应用修正的Gash解析模型对岷江上游亚高山川滇 高山栎林林冠截留的模拟

修正的Gash解析模型具有较好的物理基础,是目前估算和预测林冠截留的有效工具。基于2007年6月到9月的降雨数据、气象和林分结构资料,采用修正的Gash解析模型对岷江上游川滇高山栎林冠截留进行了模拟。结果表明,林冠持水能力为0.23mm,树干持水能力为0.041mm,树干茎流系数为0.013,使林冠饱和的降雨为0.3mm;研究期间实测的林冠截留量为80.2mm,占总降雨量的16.5%,应用模型模拟的林冠截留总量为81.8mm,高于实测值1.6mm(高于实测值2.0%),林冠截留和树干茎流周累积量模拟值均与实测值有很好的一致性,敏感性分析结果显示,应用修正的Gash解析模型进行岷江上游川滇高山栎林冠截留模拟研究中,模型最易受林冠持水能力影响,其次为郁闭度、树干持水能力,影响最小的林分参数为树干茎流系数。     

基于本土最优模型模拟入侵物种水盾草在中国的潜在分布

生态位模型预测存在不确定性, 不同模型预测结果差别较大。在生态位保守的前提下, 在本土区域构建经典生态位模型, 利用入侵地独立样本数据检验并选择最优模型, 具有独特优势, 可为入侵物种风险分析提供可靠参考。水盾草(Cabomba caroliniana)是一种恶性水生入侵杂草, 原产于南美洲, 已在我国多个省市建立种群, 本文基于本土最优模型预测其在我国的潜在分布, 以期为其风险分析和综合治理提供依据, 并通过水盾草案例探讨如何提高生态位模型预测准确性的方法。本文按时间顺序梳理了水盾草在我国的分布记录, 然后根据水盾草已有分布记录和其所关联的环境因子比较了不同地理种群所占有的气候生态空间, 测试水盾草在世界入侵过程中的现实生态位保守性。采用两组环境变量和5种算法在南美洲本土地区构建10种生态位模型, 并将其转移至我国, 基于最小遗漏率和记账错率, 利用我国(入侵地)的样本数据选择最优模型预测水盾草在我国的适宜生态空间和潜在分布。研究发现当前水盾草在我国的分布集中在东部水域充沛地区, 沿京杭运河和南水北调工程等向北扩散。生态空间比对中发现水盾草在亚洲与其他大洲所占有的生态空间具有一定的重叠, 其在我国的入侵过程中生态位是保守的。与本土空间相比, 水盾草在我国所占有的生态空间存在较大的生态位空缺, 表明水盾草在我国的潜在分布范围较大。生态位模型预测显示水盾草的适生区主要分布于我国的北京、上海、山东、浙江、江苏、安徽、湖北和湖南等省(市)。水盾草的潜在分布区多聚集在我国东南部, 该地区河流、湖泊、运河和渠道较为密集, 人类活动及自然天敌的缺乏容易助长其入侵趋势, 应在这些适宜地区开展调查, 及时发现疫情并采取相应措施。     

黑河流域高寒草甸生态系统水分收支及蒸散发拆分研究

水分收支是对水循环要素降水、蒸发蒸腾、径流以及土壤贮储水量变化等的定量刻画,对水资源的可持续开发及利用至关重要。基于黑河流域阿柔观测站2014和2015年水文气象观测数据,运用水量平衡理论,定量的评估了高寒草甸生态系统的水分收支动态,并结合双源模型对高寒草甸生态系统蒸散发(植被蒸腾和土壤蒸发)进行拆分及评价。研究结果表明(1)在生长季(5—9月)植被蒸腾是高寒草甸生态系统主要的耗水形式,2014和2015年生长季平均蒸散比(T/ET)分别为0.74和0.79;(2)土壤水分的剧烈变化主要发生在0—40 cm处,且受冻融过程影响显著;(3)在降水较多的年份(2014)高寒草甸生态系统水分收支基本平衡,且不受冻融影响的月份(6—9)有地表径流产生约42 mm;在正常年份(2015),生态系统呈现水分亏缺,亏缺量约为134 mm,6—9月约亏缺26 mm;(4)模型估算蒸散发(ET)与实测蒸散发具有很好的一致性,相关系数可达0.90,敏感性分析表明模型输入变量对蒸散发(ET)及蒸散比(T/ET)产生的误差较小,双源模型可以很好地实现对高寒草甸生态系统蒸散发(ET)的拆分。     

