Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.     

气候变化背景下江西省林火空间预测

林火是森林生态系统中重要的干扰因子之一,深刻地影响森林景观结构和功能。在全球气候化背景下,揭示气候变化对林火空间分布格局的影响,可为林火管理和防火资源分配提供科学指导。因此,基于江西省2001—2015年MODIS火影像数据(MCD14ML)和年均气温、年均降水量、植被、地形、人口密度、距道路距离、距居民点距离7个因子数据,利用增强回归树模型:(1)分析林火发生影响因子的相对重要性及其边际效应;(2)将GFDL-CM3和GISS-E2-R气候变化模式中的年均气温和年均降水量作为未来的气象数据,在3个温室气体排放量情景(RCP2.6、RCP4.5、RCP8.5)下,对2050年(2041—2060的平均值)和2070年(2061—2080的平均值)江西省林火分布进行预测,生成林火发生概率图。并采用受试者工作特征(ROC曲线)和混淆矩阵评估模型预测的精度。研究结果表明:(1)年均气温和海拔与江西省林火发生的相关性较强,年均降水量、居民点距离、人口密度、道路距离与林火发生的相关性较弱,但是与林火发生密切相关的如降水、风速等也应重点关注;(2)训练数据(70%)和验证数据(30%)的AUC值(ROC曲线下面积值)均为0.736,混淆矩阵对火点预测的正确率为67.8%,表明模型能够较好地预测研究区林火的发生;(3)在RCP8.5排放情景中林火发生的增幅最明显,其增幅较大的区域由赣南向赣北移动;(4)未来2050年和2070年林火发生与当前气候(2001—2015年)下相比,赣州市、鹰潭市的增幅较为明显,其他区域不明显。江西省各林业管理部门要加强林火高发区及潜在发生区的森林监测和管理,加大防火宣传力度,提升民众的森林防火意识。     

Tree Mortality Following Boreal Forest Fires Reveals Scale-Dependant Interactions Between Community Structure and Fire Intensity

Fire disturbance patterns influence forest communities at a range of spatial scales. Forest community structure may also influence fire disturbance patterns, because tree species vary in their fuel value and in their tolerance to fire damage. However, the influence of community structure on fire disturbance likely depends on latent ecological differences between fires and on the spatial scale at which patterns are observed. Using data on fire intensity, community structure, and post-fire tree survival in four systematically sampled boreal forest fires, we tested the hypotheses that: (1) patterns in post-fire tree survival reflect interactions between fire intensity and community structure; (2) these relationships change with the spatial scale of observation. To test the first hypothesis, we used information theoretic methods to compare eight generalized linear mixed effects models describing the influence of community structure and fire intensity on tree survival in a 500 m² sample plot, accounting for latent fire-to-fire differences in response. To test the scaling hypothesis, we reaveraged the data at nine successively larger spatial resolutions up to approximately 2 km², at each resolution tracking the parameter values of the best model. When fit to the plot-level data, the dominant feature of the best model was a strong intensity–survival correlation which varied from fire to fire, and depended on plot-level community structure. In some fires, community structure and survival became more tightly coupled at larger scales, whereas fire intensity became less important. These results support the view that fire disturbance patterns are influenced by cross-scale interactions between community structure and fire intensity.     

PLS-PM analysis of forest fires using remote sensing tools. The case of Xurés in the Transboundary Biosphere Reserve

Forest fires have environmental, social and economic impacts in many areas. Various factors related to territory directly influence both the number and the surface area of each fire. The link between different variables (climate, social and environmental) in the risk of fire and in the characteristics of fires is studied here through Partial Least Squares - Path Models. In addition, images from the Sentinel-2 sensor and geographic information systems are used to create a cartographic base of fires in the Transboundary Biosphere Reserve of Galicia and the Site of Community Importance of Xurés (Galicia) between 2015 and 2020. In all, seven variables are analyzed in this study area using the partial least squares-path modeling method: climate, topography, land use, type of environmental protection, the anthropogenic factor, fire defense, and fire data (severity and area). The parameters for each variable are used to obtain weights and thus determine the importance of each one. The areas where the problem of forest fires is greatest are those with the greatest environmental protection. Up to 31% of the surface area of the Natura 2000 Network was burned in the 6-year study period. Topography and land use are also shown to be relevant factors in the effects of forest fires in this territory. By contrast, higher population density and the development of infrastructures such as roads and water tanks mitigate the impact of fires. The problem of forest fires encompasses many variables that need to be studied. By contextualizing each study area as far as possible, specific measures to prevent and reduce damage can be drawn up.     

