Oceanographic anomalies and sea‐level rise drive mangroves inland in the Pacific coast of Mexico

Question: Although mangrove forests are generally regarded as highly threatened, some studies have shown that mangrove canopies in the Pacific coast of Mexico have been increasing in recent decades. We investigated the possible causes driving this reported mangrove expansion. Location: The mangrove lagoons of Magdalena Bay in Baja California, Mexico. Methods: We used 50‐year‐old aerial photographs and 24‐year‐old satellite images to compare long‐term vegetation change, surveyed a coastal vegetation transect to analyse flooding levels, compiled six decades of tidal and oceanographic information, as well as hurricane data to analyse changes in storm frequency or sea‐level conditions, and used isotopic analysis to date the age of trees along the gradient. Results: A significant increase in mangrove cover has occurred in backwaters of the lagoons during the last 40 years, and especially during the El Niño anomalies of the 1980s and 1990s, while at the same time the mangrove fringe has been receding. Conclusions: The observed change can be attributed to the combined action of the warm surface waters of El Niño events and sea‐level rise. Jointly, these two effects are sufficient to flood large areas of previously non‐flooded salt flats, dispersing mangrove seedlings inland. The inland expansion of mangroves, however, does not ease conservation concerns, as it is the seaward fringes, and not the inland margins, that provide the most valuable environmental services for fisheries and coastal protection.     

水文情势与盐分变化对湿地植被的影响研究综述

湿地植被是湿地生态系统的重要组成部分。水文情势与盐分变化直接影响到湿地植被的分布与演替。目前,全球气候变化和人类活动导致的水文情势改变与盐分聚集已造成大面积的湿地退化和盐渍化,已严重威胁全球淡水湿地生态系统的稳定和健康。系统总结了水文情势与盐分变化单一环境变量及其交互作用对湿地植物生理生态、物种多样性、群落结构与演替和植被动态等诸多方面的影响研究进展,并探讨了湿地水文动态-盐分变化-植被响应的综合模型研究现状,认为发展湿地综合模型预测未来水文情势与盐分变化情景下湿地演变,是应对气候变化湿地水盐管理和生态保护的重要工具,最后指出今后亟需加强的研究方向。     

陕北风沙区不同植被覆盖下的土壤养分特征

选取了陕北定边县板凳滩风沙区四种典型植被覆盖下的风沙土壤,对其基本养分含量进行了测定。分析不同类型植被覆盖下的土壤养分含量特征、土壤养分含量层次特征以及土壤各层次养分含量之间的相关性,为风沙区土壤生态恢复重建及侵蚀土壤质量的恢复保育提供了科学依据。结果表明:(1)不同植被覆盖下的土壤对有机质、全氮、速效氮、速效磷的保持能力均为:小蒿草>羊草>沙蒿>苦豆子>无植被;对全磷的保持能力,各植被覆盖条件下差异不显著,但小蒿草覆盖下含量最高,羊草最低,且低于无植被;从土壤对全钾的保持能力来看,羊草覆盖下的全钾含量最高,小蒿草最低。(2)不同植被覆盖下的土壤养分含量层次变化除全磷和全钾变化微弱外,土壤有机质、全氮、速效氮、速效磷、速效钾含量均随着土层深度的增加而逐渐下降,且降低速度基本呈现出小蒿草>羊草>沙蒿>苦豆子>无植被。(3)不同植被覆盖下的土壤各层次养分含量之间的相关性以羊草最为密切,大体呈显著中度及以上正相关;沙蒿和苦豆子覆盖下的相关性稍弱,基本呈中度正相关;而小蒿草覆盖下的相关系数正负均有,相关性较为复杂。     