Using temporally explicit habitat suitability models to assess threats to mobile species and evaluate the effectiveness of marine protected areas

A principal role of marine protected areas (MPAs) is to mitigate the decline of biodiversity. A key part of this role is to reduce the effects of fisheries on bycatch of vulnerable species. Bycatch can have an impact on species by reducing population sizes, and an ecosystem-level impact through the significant removal of biomass and subsequent trophic changes. In this regard, it is crucial to refine methods for quantifying interactions between fisheries and bycatch species, and to manage these interactions spatially. A new method is presented for quantifying interactions between fisheries and bycatch species at high spatial and temporal resolutions. Temporally explicit species distribution models are used to examine temporal dynamics of fisheries and bycatch. This method is applied to Australia’s Eastern Tuna and Billfish Fishery to estimate interactions with seven principal bycatch species. The ability of MPAs to reduce bycatch is evaluated, and considerations are outlined for the spatial management of fishery-bycatch species interactions. Australia’s Commonwealth Marine Reserve Network had a minimal impact on bycatch reduction under both the 2012 proclaimed and the 2015 panel-recommended zonings. These results highlight the need for threats to marine biodiversity to be incorporated directly into design of MPAs, and for close scrutiny of assumptions that threats will be incidentally abated after MPAs have been proclaimed, or that off-reserve mechanisms will compensate for inadequacies of MPAs.     

A model to predict the presence of longfin eels in some New Zealand streams, with particular reference to riparian vegetation and elevation

Two logistic regression models were developed from a database of 27 biotic and physicochemical variables for 99 sites in the Taieri River, New Zealand, to predict the probability of occurrence of longfin eels. Average depth was associated positively with eels while woody debris and oxygen concentration were negatively associated. At a macro-scale probability of eel occurrence declined with increasing elevation and, for a given elevation, was higher in tussock and pasture catchments and lower in pine and native forest settings. Using a separate fish database for the Taieri River this macro-scale model predicted eel presence 95·4% in agreement with observation. A map was generated from the model showing areas of predicted high, moderate and low probabilities of eel occurrence. The model also estimated the minimum total number of eels present in the Taieri River catchment (excluding lakes, and streams below 100 m and above 1000 m) as 20 865 (95% CL: 10 560-36 350).     

滦河干流中上游浮游细菌群落多样性及其影响因素

浮游细菌是河流生态系统中营养元素的转运者和能量流动的主要贡献者,其群落组成和多样性会受沿途河岸带环境的影响,但目前对开放流动水体中浮游细菌群落的研究还不足。研究使用高通量测序方法,获取了滦河中上游21个样点的浮游微生物群落数据,并结合遥感数据和水体理化指标进行分析,探讨浮游细菌群落结构与水环境因子的关系。结果表明：(1)变形菌门和放线菌门是滦河干流中占据优势地位的门类。(2)群落Chao1丰富度指数与Shannon′s多样性指数均与采样点距河流源头距离存在显著负相关(P<0.05),其中Chao1丰富度指数在河流中段的反常升高暗示着外源性偶见种在该河段的大量涌入。(3)采样点距源头距离与细菌群落组成相关性最高;以距源头距离作为控制变量,只有总氮、硝酸盐氮、氨氮与细菌群落组成相关(P<0.05),表明距源头距离所代表的滞水时间和氮营养盐对细菌群落组成存在显著影响。(4)在4种土地利用因子中,无论是否以距源头距离作为控制变量,只有建设用地占比与细菌群落组成相关(P<0.05);若以硝酸盐氮、电导率作为控制变量,则建设用地占比与细菌群落组成在α=0.05的显著性水平下不再显...     