KGraph: a system for visualizing and evaluating complex genetic associations

The KGraph is a data visualization system that has been developed to display the complex relationships between the univariate and bivariate associations among an outcome of interest, a set of covariates, and a set of genetic factors, such as single nucleotide polymorphisms (SNPs). It allows for easy viewing and interpretation of genetic associations, correlations among covariates and SNPs, and information about the replication and cross-validation of the associations. The KGraph allows the user to more easily investigate multicollinearity and confounding through visualization of the multidimensional correlation structure underlying genetic associations. It emphasizes gene-environment and gene-gene interaction, both important components of any genetic system that are often overlooked in association frameworks. AVAILABILITY: http://www.epidkardia.sph.umich.edu/software/kgrapher     

A survey of some tensor analysis techniques for biological systems

Background: Since biological systems are complex and often involve multiple types of genomic relationships, tensor analysis methods can be utilized to elucidate these hidden complex relationships. There is a pressing need for this, as the interpretation of the results of high-throughput experiments has advanced at a much slower pace than the accumulation of data.Results: In this review we provide an overview of some tensor analysis methods for biological systems.Conclusions: Tensors are natural and powerful generalizations of vectors and matrices to higher dimensions and play a fundamental role in physics, mathematics and many other areas. Tensor analysis methods can be used to provide the foundations of systematic approaches to distinguish significant higher order correlations among the elements of a complex systems via finding ensembles of a small number of reduced systems that provide a concise and representative summary of these correlations.     

Changes in forest biomass and linkage to climate and forest disturbances over Northeastern China

The forests of northeastern China store nearly half of the country's total biomass carbon stocks. In this study, we investigated the changes in forest biomass by using satellite observations and found that a significant increase in forest biomass took place between 2001 and 2010. To determine the possible reasons for this change, several statistical methods were used to analyze the correlations between forest biomass dynamics and forest disturbances (i.e. fires, insect damage, logging, and afforestation and reforestation), climatic factors, and forest development. Results showed that forest development was the most important contributor to the increasing trend of forest biomass from 2001 to 2010, and climate controls were the secondary important factor. Among the four types of forest disturbance considered in this study, forest recovery from fires, and afforestation and reforestation during the past few decades played an important role in short‐term biomass dynamics. This study provided observational evidence and valuable information for the relationships between forest biomass and climate as well as forest disturbances.     

1953-2011年小兴安岭森林火灾含碳气体排放的估算

根据1953-2011年小兴安岭森林调查数据和森林火灾统计资料,结合野外火烧迹地调查与室内控制试验数据,估算了小兴安岭1953-2011年森林火灾的碳排放量和含碳气体排放量.结果表明: 1953-2011年小兴安岭森林火灾的总碳排放量为1.12×10⁷ t,年均排放量为1.90×10⁵ t,约占全国年均森林火灾碳排放量的1.7%;其中,含碳气体CO₂、CO、CH₄和非甲烷烃(NMHC)的排放量分别为3.39×10⁷、1.94×10₅、1.09×10⁵和7.46×10⁴ t,相应年均排放量5.74×10⁵、3.29×10⁴、1.85×10³、1.27×10³ t分别占全国年均森林火灾含碳气体排放量的1.4%、1.2%、1.7%和1.1%.不同林型的燃烧效率和单位过火面积的碳排放量均为针叶林＞阔叶林＞针阔混交林.最后提出了合理的林火管理措施.     

Exploring wood anatomy,density and chemistry profiles to understand the tree-ring formation in Amazonian tree species

Long-term analysis of tree growth using annual tree rings is increasingly in demand for tropical tree species. The basis of these studies has traditionally been the anatomical identification of the annual ring boundary. However, the structure of these annual rings has been sparsely explored for complementary physical and chemical wood traits. Here, we explore the relationships among wood density features and chemical elements (S, K, Ca, Mn) involved in the annual tree ring formation of 12 tropical tree species from non-flooded forest in the southern Amazon basin. Transverse wood sections were used for each species to determine: 1) macroscopic distinction (radial growth and wood density), 2) microscopic analyse of vessels, axial and ray parenchyma (anatomy) and 3) X-ray densitometry (physical) and X-ray fluorescence (chemical). For some species, the profiles of wood density, and Ca and Mn content showed intra- and inter-annual patterns that allowed to define and characterize the growth boundary of tree rings. Ca, K and S were mainly distributed in axial parenchyma cells, and around vessels, whereas, Mn was mainly distributed in fibres. Our results showed significant species-specific correlations between tree-ring width, density and concentrations of Ca, K and Mn. The anatomical characterization and the complementary information provided by the density and chemical profiles in some Amazonian species can represent a valuable proxy to improve the definition of annual ring-boundaries and improve the understanding of long-term growth and physiological patterns.     

