Monitoring tropical forests under a functional perspective with satellite‐based vegetation optical depth

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate‐induced events may initially alter the functions more than slow‐changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental drivers, linked to leaf traits and forest structure, and influenced by climate change effects. The ability of vegetation optical depth (VOD) to provide forest functional information is investigated using 2011–2014 satellite data collected by the Soil Moisture and Ocean Salinity mission and using the EFPs as reference dataset. Tropical forests in Africa and South America were analyzed, also according to ecological homogeneous units. VOD jointly with water deficit information explained 93% and 87% of the yearly variability in both flux upscaled maximum gross primary productivity and light use efficiency functional properties, in Africa and South America forests respectively. Maps of the retrieved properties evidenced changes in forest functional responses linked to anomalous climate‐induced events during the study period. The findings indicate that VOD can support the flux upscaling process in the tropical range, affected by high uncertainty, and the detection of forest anomalous functional responses. Preliminary temporal analysis of VOD and EFP signals showed fine‐grained variability in periodicity, in signal dephasing, and in the strength of the relationships. In selected drier forest types, these satellite data could also support the monitoring of functional dynamics.     

基于灰色三角白化权集对分析模型的喀斯特山区农业生态环境脆弱性评价

生态脆弱性一直是全球变化与可持续发展研究的热点问题,研究农业生态环境脆弱性问题有利于合理利用区域农业资源,提出有效的农业生态环境保护措施。针对农业生态环境脆弱性评价未考虑不同评价级别内各指标之间同、异、反关系,本研究基于灰色三角白化权集对分析(SPA)模型,从生态环境外在脆弱性方面选择人口密度、人均耕地面积、人均造林面积等11个评价指标,对喀斯特山区农业生态环境脆弱性进行评价。结果表明: 研究区农业生态环境比较脆弱,以极度、高度和中度脆弱度为主;极度、高度、中度、轻度和微度农业生态环境脆弱区比例分别为32.4%、14.1%、17.7%、23.6%和12.2%;评价结果与研究区域农业生态环境脆弱性实际状况相符。说明以灰色三角白化权SPA模型评价农业生态环境脆弱性具有可行性,可为农业生态环境脆弱性评价提供一种新的方法和思路。     

广西乐业大石围天坑群种子植物区系研究

广西乐业大石围天坑群(以下简称大石围天坑群)是最典型的塌陷型天坑群。该研究采用样线法和样方法对大石围天坑群的种子植物进行了实地调查,并结合已有资料综合分析了大石围天坑群种子植物区系特征。结果表明:大石围天坑群野生种子植物丰富,有137科445属863种;在科级和属级水平上,地理成分以热带成分为主,中国特有成分相对贫乏;与热带区系的联系主要以泛热带成分为主,与温带区系的联系主要以北温带成分为主;大石围天坑群的热带科和温带科之比以及热带属和温带属之比,均小于中国乐业-凤山世界地质公园,其种子植物区系更能反映该地区过去植物组成的"原貌",即温带成分比例过去的比现代的高,是全球气候变暖的有力证据:天坑群保育了82种珍稀濒危植物,包括30属67种野生兰科植物,是现存珍稀濒危植物的"避难所"。     

Optimizing canopy‐forming algae conservation and restoration with a new herbivorous fish deterrent device

The role of herbivorous fish in threatening marine forests of temperate seas has been generally overlooked. Only recently, the scientific community has highlighted that high fish herbivory can lead to regime shifts from canopy‐forming algae to less complex turf communities. Here, we present an innovative herbivorous fish deterrent device (DeFish), which can be used for conservation and restoration of marine forests. Compared to most traditional fish exclusion systems, such as cages, the DeFish system does not need regular cleaning and maintenance, making it more cost‐efficient. Resistance of DeFish was tested by installing prototypes at different depths in the French Riviera and in Montenegro: more than 60% of the devices endured several years without maintenance, even if most of them were slightly damaged in the exposed site in Montenegro. The efficacy of DeFish in limiting fish herbivory was tested by an exclusion experiment on Cystoseira amentacea in the French Riviera. In a few months, the number of fish bite marks on the seaweed was decreased, causing a consequent increase in algal length. The device here presented has been conceived for Mediterranean canopy‐forming algae, but the same concept can be applied to other species vulnerable to fish herbivory, such as kelps or seagrasses. In particular, the DeFish design could be improved using more robust and biodegradable materials. Innovative engineering systems, such as DeFish, are expected to become useful tools in the conservation and restoration of marine forests, to complement other practices including active reforestation, herbivore regulation, and regular monitoring of their status.     