基于遥感和GIS的川西绿被时空变化研究

探索出了利用多时相MODIS数据分析绿被时空变化的技术方法,揭示出了川西2002—2008年间绿被的变化特征。建立了绿被提取模型。用其从2002—2008年的多期MODIS影像中提取出川西多期绿被数据。其次,利用GIS技术对2002—2008年间绿被变化,及其与温度、降雨的关系等进行了分析。研究表明:2002年绿被天数在195 d以上的区域有43.3%。终年无绿被的区域有4.3%。西北部植被生长日数短,而东南部生长日数长。2002—2008年间,春季绿被面积变幅最大,秋季最小。最大绿被面积出现在2006年的夏季,最小绿被面积出现在2005年的冬季。平均夏冬绿被面积差占区域面积46.7%。在季节上,绿被面积与温度和降雨量均在0.01的水平上呈显著正相关关系,其相关系数分别为0.82和0.84。该研究成果对植被生长潜力挖掘、农牧生产和生态建设决策等均有重要意义。     

林隙干扰和升温对小兴安岭红松和臭冷杉径向生长的影响

通过建立小兴安岭阔叶红松(Pinus koraiensis)林内林隙与非林隙红松、臭冷杉(Abies nephrolepis)轮宽年表,分析林隙干扰(微环境差异)和1980年后显著升温对树木径向生长的影响。结果表明:升温减缓了非林隙红松生长,却加快了林隙红松生长;升温后,非林隙红松受温度影响减弱,而林隙红松则增强,林隙和非林隙红松径向生长与帕默尔干旱指数(Palmer drought severity index,PDSI)均由负相关变为正相关;林隙干扰导致臭冷杉径向生长减缓,升温导致林隙与非林隙臭冷杉年生长量均下降了约50%,非林隙木对温度的负响应要高于林隙木;升温后,5—10月温度对非林隙木抑制作用明显,非生长季(1—5月)降水对非林隙臭冷杉的抑制作用加强,而对林隙臭冷杉则由抑制变为促进;PDSI与非林隙臭冷杉由升温前的负相关变为升温后的正相关,而林隙臭冷杉则负相关更显著;林隙干扰减少耐荫喜湿树木径向生长,而对阳性树种影响不大或略有增加;林隙木比非林隙木更易受外界环境变化的影响,林隙干扰可使喜湿耐荫树种提前适应暖干环境,以提高了对升温适应性;升温导致林隙木与非林隙木年轮气候响应差异变大。     

基于VAR模型的森林植被碳储量影响因素分析——以陕西省为例

森林作为陆地生态系统最大的碳库,对现在及未来的气候变化、碳平衡都具有重要影响。而对影响森林植被碳库的自然和非自然因素进行研究更是对增强森林的碳汇作用,继而改善生态环境状况意义重大。现有的森林动态模型虽然可以很好的模拟碳储量各影响因子之间的联系,但研究往往集中于小尺度从单一影响因素着手,且由于确定模型输入变量和参数的复杂性,使得这些模型在区域甚至更大尺度上的应用存在着一些困难。因此,运用VAR模型,以陕西省为例,构建森林植被碳储量与病虫害发生面积、木材产量、森林火灾面积、森林抚育面积、人工更新造林面积、降水和温度之间的动态关系,来验证该模型在省级尺度条件下的区域森林植被碳储量影响因素分析中的可行性。结果表明:各变量在5%的显著性水平下呈一阶单整序列并具有长期稳定的均衡关系,VAR模型也通过了平稳性检验满足运行的前提条件。通过脉冲响应和方差分解分析可知,森林病虫害、木材产量对陕西省森林植被碳储量呈现出很明显的负作用,并且贡献度很高,分别为5.61%和4.52%;森林抚育、人工更新造林对碳储量的影响存在一定的滞后期;火灾、温度和降水的冲击给碳储量带来的影响均不明显。模型较好的模拟了各影响因素对陕西省碳储量的影响,且具有一定的现实意义,因此,该模型可应用于省级尺度条件下的区域森林植被碳储量影响因素分析。     