Temporal and spatial trends in nitrogen and phosphorus inputs to the watershed of the Altamaha River,Georgia, USA

The watershed of the Altamaha River, Georgia, is one of the largest in the southeastern U.S., draining 36,718 km² (including parts of metro Atlanta). We calculated both nitrogen (fertilizer, net food and feed import, atmospheric deposition, and biological N fixation in agricultural and forest lands) and phosphorus (fertilizer and net food and feed import) inputs to the watershed for 6 time points between 1954 and 2002. Total nitrogen inputs rose from 1,952 kg N km⁻² yr⁻¹ in 1954 to a peak of 3,593 kg N km⁻² yr⁻¹ in 1982 and then declined to 2,582 kg N km⁻² yr⁻¹ by 2002. Phosphorus inputs rose from 409 kg P km⁻² yr⁻¹ in 1954 to 532 kg P km⁻² yr⁻¹ in 1974 before declining to 412 kg P km⁻² yr⁻¹ in 2002. Fertilizer tended to be the most important input of both N and P to the watershed, although net food and feed import increased in importance over time and was the dominant source of N input by 2002. When considered on an individual basis, fertilizer input tended to be highest in the middle portions of the watershed (Little and Lower Ocmulgee and Lower Oconee sub-watersheds) whereas net food and feed imports were highest in the upper reaches (Upper Oconee and Upper Ocmulgee sub-watersheds). Although the overall trend in recent years has been towards decreases in both N and P inputs, these trends may be offset due to continuing increases in animal and human populations.     

Combining point‐process and landscape vegetation models to predict large herbivore distributions in space and time—A case study of Rupicapra rupicapra

Aim

When modelling the distribution of animals under current and future conditions, both their response to environmental constraints and their resources’ response to these environmental constraints need to be taken into account. Here, we develop a framework to predict the distribution of large herbivores under global change, while accounting for changes in their main resources. We applied it to Rupicapra rupicapra, the chamois of the European Alps.

Location

The Bauges Regional Park (French Alps).

Methods

We built sixteen plant functional groups (PFGs) that account for the chamois’ diet (estimated from sequenced environmental DNA found in the faeces), climatic requirements, dispersal limitations, successional stage and interaction for light. These PFGs were then simulated using a dynamic vegetation model, under current and future climatic conditions up to 2100. Finally, we modelled the spatial distribution of the chamois under both current and future conditions using a point‐process model applied to either climate‐only variables or climate and simulated vegetation structure variables.

Results

Both the climate‐only and the climate and vegetation models successfully predicted the current distribution of the chamois species. However, when applied into the future, the predictions differed widely. While the climate‐only models predicted an 80% decrease in total species occupancy, including vegetation structure and plant resources for chamois in the model provided more optimistic predictions because they account for the transient dynamics of the vegetation (?20% in species occupancy).

Main conclusions

Applying our framework to the chamois shows that the inclusion of ecological mechanisms (i.e., plant resources) produces more realistic predictions under current conditions and should prove useful for anticipating future impacts. We have shown that discounting the pure effects of vegetation on chamois might lead to overpessimistic predictions under climate change. Our approach paves the way for improved synergies between different fields to produce biodiversity scenarios.

     

黑河上游植被总初级生产力遥感估算及其对气候变化的响应

定量描述植被总初级生产力(GPP)对于全球碳循环和全球气候变化研究具有重要意义。针对MODIS MOD_17 GPP (MOD_17)产品在通量站点低估的现象, 通过3个实验依次改进了模型输入参数(气象数据和吸收的光合有效辐射吸收比例(fPAR))和模型本身的参数(最大光能利用率), 分析了各个参数对模拟结果的不确定性影响, 结果表明各参数对模拟结果都有不同程度的影响。在阿柔草地站, 最大光能利用率的重新标定对结果影响最大, GPP估算结果的提高最为明显; 在关滩森林站利用广义神经网络算法得到的GLASS fPAR代替原始MODIS fPAR产品, 比其他参数的改进效果更明显, GPP的值更接近涡动通量观测值。利用改进的MOD_17模型重新估算了黑河上游2001-2012年间植被GPP, 通过趋势分析得出该研究时段内GPP以9.58 g C·m^-2·a^-1的平均速率呈上升趋势。同时计算了气候因子(温度、降水和饱和水汽压差(VPD))与时间序列GPP的偏相关性, 分析了植被GPP对气候变化的响应情况, 2001-2012年平均温度和VPD与年GPP大部分区域呈正相关, 体现了温度和VPD对植被生长的促进作用; 2001-2012年的降水量与年GPP无明显相关, 且大部分区域呈负相关。     

随机配对法在亚高山草甸优势种群格局分析中的应用

随机配对法是植物种群格局分析的主要方法之一,理论上讲它是最好的方法,因为他改进了等级方差法的所有缺点.但该方法还没有在我国研究实践中应用过.本文将随机配对法应用于芦芽山亚高山草甸群落优势种群的格局研究.结果较好地反映了种群的空间特征.该方法分辨力较强,可以揭示各种格局规模.     

