基于稳定同位素的消费者营养来源溯源的方法和过程

为降低利用稳定同位素分析对消费者营养来源进行溯源所造成的一定程度误读, 文章基于实测同位素数据集(浮游动物同位素数据集), 通过原始数据的简单统计检验、营养来源先验信息的矫正, 构建系列贝叶斯模型; 通过同位素空间的构建与检验, 及先验信息和后验分布差异等多种分析方法与步骤, 来描述消费者营养来源溯源的方法和过程。以此为应用稳定性同位素技术开展消费者营养溯源研究提供指导。     

基于稳定氧同位素确定植物水分来源不同方法的比较

利用稳定同位素技术确定植物水分来源,对提高生态水文过程的认识和对干旱半干旱区的生态管理至关重要。目前基于稳定同位素技术确定植物水分来源的方法众多,但不同方法之间对比的研究较少。本研究基于原位样品采集,室内实验测试,利用直接对比法、多元线性混合模型(IsoSource)、贝叶斯混合模型(MixSIR、MixSIAR)和吸水深度模型分析植物水分来源,并对比各方法的优缺点。结果表明:相对于多元线性混合模型(IsoSource)而言,贝叶斯混合模型(MixSIR、MixSIAR)具有更好的水源区分性能,但对数据要求较高,且植物木质部水和潜在水源同位素组成的标准差越小,模型运行结果的可信度更高。本研究中贝叶斯混合模型(MixSIR)为最优解。在利用稳定氢氧同位素技术确定植物水分来源时,可先通过直接对比法定性判断植物可能利用的潜在水源,然后再用多元线性混合模型(IsoSource)、贝叶斯混合模型(MixSIR、MixSIAR)计算出各潜在水源对植物的贡献率和贡献范围,必要时可评估模型性能,选择出最优模型,定量分析植物的水分来源。若植物主要吸收利用不同土层深度的土壤水,可结合吸水深度模型计算出植物吸收土壤水的平均深度。本研究为干旱半干旱地区利用同位素技术确定植物水分来源方法的选择提供了理论依据。     

利用放射性碳和稳定性碳同位素技术估算抚仙湖北部近岸湖区消费者的碳源贡献

碳同位素技术可用于辨析湖泊消费者的食物来源.基于抚仙湖北部近岸湖区主要消费者及其各食物来源的放射性同位素特征(Δ14C)与稳定同位素特征(δ13C),运用IsoSource混合同位素模型估算了不同碳源对湖泊消费者的贡献.抚仙湖各食物来源浮游植物、沉水植物和陆源碎屑的 δ13C比值分别为-31‰、-13.5‰和-29.4...     

基于稳定同位素的湿地食物源判定和食物网构建研究进展

湿地生物营养动力学是湿地生态系统结构和功能评价研究的基础.碳、氮稳定同位素作为识别营养关系的方法,已在湿地生态系统食物来源、组成和食物链传递研究中得到广泛运用.本文系统综述了稳定同位素食物贡献度计算模型和营养级确定的基本方法和理论;讨论了动物营养分馏值和基线的选择依据;概括了湿地生态系统典型食物源及其稳定同位素变化特征;总结了草食、杂食和肉食等不同营养级动物的食物来源.指出了稳定同位素在湿地食物源溯源和食物网研究中的不足;基于国内外研究现状和发展趋势及需求,展望了未来同位素技术在湿地食物网生态学研究中的运用前景和研究重点,提出需要加强稳定同位素营养分馏和基线的影响因素、样品处理和保存方式研究以及胃含物、分子标记物和多元素同位素结合分析.     