Independence among physiological traits suggests flexibility in the face of ecological demands on phenotypes

Phenotypic flexibility allows animals to adjust their physiology to diverse environmental conditions encountered over the year. Examining how these varying traits covary gives insights into potential constraints or freedoms that may shape evolutionary trajectories. In this study, we examined relationships among haematocrit, baseline corticosterone concentration, constitutive immune function and basal metabolic rate in red knot Calidris canutus islandica individuals subjected to experimentally manipulated temperature treatments over an entire annual cycle. If covariation among traits is constrained, we predict consistent covariation within and among individuals. We further predict consistent correlations between physiological and metabolic traits if constraints underlie species-level patterns found along the slow-fast pace-of-life continuum. We found no consistent correlations among haematocrit, baseline corticosterone concentration, immune function and basal metabolic rate either within or among individuals. This provides no evidence for constraints limiting relationships among these measures of the cardiovascular, endocrine, immune and metabolic systems in individual red knots. Rather, our data suggest that knots are free to adjust individual parts of their physiology independently. This makes good sense if one places the animal within its ecological context where different aspects of the environment might put different pressures on different aspects of physiology.     

Recent fire regime characteristics and potential natural vegetation relationships in Spain

Abstract. In heavily altered landscapes, where vegetation is not natural and where people are the main source of ignitions, relationships between fire occurrence and climate conditions may be unclear. The objective of this study was to evaluate to what extent territories with similar Potential Natural Vegetation (PNV) in peninsular Spain differ in their forest fire characteristics. From 1974 to 1994, more than 174 000 fires occurred. We used (1) the Spanish data base of forest fires, (2) a PNV map and (3) a land use map. Separate fire characteristics, based either on the number of fires occurred or the area burned, were obtained for each of the ca. 5000 grid‐cells (10 km × 10 km) into which peninsular Spain is divided in the UTM projection. Also, meteorological conditions at the time of fire ignition, cause of ignition and present forest cover were referred to the same grid‐cells as external factors potentially determinant of fire occurrence. The relationships between fire regime characteristics and PNV units were explored with Principal Components Analysis (PCA). The role of the three sets of external factors in the fire characteristics was evaluated with Redundancy Analysis (RDA). Groups of similar PNV types were clearly segregated, suggesting a gradient of fire characteristics. Higher fire incidence (higher frequencies and spatial incidence of fires, but lower proportions of grid‐cells affected by large fires) was associated with Atlantic, warm territories with deciduous forests as PNV. Intermediate fire frequency and rotation period, but with a higher relative incidence of medium and large fires occurred in Mediterranean PNV units, dominated by sclerophyllous oak forests. Low fire frequency and long rotation periods, with strong seasonal and yearly variability occurred for PNV units in the cold uplands (Fagus, Pinus, Abies, Juniperus) or in the semi‐arid, shrubby PNV units. The cause of ignition best explained the patterns of forest fire characteristics, followed by weather conditions. Our results indicate that, even in human influenced regions, climate and soil conditions exert control on the resulting forest fire characteristics, as indicated by the high segregation of the PNV types. However, the role of man was crucial in shifting the patterns of fire incidence. This was so that highest fire incidence occurred in regions that, otherwise, would be expected to have a much lower one, thus posing a serious threat for such areas. PNV maps, by providing a phytogeographical framework for characterizing forest fires, could be valuable tools for applying research results to forest fire management policies, taking properly into account the underlying determinant factors.     