Alternative pathways of liana communities in the forests of northwestern Argentina

Liana dynamics in secondary and mature forests are well known in tropical areas dominated by native tree species. Outside the tropics and in secondary forests invaded by exotic species, knowledge is scarce. In this study, we compare liana communities between secondary and mature forests dominated by native species in a subtropical montane area of Sierra de San Javier, Tucuman, Argentina. Additionally, we evaluate changes of liana communities in secondary forests with increasing densities of Ligustrum lucidum and Morus alba, two of the most invasive exotic trees of the area. We surveyed liana species richness and density in three 30-year secondary patches, four 60-year secondary patches, and four mature patches dominated by native tree species, to analyze changes in liana communities with forest age. Within each patch, we sampled 10–25 20 × 20 m quadrats. Additionally, we surveyed liana density and species richness in secondary forest patches with different densities of L. lucidum and M. alba. In native-dominated forests, liana species richness increased and showed a tendency of increasing basal area from 30-year secondary forests to mature forests. Liana density was highly variable, and most of the species were shared between native-dominated secondary and mature forests. Liana density and species richness decreased with L. lucidum density, whereas in secondary forests highly dominated by M. alba, lianas increased in density. Overall, lianas followed different pathways influenced by native forest succession and exotic tree invasions.     

云南岩溶断陷盆地土地利用方式对丛枝菌根真菌群落结构的影响

【背景】丛枝菌根真菌(arbuscular mycorrhizal fungus,AMF)是一类能与绝大部分植物形成共生关系的真菌,在植被演替和生态恢复过程中发挥重要作用。【目的】了解云南岩溶断陷盆地不同土地利用方式对AMF群落结构的影响。【方法】采用Illumina HiSeq 2500高通量测序技术对云南岩溶断陷盆地林地、灌丛和草地等3种土地利用方式土壤样品的AMF群落结构进行分析。【结果】草地总磷(total phosphorus,TP)、速效钾(available potassium,AK)、交换性镁(exchangeable magnesium,E-Mg)、电导率(electrical conductivity,EC)和土壤温度(temperature,T)显著高于林地和灌丛,林地总氮(total nitrogen,TN)和有机碳(soil organic carbon,SOC)含量显著高于灌丛和草地。TN、SOC、AK和EC是AMF群落结构最主要的影响因子。草地样品的Chao1、ACE、Shannon和Observed species指数显著高于林地和灌丛样品,尽管Simpson指数差异不显著,但是也表现出了类似的变化趋势。9个土壤样品共产生953个AMF-OTU,鉴定出AMF 3个纲4个目9个科13个属。Glomeromycetes和Paraglomeromycetes为优势纲;Glomus和Paraglomus为优势属,其次为Claroideoglomus、Acaulospora和Diversispora。Glomus和Diversispora主要分布在草地和灌丛中,随着演替的进行其相对丰度有所下降,而Paraglomus的相对丰度逐渐上升。【结论】云南岩溶断陷盆地土地利用方式的AMF群落结构具有显著差异,土壤理化因子是重要的影响因素。     

Comparison of complex modeling strategies for prediction of a binary outcome based on a few,highly correlated predictors