三种针叶树种节子属性通用方程的构建

以2020年在黑龙江省林口林业局与孟家岗林场选取的3种典型针叶树种红松、长白落叶松、樟子松为研究对象,对节子直径、疏松节长度、健全节长度3种属性构建基础模型、哑变量模型和混合模型,分析不同树种节子属性的差异,简化模型的建模工作。首先通过剖析法收集相关节子属性数据,结合相关文献,转换模型形式以及替换相关变量,构建基础模型;将树种作为定性因子,转化为哑变量,引入基础模型中,构建相关属性的哑变量模型;在构建混合模型时,引入样木与样地水平的随机效应,通过比较赤池信息准则(AIC)、贝叶斯信息准则(BIC)等评价指标,选出拟合效果最佳的混合模型。之后对基础模型、哑变量模型、混合模型的拟合精度进行对比,选出最优的通用方程。结果表明：3种模型中,哑变量模型与混合模型的拟合精度均大于基础模型。AIC、BIC等评价指标显示,混合模型对节子属性的拟合效果优于哑变量模型。模型对比结果中,健全节长度、疏松节长度、节子直径混合模型的R²相较于基础模型分别提升了13.2%、84.8%、40.3%。不同树种3种节子属性基础模型的预测精度均大于90%,哑变量模型与混合模型的预测精度均在94%以上...     

黄河口近海海草床浮游-底栖营养传递特征

为了探寻海草床浮游-底栖营养传递耦合特征,于2017年7月对黄河口近海海草床碳源和消费者功能群进行样品采集和碳氮稳定同位素（δ¹³C和δ¹⁵N）测定,计算了消费者功能群的营养级,利用基于贝叶斯的稳定同位素混合模型定量化消费者功能群的食源组成,计算了消费者功能群的浮游、底栖营养贡献比例。结果表明：黄河口近海海草床的碳源和消费者功能群的δ¹³C和δ¹⁵N值均呈现显著性差异（P<0.05）,浮游碳源的δ¹³C值显著低于底栖碳源,消费者功能群的营养级范围为1.49-4.20。浮游动物和腹足类分别由浮游和底栖营养传递途径提供能量来源,其余消费者功能群共同依赖于这两种营养传递路径。消费者功能群随着浮游营养贡献比例的增加,其δ¹³C值逐渐降低。反之,随着底栖营养贡献比例的增加,其δ¹³C值逐渐增加。这与浮游碳源和底栖碳源的δ¹³C值的分化现象一致。对该海草床营养传递特征的系统性定量化解析有助于了解海草床的能量传递模式,为海草床的生态保护和修复提供系统性视角。     

基于非线性混合模型的红松人工林枝条生长

基于黑龙江省孟家岗林场36株红松人工林的枝解析数据,以单分子式和理查德方程作为枝条基径(BD)和枝长(BL)生长模型,分别考虑样地效应和样木效应,利用SAS软件的PROC NLMIXED模块构建了枝条基径和枝长生长的非线性混合模型.采用Akaike信息准则(AIC)、贝叶斯信息准则(BIC)、对数似然值(-2Log likelihood)和似然比检验(LRT)等评价指标对所构建模型的精度进行比较.结果表明:当考虑样地效应时,α1、α3和β1、β3分别作为随机参数时基径和枝长生长模型拟合效果最好;当考虑样木效应影响时,α2、α3和β1、β3分别作为随机参数时基径和枝长生长模型拟合效果最好.非线性混合模型不但可反映枝生长总体平均变化趋势,还能反映个体之间的差异.无论考虑样地效应还是样木效应,非线性混合模型的拟合精度都比传统回归模型的拟合精度高,并且考虑样木效应的拟合精度高于考虑样地效应的拟合精度.     

基于广义线性混合效应模型的森林树木死亡研究

基于计数模型方法,同时考虑样地的随机效应,构建林分水平死亡模型,探究影响树木死亡的因素,以期为森林资源的监测与管理提供参考依据。以美国德州东部森林连续清查的样地数据为数据源,按4∶1的比例将其进行随机抽样,划分为训练集和验证集数据,将立地因子、林分因子和气候因子作为模型的自变量,林木死亡株数则作为模型的因变量,运用计数模型和混合效应模型方法进行模型的构建,并分析影响林木死亡株数的因子。使用赤池信息准则(AIC)、贝叶斯信息准则(BIC)和-2倍对数似然函数值(-2logL) 3种模型评价指标评估各模型间的拟合效果;采用平均绝对误差(MAE)和均方根误差(RMSE) 2种评价指标评估其预测效果,以便筛选出最佳的林分水平死亡模型。结果表明：立地因子方面,林木死亡株数与海拔(P<0.01)呈显著的负效应,与坡度(P<0.05)呈显著的正效应,说明林木死亡株数随海拔的升高而减少,随坡度的增加而增多;林分因子方面,林木死亡株数与林分年龄(P<0.001)和树木基面积(P<0.001)呈显著的正效应,与林分平方平均胸径(P<0.001)和林分密度(P<0.05)...     