Current and future distribution of the deciduous shrub Hydrangea macrophylla in China estimated by MaxEnt

Climate change has a significant impact on the growth and distribution of vegetation worldwide. Hydrangea macrophylla is widely distributed and considered a model species for studying the distribution and responses of shrub plants under climate change. These results can inform decision‐making regarding shrub plant protection, management, and introduction of germplasm resources, and are of great importance for formulating ecological countermeasures to climate change in the future. We used the maximum entropy model to predict the change, scope expansion/reduction, centroid movement, and dominant climate factors that restrict the growth and distribution of H. macrophylla in China under current and future climate change scenarios. It was found that both precipitation and temperature affect the distribution of suitable habitat for H. macrophylla. Akaike information criterion (AICc) was used to select the feature combination (FC) and the regularization multiplier (RM). After the establishment of the optimal model (FC = QP, RM = 0.5), the complexity and over‐fitting degree of the model were low (delta AICc = 0, omission rate = 0.026, difference between training and testing area under the curve values = 0.0009), indicating that it had high accuracy in predicting the potential geographical distribution of H. macrophylla (area under the curve = 0.979). Overall, from the current period to future, the potential suitable habitat of this species in China expanded to the north. The greenhouse effect caused by an increase in CO₂ emissions would not only increase the area of high‐suitability habitat in Central China, but also expand the area of total suitable habitat in the north. Under the maximum greenhouse gas emission scenario (RCP8.5), the migration distance of the centroid was the longest (e.g., By 2070s, the centroids of total and highly suitable areas have shifted 186.15 km and 89.84 km, respectively).     

Using the robust design framework and relative abundance to predict the population size of pallid sturgeon Scaphirhynchus albus in the lower Missouri River

Several population viability models were constructed to aid recovery in endangered Scaphirhynchus albus, but these models are dependent upon accurate and precise input parameters that are not provided with standard catch per unit effort (CPUE) indices. Nine years of sampling efforts, under the robust design framework, provided 1223 unique captures with an 18·3% recapture rate. The annual population estimates varied from 4·0–7·3 fish rkm^?1 for wild and 8·4–18·4 fish rkm^?1 for hatchery‐reared S. albus. The relationship between abundance (N) and annual trot‐line CPUE indices (x = 70.726y + 2·533, R² = 0·91, P < 0·001) was used to predict an abundance of 13 616 ± 7142 s.e. S. albus in the lower Missouri River. The use of small‐scale intensive sampling to develop a relationship with relative abundance indices reported here, may provide a framework for other fisheries management applications where large‐scale intensive sampling is not feasible, but catch data are available.     

Fragmentation and thermal risks from climate change interact to affect persistence of native trout in the Colorado River basin

Impending changes in climate will interact with other stressors to threaten aquatic ecosystems and their biota. Native Colorado River cutthroat trout (CRCT; Oncorhynchus clarkii pleuriticus) are now relegated to 309 isolated high‐elevation (>1700 m) headwater stream fragments in the Upper Colorado River Basin, owing to past nonnative trout invasions and habitat loss. Predicted changes in climate (i.e., temperature and precipitation) and resulting changes in stochastic physical disturbances (i.e., wildfire, debris flow, and channel drying and freezing) could further threaten the remaining CRCT populations. We developed an empirical model to predict stream temperatures at the fragment scale from downscaled climate projections along with geomorphic and landscape variables. We coupled these spatially explicit predictions of stream temperature with a Bayesian Network (BN) model that integrates stochastic risks from fragmentation to project persistence of CRCT populations across the upper Colorado River basin to 2040 and 2080. Overall, none of the populations are at risk from acute mortality resulting from high temperatures during the warmest summer period. In contrast, only 37% of populations have a ≥90% chance of persistence for 70 years (similar to the typical benchmark for conservation), primarily owing to fragmentation. Populations in short stream fragments <7 km long, and those at the lowest elevations, are at the highest risk of extirpation. Therefore, interactions of stochastic disturbances with fragmentation are projected to be greater threats than warming for CRCT populations. The reason for this paradox is that past nonnative trout invasions and habitat loss have restricted most CRCT populations to high‐elevation stream fragments that are buffered from the potential consequences of warming, but at risk of extirpation from stochastic events. The greatest conservation need is for management to increase fragment lengths to forestall these risks.     