Motivated by a clinical prediction problem, a simulation study was performed to compare different approaches for building risk prediction models. Robust prediction models for hospital survival in patients with acute heart failure were to be derived from three highly correlated blood parameters measured up to four times, with predictive ability having explicit priority over interpretability. Methods that relied only on the original predictors were compared with methods using an expanded predictor space including transformations and interactions. Predictors were simulated as transformations and combinations of multivariate normal variables which were fitted to the partly skewed and bimodally distributed original data in such a way that the simulated data mimicked the original covariate structure. Different penalized versions of logistic regression as well as random forests and generalized additive models were investigated using classical logistic regression as a benchmark. Their performance was assessed based on measures of predictive accuracy, model discrimination, and model calibration. Three different scenarios using different subsets of the original data with different numbers of observations and events per variable were investigated. In the investigated setting, where a risk prediction model should be based on a small set of highly correlated and interconnected predictors, Elastic Net and also Ridge logistic regression showed good performance compared to their competitors, while other methods did not lead to substantial improvements or even performed worse than standard logistic regression. Our work demonstrates how simulation studies that mimic relevant features of a specific data set can support the choice of a good modeling strategy.     

Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama

In tropical regions, rainfall gradients often explain the abundance and distribution of plant species. For example, many tree and liana species adapted to seasonal drought are more abundant and diverse in seasonally-dry forests, characterized by long periods of seasonal water deficit. Mean annual precipitation (MAP) is commonly used to explain plant distributions across climate gradients. However, the relationship between MAP and plant distribution is often weak, raising the question of whether other seasonal precipitation patterns better explain plant distributions in seasonally-dry forests. In this study, we examine the relationship between liana abundance and multiple metrics of seasonal and annual rainfall distribution to test the hypothesis that liana density and diversity increase with increasing seasonal drought along a rainfall gradient across the isthmus of Panama. We found that a normalized seasonality index, which combines MAP and the variability of monthly rainfall throughout the year, was a significant predictor of both liana density and species richness, whereas MAP, rainfall seasonality and the mean dry season precipitation (MDP) were far weaker predictors. The strong response of lianas to the normalized seasonality index indicates that, in addition to the total annual amount of rainfall, how rainfall is distributed throughout the year is an important determinant of the hydrological conditions that favor liana proliferation. Our findings imply that changes in annual rainfall and rainfall seasonality will determine the future distribution and abundance of lianas. Models that aim to predict future plant diversity, distribution, and abundance may need to move beyond MAP to a more detailed understanding of rainfall variability at sub-annual timescales.     

Linking variability of tree water use and growth with species resilience to environmental changes

Tree growth is an indicator of tree vitality and its temporal variability is linked to species resilience to environmental changes. Second-order statistics that quantify the cross-scale temporal variability of ecophysiological time series (statistical memory) could provide novel insights into species resilience. Species with high statistical memory in their tree growth may be more affected by disturbances, resulting in lower overall resilience and higher vulnerability to environmental changes. Here, we assessed the statistical memory, as quantified with the decay in standard deviation with increasing time scale, in tree water use and growth of co-occurring European larch Larix decidua and Norway spruce Picea abies along an elevational gradient in the Swiss Alps using measurements of stem radius changes, sap flow and tree-ring widths. Local-scale interspecific differences between the two conifers were further explored at the European scale using data from the International Tree-Ring Data Bank. Across the analysed elevational gradient, tree water use showed steeper variability decay with increasing time scale than tree growth, with no significant interspecific differences, highlighting stronger statistical memory in tree growth processes. Moreover, Norway spruce displayed slower decay in growth variability with increasing time scale (higher statistical memory) than European larch; a pattern that was also consistent at the European scale. The higher statistical memory in tree growth of Norway spruce in comparison to European larch is indicative of lower resilience of the former in comparison to the latter, and could potentially explain the occurrence of European larch at higher elevations at the Alpine treeline. Single metrics of resilience cannot often summarize the multifaceted aspects of ecosystem functioning, thus, second-order statistics that quantify the strength of statistical memory in ecophysiological time series could complement existing resilience indicators, facilitating the assessment of how environmental changes impact forest growth trajectories and ecosystem services.