高营养级捕食者在浅水湖泊沿岸带与敞水区能量耦合的维持作用

研究利用保安湖沿岸带与敞水区两种生境中高营养级捕食者(达氏鲌与红鳍原鲌)的碳(δ13C)、氮(δ15N)稳定同位素数据,通过稳定同位素质量平衡混合模型、非度量多维尺度分析(NMDS)等方法,分析了两种生境中鲌类食物来源的差异.结果表明,两种生境中鲌类食物来源基本一致,且食物来源较为广泛,包括沿岸带饵料鱼类、敞水区饵料鱼...     

利用稳定氢氧同位素定量区分白刺水分来源的方法比较

水是影响植物分布的重要生态因子之一,对植物水源的研究有助于在全球变化背景下了解植物的时空分布格局.根据同位素质量守恒,利用稳定氢氧同位素可以确定植物水分来源,相关的方法也不断改进.利用三源线性混合模型、多源线性混合模型、吸水深度模型以及动态模型分别对格尔木白刺(Nitraria Tangutorum)的水分来源进行了对比研究,发现格尔木白刺主要吸收利用50-100 cm处的土壤水及地下水.在研究方法上,各模型都有自己的应用范围和局限:三源线性混合模型一般只能在植物吸收的水分来源不超过3个的情况下运行;多源线性混合模型弥补了三源线性混合模型的不足,可以同时比较多种来源水各自对白刺的贡献率及贡献范围;吸水深度模型弥补了混合模型中不能计算白刺对土壤水的平均吸水深度的缺陷;动态模型则会为未来降水格局变化对植物的时空分布的影响研究起很大作用.针对不同的适用范围,模型的选择及综合应用会更广泛.但是,该技术还存在一些不足,需要结合测定土水势,富氘水的示踪等方法来弥补.     

Incorporating uncertainty and prior information into stable isotope mixing models

Stable isotopes are a powerful tool for ecologists, often used to assess contributions of different sources to a mixture (e.g. prey to a consumer). Mixing models use stable isotope data to estimate the contribution of sources to a mixture. Uncertainty associated with mixing models is often substantial, but has not yet been fully incorporated in models. We developed a Bayesian-mixing model that estimates probability distributions of source contributions to a mixture while explicitly accounting for uncertainty associated with multiple sources, fractionation and isotope signatures. This model also allows for optional incorporation of informative prior information in analyses. We demonstrate our model using a predator–prey case study. Accounting for uncertainty in mixing model inputs can change the variability, magnitude and rank order of estimates of prey (source) contributions to the predator (mixture). Isotope mixing models need to fully account for uncertainty in order to accurately estimate source contributions.     

Merging resource availability with isotope mixing models: the role of neutral interaction assumptions

Background

Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator''s diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values.

Methodology

We develop a procedure to incorporate prey availability data into Bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator''s diet. We test the utility of this method in an intertidal community against independently measured feeding rates.

Conclusions

Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator''s diet cannot be assumed for all species in a system.     

SIDER: an R package for predicting trophic discrimination factors of consumers based on their ecology and phylogenetic relatedness

Stable isotope mixing models (SIMMs) are an important tool used to study species' trophic ecology. These models are dependent on, and sensitive to, the choice of trophic discrimination factors (TDF) representing the offset in stable isotope delta values between a consumer and their food source when they are at equilibrium. Ideally, controlled feeding trials should be conducted to determine the appropriate TDF for each consumer, tissue type, food source, and isotope combination used in a study. In reality however, this is often not feasible nor practical. In the absence of species‐specific information, many researchers either default to an average TDF value for the major taxonomic group of their consumer, or they choose the nearest phylogenetic neighbour for which a TDF is available. Here, we present the SIDER package for R, which uses a phylogenetic regression model based on a compiled dataset to impute (estimate) a TDF of a consumer. We apply information on the tissue type and feeding ecology of the consumer, all of which are known to affect TDFs, using Bayesian inference. Presently, our approach can estimate TDFs for two commonly used isotopes (nitrogen and carbon), for species of mammals and birds with or without previous TDF information. The estimated posterior probability provides both a mean and variance, reflecting the uncertainty of the estimate, and can be subsequently used in the current suite of SIMM software. SIDER allows users to place a greater degree of confidence on their choice of TDF and its associated uncertainty, thereby leading to more robust predictions about trophic relationships in cases where study‐specific data from feeding trials is unavailable. The underlying database can be updated readily to incorporate more stable isotope tracers, replicates and taxonomic groups to further increase the confidence in dietary estimates from stable isotope mixing models, as this information becomes available.     