Mapping the vertical distribution of maize roots in China in relation to climate and soil texture

Aims Optimizing water and fertilizer management for crops requires an understanding of root distribution. Maize (Zea maysL.) is currently the most widely planted cereal crop in China, yet the vertical distribution of maize roots across different regions remains unknown. The aims of this work were (i) to quantify the effects of climate and soil texture on the vertical distribution of maize roots, and (ii) to show the depth distribution of root biomass in China.     

Using a nitrogen and oxygen isotopic approach to identify nitrate sources and cycling in the Wei River of northwestern China

The Wei River is the largest tributary of the Yellow River in China. To understand the sources and cycling of nitrate in the Wei River, we determined the concentrations and nitrogen and oxygen isotopic values of nitrate from water samples. Our results revealed that NO₃^?-N dominated the inorganic N and ranged from 0.1 to 8.8 mg/L (averaging 3.3 mg/L). Although this NO₃^?-N concentration does not exceed the World Health Organization's drinking water standard of 10 mg/L, the NO₃^?-N content of most water samples exceeded 3 mg/L, indicating poor water quality. The NO₃^?-N concentrations and δ¹⁵N-NO₃^? values demonstrate that there are significant differences in the spatial distribution of nitrogen between the tributaries and the main stream of the Wei River. In addition, a negative linear relationship (r² = 0.63) between NO₃^?-N concentrations and δ¹⁸O-NO₃^? values suggests mixing between two distinct sources (fertilizer and manure or sewage). Furthermore, we infer that the main source of nitrate is not manure or sewage itself, but rather the nitrification of NH₄⁺ in manure and sewage. Finally, no obvious denitrification processes were observed. These results expand our understanding of sewage as a major source of nitrate to the Wei River, emphasizing the role of nitrification.     

渭河底栖动物性状和功能对空间尺度环境变量响应的生态区差异性

以我国中部渭河南部流域山区和平原生态区的底栖动物为研究对象,通过计算29个生物性状类别和7个功能多样性指数,比较了不同生态区的生物性状组成和功能与性状多样性指数差异性;应用综合RLQ和fourth-corner方法探索底栖动物生物性状组成与土地利用和理化变量的关系;通过广义线性模型(GLM)比较不同空间尺度环境变量对底栖动物功能与性状多样性指数影响的生态区差异性。研究发现,共18个底栖动物性状组成在山区和平原间存在显著差异性,其中具有无庇护所和以叶片为庇护所材料、外骨骼轻微骨化和骨化良好、草食性、捕食性等生物性状的底栖动物栖息于栖境状况较好的山区,体壁呼吸、虫体柔软、集食者等生物性状更多的集中在人类活动较严重的平原区。除了功能均匀度指数外,山区的性状和功能多样性指数均显著高于平原,说明平原环境干扰显著降低了底栖动物性状和功能多样性。综合RLQ和fourth-corner方法表明底栖动物生物性状对环境胁迫的响应存在可预测性。GLM模型结果表明,山区和平原生物性状和功能多样性指数受到不同空间尺度土地利用和理化环境变量的影响:流域尺度城镇用地、水温和TN含量是影响山区功能和性状多样性指数模型的重要环境变量,但平原区河段尺度农业用地面积百分比和平均水深是影响功能和性状多样性的主要因子。     

