律差异分析

受伤和体弱白鹤的救护及放归是白鹤保护的重要方式之一。2014—2016年间,先后对8只救护白鹤和2只野生白鹤进行环志并安装卫星跟踪器,根据所获得的卫星跟踪数据来分析比较救护白鹤与野生白鹤在秋季迁徙路线和在重要中途停歇地的最大日活动距离、活动区分布和面积、生境类型等方面的异同。结果显示,救护白鹤放归当年与放归次年以及救护白鹤放归当年与野生白鹤的秋季迁徙路线和活动规律之间存在明显差异,但救护白鹤放归次年与野生白鹤之间差异不明显。(1)放归当年,4只救护白鹤在农田和水塘停歇1个月左右,停歇时长明显高于野生白鹤和放归次年的救护白鹤。(2)救护白鹤放归当年在跨海方式、登陆地点、停歇地点以及登陆后的迁徙方向上表现出多样性和不确定性,其中部分个体在迁徙过程中有停顿徘徊、迷失迁徙方向的现象,且跨越渤海和大别山的距离大于放归次年的救护白鹤和野生白鹤。(3)救护白鹤放归后4天内每日最大活动距离小,而后高低分化明显,无明显规律,而救护白鹤放归次年的每日最大活动距离规律变化与野生白鹤较一致。(4)与救护白鹤放归次年以及野生白鹤的活动规律相比,救护白鹤放归当年的栖息地位点变化频繁,具体表现为生境类型选择的多样化,且无明显规律,同时活动区面积较小。探索救护白鹤放归野外后与野生白鹤迁徙路线和活动规律的差异,对救护白鹤的科学放归具有指导意义。     

人为干扰对传粉昆虫群落物种多样性及其优势类群生态位的影响

物种多样性是群落功能复杂性和稳定性的重要量度指标,不同干扰强度下物种多样性和生态位特征不同,人为干扰对传粉群落的影响可以通过群落结构和物种多样性的变化直接表现出来。在巩义市选取24个采样点,3种景观类型(农田、灌丛、林地)进行取样,共捕获传粉昆虫18576头,分属于14目,147科,双翅目、膜翅目、鞘翅目、鳞翅目、半翅目与缨翅目6个传粉功能群。为了解研究区人为干扰对传粉昆虫类群传粉类群及其生态位的影响,本研究选取双翅目、膜翅目、鞘翅目3类主要传粉昆虫作为研究对象,在景观类型分类与实际情况的基础上,依据人为干扰指数赋值表和干扰强度计算公式,分析不同干扰强度下传粉昆虫优势种群生态位特征情况,结果表明:各传粉类群在不同的干扰条件下物种多样性不同;作为优势类群的蠓科、胡蜂科,生态位宽度和生态位重叠均均值高于其他几个类群,且中度干扰强度下值最大,但其生态宽度值与生态重叠值之间没有明显的相关关系。     

基于GIS的滨海盐渍化农田土壤空间变异及其分区管理

针对滨海盐渍化农田盐碱瘠薄、土壤属性空间变异大、粗放管理效益低的现实,研究管理分区精准划分方法,采取差异化措施,提升盐渍化土地利用水平。该文以无棣县农田为研究区,采用网格法结合土地利用现状定点野外采样、室内化验分析获取土壤属性数据,运用ArcGIS 10.2地统计方法分析土壤属性的空间变异特征;在MATLAB R2016a中采用模糊c-均值聚类法（FCM）计算各样点的模糊隶属度,通过插值预测模糊隶属度的空间分布,基于最大隶属度原则进行分区;通过变异性分析和最小极差法（LSR）差异显著性检验,对分区结果进行精度验证。结果表明：无棣县农田土壤总体呈轻中度盐渍化,有效氮含量偏低,有机质、有效磷含量中等,速效钾含量较高;有机质、有效氮、有效磷、速效钾和含盐量呈中等变异性（变异系数25.0%-52.3%）,空间变异性较大,应分区调控;速效钾、含盐量和pH的块金效应值小于25%,主要受土壤质地、地下水矿化度等结构因素影响,有机质、有效氮和有效磷的块金效应值在50%-75%之间,受耕作方式、施肥等人为因素影响较大。将全县农田划分为3类管理区,估算面积分别为2.56万hm²、1.76万hm²、3.24万hm²;各分区土壤养分变异系数分别为23.9%-51.5%、15.9%-50.3%、14.7%-33.0%,检验结果表明各分区间差异显著,而各分区内部变异性明显低于未分区。管理分区与土壤属性空间分布特征具有较高的拟合度,分区结果可以作为差异化管理的作业单元。研究结果为各分区内部统一、不同分区间差异化管理提供了依据,研究有助于推进滨海盐渍化农田精准化管理水平的提高。     

Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin,USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream‐segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large‐river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC_C‐selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC_C‐selected models were more inclusive of westward‐situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.