Spatial analysis of stable isotope data to determine primary sources of nutrition for fish

Carbon and nitrogen stable isotopes were used to determine the ultimate autotrophic sources supporting production of three commercially important fish species over unvegetated mudflats in a subtropical estuary. Mean isotope values over the whole estuary for fish and autotroph sources were modeled to indicate feasible combinations of sources. Variability in isotope values among nine locations (separated by 3-10 km) was then used as a further test of the likelihood that sources were involved in fish nutrition. A positive spatial correlation between isotope values of a fish species and an autotroph indicates a substantial contribution from the autotroph. Spatial correlations were tested with a newly developed randomization procedure using differences between fish and autotroph values at each location, based on carbon and nitrogen isotopes combined in two-dimensional space. Both whole estuary modeling and spatial analysis showed that seagrass, epiphytic algae and particulate organic matter in the water column, including phytoplankton, are likely contributors to bream (Acanthopagrus australis) nutrition. However, spatial analysis also showed that mangroves were involved (up to 33% contribution), despite a very low contribution from whole estuary modeling. Spatial analysis on sand whiting (Sillago ciliata) demonstrated the importance of two sources, mangroves (up to 25%) and microalgae on the mudflats, considered unimportant based on whole estuary modeling. No spatial correlations were found between winter whiting (Sillago maculata) and autotrophs, either because fish moved among locations or relied on different autotrophs at different locations. Spatial correlations between consumer and source isotope values provide a useful analytical tool for identifying the role of autotrophs in foodwebs, and demonstrated here that both in situ production of microalgae and organic matter from adjacent habitats were important to fish over mudflats.     

Source Partitioning Using Stable Isotopes: Coping with Too Much Variation

Background

Stable isotope analysis is increasingly being utilised across broad areas of ecology and biology. Key to much of this work is the use of mixing models to estimate the proportion of sources contributing to a mixture such as in diet estimation.

Methodology

By accurately reflecting natural variation and uncertainty to generate robust probability estimates of source proportions, the application of Bayesian methods to stable isotope mixing models promises to enable researchers to address an array of new questions, and approach current questions with greater insight and honesty.

Conclusions

We outline a framework that builds on recently published Bayesian isotopic mixing models and present a new open source R package, SIAR. The formulation in R will allow for continued and rapid development of this core model into an all-encompassing single analysis suite for stable isotope research.     

Methodological uncertainty in resource mixing models for generalist fishes

Carbon and nitrogen stable isotope ratios are used to assess diet composition by determining bounds for the relative contributions of different prey to a predator's diet. This approach is predicated on the assumption that the isotope ratios of predator tissues are similar to those of dominant food sources after accounting for trophic discrimination (Δ(x)X), and is formulated as linear mixing models based on mass balance equations. However, Δ(x)X is species- and tissue-specific and may be affected by factors such as diet quality and quantity. From the different methods proposed to solve mass balance equations, some assume Δ(x)X to be exact values whilst others (based on Bayesian statistics) incorporate variability and inherent uncertainty. Using field data from omnivorous reef fishes, our study illustrates how uncertainty may be taken into account in non-Bayesian models. We also illustrate how dietary interpretation is a function of both absolute Δ(x)X and its associated uncertainty in both Bayesian and non-Bayesian isotope mixing models. Finally, collated literature illustrate that uncertainty surrounding Δ(x)X is often too restricted. Together, these data suggest the high sensitivity of mixing models to variation in trophic discrimination is a consequence of inappropriately constrained uncertainty against highly variable Δ(x)X. This study thus provides guidance on the interpretation of existing published mixing model results and in robust analysis of new resource mixing scenarios.     

Quantifying Inter- and Intra-Population Niche Variability Using Hierarchical Bayesian Stable Isotope Mixing Models

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.