不同龄组的热带森林植被生物量与遥感地学数据之间的相关性分析

 在森林植被生物量遥感动态监测方面最基础性的研究是探讨生物量与遥感数据及其派生数据、地形数据和气象数据之间的相关性。为此,以我国云南省西双版纳的热带森林植被为例,分别对幼龄林、中龄林、近熟林和成过熟林的生物量与其对应的LANDSAT TM数据及其派生数据、气象数据和地形数据之间的相关性进行了分析。首先,利用森林资源连续清查的林业固定样地数据,通过各树种组的各器官生物量估算模型计算出各样地森林植被的生物量,并根据样地的坐标来建立样地GIS数据库。然后,利用地形图对遥感图像进行几何校正,并对遥感图像进行主成分变换、缨帽变换以及植被指数的计算来产生其派生数据。其次,将栅格样地数据、遥感数据（如LANDSAT TM数据）及其派生数据（如各种植被指数数据、主成分数据、缨帽变换的亮度、绿度和湿度数据）、栅格地形数据（如DEM和坡向）和栅格气象数据（包括年平均温度、大于0 ℃的积温、年平均降雨量和湿润度）统一到同一坐标系和投影下,并将所有的数据内插为30 m分辨率的格网数据,利用样地数据与遥感数据及其派生数据、地形数据和气象数据进行栅格空间叠加分析,从而得到各样地的样地数据、遥感数据及其派生数据、地形数据和气象数据。再次,根据各样地优势树种所属的龄组将所有的数据层化为幼龄林、中龄林、近熟林和成过熟林等几个不同龄组的样本数据。最后,分别对幼龄林、中龄林、近熟林和成过熟林的样地生物量与其对应的遥感数据和派生数据、气象数据和地形数据进行相关性分析。研究表明,在所有的因子中,幼龄林的生物量与LANDSAT 的TM1和TM6波段的亮度值在0.05的水平上呈显著相关,其相关系数均为-0.33;中龄林的生物量与降雨量在0.05的水平上呈显著相关,其相关系数为0.33;近熟林的生物量与LANDSAT TM的派生数据VI3、LANDSAT的TM4和缨帽变换的亮度值在0.05的水平上呈显著相关,其相关系数分别为0.50、-0.45和-0.45;成过熟林的生物量与主成分变换的第二主成分（PC2）在0.05的水平上呈显著相关,其相关系数为-0.46。在0.05的水平上,近熟林的生物量与LANDSAT TM的派生数据VI3的相关系数最高,达到0.50,其次是成过熟林的生物量与主成分变换的第二主成分的相关系数,为-0.46。     

Pantropical trends in mangrove above-ground biomass and annual litterfall

A major paradigm in biosphere ecology is that organic production, carbon turnover and, perhaps, species diversity are highest at tropical latitudes, and decrease toward higher latitudes. To examine these trends in the pantropical mangrove forest vegetation type, we collated and analysed data on above-ground biomass and annual litterfall for these communities. Regressions of biomass and litterfall data show significant relationships with height of the vegetation and latitude. It is suggested that height and latitude are causally related to biomass, while the relationship with litterfall reflects the specific growing conditions at the respective study sites. Comparison of mangrove and upland forest litterfall data shows similar trends with latitude but indicates that mangrove litterfall is higher than upland forest litterfall. The regression equations allow the litterfall/biomass ratio to be simulated, and this suggests that the patterns of organic matter partitioning differ according to latitude.     

浙江省1991—2006森林火灾直接碳释放量的估算

森林火灾是自然生态系统重要的干扰因子,在燃烧过程中释放大量的温室气体.随着全球温度持续升高,林火有更频发的趋势.根据1991—2006年浙江省森林火灾统计资料和浙江省各种森林类型地上生物量数据,采用排放因子法和排放比法,分析浙江省年均森林火灾温室气体排放量.结果表明:浙江省森林火灾平均每年释放CO₂、CO、甲烷(CH₄)和非甲烷烃(NMHC)分别为127930、7672.8、3098.7和1475.5 t;年均消耗生物量和碳损失量分别为86148.1和38766.7 t,对区域碳平衡有一定影响.     

Exploring interactions by second-stage community analyses

Many biological data sets, from field observations and manipulative experiments, involve crossed factor designs, analysed in a univariate context by higher-way analyses of variance which partition out ‘main’ and ‘interaction’ effects. Indeed, tests for significance of interactions among factors, such as differing Before-After responses at Control and Impact sites, are the basis of the widely used BACI strategy for detecting impacts in the environment. There are difficulties, however, in generalising simple univariate definitions of interaction, from classic linear models, to the robust, non-parametric multivariate methods that are commonly required in handling assemblage data. The size of an interaction term, and even its existence at all, depends crucially on the measurement scale, so it is fundamentally a parametric construct. Despite this, certain forms of interaction can be examined using non-parametric methods, namely those evidenced by changing assemblage patterns over many time periods, for replicate sites from different experimental conditions (types of ‘Beyond BACI’ design) - or changing multivariate structure over space, at many observed times. Second-stage MDS, which can be thought of as an MDS plot of the pairwise similarities between MDS plots (e.g. of assemblage time trajectories), can be used to illustrate such interactions, and they can be formally tested by second-stage ANOSIM permutation tests. Similarities between (first-stage) multivariate patterns are assessed by rank-based matrix correlations, preserving the fully non-parametric approach common in marine community studies. The method is exemplified using time-series data on corals from Thailand, macrobenthos from Tees Bay, UK, and macroalgae from a complex recolonisation experiment carried out in the Ligurian Sea, Italy. The latter data set is also used to demonstrate how the analysis copes straightforwardly with certain repeated-measures designs.     