珠三角地区PM2.5浓度估算及其健康效应评估

快速的社会经济发展导致城市出现以PM_2.5为首要污染物的空气污染问题,PM_2.5污染严重危害人群健康。因此,厘清PM_2.5时空分布特征并估算其带来的健康影响,对于PM_2.5的区域联防联控具有重要意义。现有研究中,为弥补地面监测数据的不足,借助机器学习算法估算PM_2.5浓度成为研究热点,此外,基于流行病学研究结果的健康效应模型也被广泛用于评估PM_2.5健康影响的研究中。利用珠江三角洲地区2014-2018年56个空气质量监测站的PM_2.5实时监测数据、气象数据、社会经济数据和归一化植被指数,构建随机森林模型,多要素联合估算2000-2018年监测站点的PM_2.5浓度,并采用克里金插值方法获得PM_2.5浓度的空间分布,在此基础上应用全球暴露死亡（GEMM）模型,评估珠三角地区的PM_2.5健康效应。结果表明：（1）2000-2018年期间,珠三角地区的PM_2.5算术年均浓度维持在35μg/m³左右,呈现"西北-东南"递减空间分异;降水量、温度、风速和水汽压等气象因子对PM_2.5浓度具有负向影响,GDP和人口密度等社会经济因子对PM_2.5浓度具有正向影响。（2）2000-2018年期间,珠三角地区PM_2.5人口加权年均浓度均低于PM_2.5算术年均浓度,表明珠三角地区人口密度和PM_2.5浓度未呈现明显的空间匹配关系,例如肇庆PM_2.5浓度较高但人口密度较低,深圳PM_2.5浓度较低但人口密度较高。（3）2000-2018年期间,珠三角地区PM_2.5污染对于缺血性心脏病和中风的健康影响较显著,而对下呼吸道感染的健康影响较弱。区域PM_2.5相关过早死亡人数逐渐增多,主要集中在PM_2.5浓度和人口密度较高的地区,例如珠三角中心地区,以广州中心城区表现明显。本研究建议珠三角地区加大空气污染治理力度,提高医疗服务水平,同时关注城市人口结构,引导城市人口有序流动迁移,以缓解PM_2.5带来的健康影响,实现城市化的健康发展。     

Using the output from global circulation models to predict changes in the distribution and abundance of cereal aphids in Canada: a mechanistic modeling approach

Climate change will alter the abundance and distribution of species. Predicting these shifts is a challenge for ecologists and essential information for the formation of public policy. Here, I use a mechanistic mathematical model of the interaction between grass growth physiology and aphid population dynamics, coupled with the climate change projections from the UK's Hadley Centre HadCM3 global circulation model (GCM) and Canada's Center for Climate Modeling and Analysis CGCM2 GCM to predict the changes in the abundance and distribution of summer cereal aphid populations in wheat-growing regions of Canada. When used with the HadCM3 projections, the model predicts a latitudinal shift northward in abundances but there is longitudinal variation as well. However, when used with the CGCM2 projections the model predicts that continental regions will see a decline while coastal regions will see an increase in summer cereal aphid populations. These effects are stronger under the higher emissions scenarios.     

Using a trait‐based approach for assessing the vulnerability and resilience of hillslope seep wetland vegetation cover to disturbances in the Tsitsa River catchment,Eastern Cape,South Africa

Hill slope seep wetlands are ecologically and economically important ecosystems as they supply a variety of ecosystem services to society. In South Africa, livestock grazing is recognized as one of the most important disturbance factors changing the structure and function of hill slope seep wetlands. This study sought to investigate the potential effect of livestock grazing on the resilience and vulnerability of hillslope seep wetland vegetation cover using a trait‐based approach (TBA). Changes in vegetation cover were used as a surrogate for indicating grazing intensity. The degree of human disturbances was assessed using the Anthropogenic Activity Index. A TBA was developed using seven plant traits, resolved into 27 trait attributes. Based on the developed approach, plant species were grouped into vulnerable and resilient groups in relation to grazing pressure. It was then predicted that species belonging to the vulnerable group would be less dominant at the highly disturbed sites, as well as in the winter season when grazing pressure is at its peak. The approach developed enabled accurate predictions of the responses of hillslope plant species to grazing pressure seasonally, but spatially, only for the summer season. The predicted responses during the winter season across sites did not match the observed results, which could be attributed to the difficulty in species identification and accurate estimation of vegetation cover during winter. Overall, the approach developed here provides a general framework for applying the TBA and can thus be tested and applied elsewhere.