基于中高分辨率遥感的植被覆盖度时相变换方法

植被覆盖度是衡量地表植被状况、指示生态环境变化的一个重要指标,也是许多学科的重要参数。传统的测量方法难以获取时间连续的面状数据,且耗时、耗力,很难大范围推广。遥感估算方法虽然可以弥补传统方法的不足,但由于云覆盖等天气条件的影响,获得同一时相覆盖整个研究区的遥感影像非常困难,时相的差异必然导致研究结果产生误差。针对植被覆盖度这一重要生态参数,结合低分辨率遥感数据的时间优势和中高分辨率遥感数据的空间优势,提出一种时相变换方法,将源于中高分辨率影像的植被覆盖度变换到研究需要的时相上。首先,利用像元二分模型计算MODIS尺度的时间序列植被覆盖度,并利用已经获得的SPOT影像计算其获取时相上的植被覆盖度;其次,利用土地利用图划分植被覆盖类型,并利用MODIS数据和土地利用数据之间的空间对应关系制作MODIS像元内各类植被覆盖的面积百分比数据;再次,利用面积百分比数据提取各类植被覆盖的纯像元,结合MODIS植被覆盖度时间序列,从而提取各类植被覆盖纯像元的植被覆盖度时间序列曲线;最后利用像元分解的方法提取MODIS像元内各类植被覆盖组分的植被覆盖度的变化规律,将其应用到该组分对应位置上SPOT像元的植被覆盖度上,从而将其变换到所需要的时相上。在密云水库上游进行试验,将覆盖研究区的10景SPOT5多光谱影像计算的植被覆盖度统一变换到7月上旬,结果显示:视觉效果上明显好转,且空间上连续一致;变换前后植被覆盖度的统计量对比结果也符合植被生长规律;利用外业样点数据与对应位置的植被覆盖度变换结果进行回归分析,结果发现各植被覆盖类型的R2均在0.8左右,表明变换结果与实测值非常接近,时相变换的效果较好,从而可以很好地促进相关研究精度的提高。     

Estimation of aboveground biomass in conserved areas of Stipa tenacissima L. stands in the high steppes of western Algeria by mean of the Landsat 8 imagery‐based vegetation indices

The main aim of this paper was to evaluate the use of OLI spectral data as a tool to assess the steppe vegetation in a conservation context. The field sampling was conducted for two specific areas of treatment (a) an exclosure area and (b) a free grazing area. After testing several vegetation indices (VIs), the optimal results were obtained for the Normalised Difference Vegetation Index (NDVI)‐based aboveground biomass model with r² = 0.61 and r² = 0.72 for total and perennial biomass, respectively. No difference between observed and predicted total and perennial biomass was found (p = 0.700 and p = 0.306, respectively). The comparison between the two treatments using the field sampling revealed a significant difference on total plant cover (p = 0.016) and total biomass (p = 0.005), with a plant cover of 50.6% and a biomass of 325.771 kg dry matter per hectare (kg DM ha^?1) on average in grazed area and 66.9%, 1,407.869 kg DM ha^?1 in exclosure. Finally, a concordance is noted between the results obtained by the NDVI‐based biomass model and the field sampling‐based biomass.     

NDVI is not reliable as a surrogate of forage abundance for a large herbivore in tropical forest habitat

Remotely sensed vegetation indices are increasingly being used in wildlife studies but field‐based support for their utility as a measure of forage availability comes largely from open‐canopy habitats. We assessed whether normalized difference vegetation index (NDVI) represents forage availability for Asian elephants in a southern Indian tropical forest. We found that the number of food species was a small percentage of all plant species. NDVI was not a good measure of food abundance in any vegetation category partly because of (a) small to moderate proportional abundances of food species relative to the total abundance of all species in that category (herbs and shrubs), (b) abundant overstory vegetation resulting in low correlations between NDVI and food abundance, despite a high proportional abundance of food species and a concordance between total abundance and food species abundance (graminoids), and (c) the relevant variables measured and important as food at the ground level (count and GBH) not being related to primary productivity (trees and recruits). NDVI had a negative relationship with the total abundance of graminoids, which represent a bulk of elephant and other herbivore diet, because of negative interaction with other vegetation and canopy cover that positively explained NDVI. Spatially interpolated total graminoid abundance modeled from field data outperformed NDVI in predicting total graminoid abundance, although interpolation models of food graminoid abundance were not satisfactory. Our results reject the utility of NDVI in mapping elephant forage abundance in tropical forests, a finding that has implications for studies of other herbivores also. Abstract in Kannada is available with online material.