An interdisciplinary evaluation of the status and health of African lake fisheries using a rapid appraisal technique

Data from biological, economic, sociological, and technological attribute lists for 32 African lake fisheries were analysed with multivariate statistics. Multidimensional scaling (MDS) was used to create two-dimensional graphic ordinations of the fisheries for each of these four attributes lists. An overall MDS ordination was also generated, based on the fisheries' scores in the four ordinations. Groupings in each MDS ordination were achieved through cluster analysis. Multiple correlations was used to help determine the attributes which were most important in creating the MDS ordinations. This work showed that relatively fast and simple assessments of the status of African lake and other fisheries can be achieved. The technique also provided insight to help resolve the confounding information often associated with fisheries assessment. Diagnostic information may also be a product of such investigations as this research identified African lake fisheries at risk of declining standards. Indeed, many of the fisheries studied demonstrated similar interdisciplinary symptoms of fisheries decline as other small-scale tropical fisheries.     

黑龙江省温带森林火灾碳排放的计量估算

森林火灾干扰作为森林生态系统重要的干扰因子,剧烈地改变着森林生态系统的结构、功能、格局与过程,对区域乃至全球的碳循环与碳平衡产生重要影响。随着全球气候变暖,森林火灾干扰的频率和强度进一步加剧,其排放的含碳气体对大气中温室气体浓度的贡献率更大,进而加快气候变暖的速率。科学有效地对森林火灾碳排放及含碳气体排放量进行计量估算,对了解区域乃至全球的碳循环及碳平衡具有重要的理论价值和实践意义。根据黑龙江省温带森林1953—2012年火灾统计资料和森林调查数据,结合地理信息系统GIS技术,通过野外火烧迹地调查以及实验室的控制环境实验来确定森林火灾碳排放计量中的各种参数,在林分水平上,利用排放因子的方法,估算了黑龙江省温带森林60年间火灾碳排放量和含碳气体排放量。结果表明:黑龙江省温带森林60年间火灾碳排放量为5.88×107t,年均排放量为9.80×105t,约占全国年均森林火灾碳排放量的8.66%;含碳气体CO2、CO、CH4和非甲烷烃(nonmethane hydrocarbons,NMHC)的排放量分别为1.89×108、1.06×107、6.33×105和4.43×105t,含碳气体CO2、CO、CH4和NMHC的年均排放量分别为3.15×106、1.77×105、1.05×104和7.38×103t,分别占全国年均森林火灾各含碳气体排放量的7.74%、6.52%、9.42%和6.53%。研究发现针阔混交林型的森林火灾面积占总过火林地面积的57.54%,由于其燃烧效率较低,在森林火灾中的碳排放量仅占排放总量的38.57%;尤其是针阔混交林森林火灾面积占总过火林地面积的20.71%,而碳排放量仅占总排放量的9.67%;且CO2的排放因子较低,其CO2排放量仅占总排放量的8.95%。同时研究表明,黑龙江省温带森林年均的碳排放对该区域的碳循环与碳平衡产生重要影响,并针对研究结果提出了应对气候变化的森林经营可持续管理策略,亦提出了科学的林火管理策略及其合理化的林火管理路径。     

Co-variation and indicators of species diversity: Can richness of forest-dwelling species be predicted in northern boreal forests?

Design and establishment of ecologically good networks of conservation areas often requires quick assessments of their biodiversity. Reliable indicators would be useful when doing such assessments. In order to explore the potential indicators for species richness in boreal forests, we studied (1) the co-variation of species richness and composition of species assemblages among beetles, polypores, birds and vascular plants, (2) the relationships between species richness and four boreal forest site types, (3) the relationship between species richness and forest physical structure and (4) the suitability of potential indicator groups within the four taxa to predict the species richness generally. The data show that there are probably not a single taxonomic or forest structural characteristic to be used as a general biodiversity indicator or surrogate for all the species. The correlations in species richness among the four taxa studied were low. However, group-specific indicators were obvious: forest site type was a good surrogate for vascular plant richness, and quantity and quality of dead wood predicted the species richness of polypores. The results support the view that different indicators shall be used for different forest types and taxonomic groups. These indicators should facilitate relatively rapid methods to assess biodiversity patterns at the forest stand level.