Greater deciduous shrub abundance extends tundra peak season and increases modeled net CO2 uptake

Satellite studies of the terrestrial Arctic report increased summer greening and longer overall growing and peak seasons since the 1980s, which increases productivity and the period of carbon uptake. These trends are attributed to increasing air temperatures and reduced snow cover duration in spring and fall. Concurrently, deciduous shrubs are becoming increasingly abundant in tundra landscapes, which may also impact canopy phenology and productivity. Our aim was to determine the influence of greater deciduous shrub abundance on tundra canopy phenology and subsequent impacts on net ecosystem carbon exchange (NEE) during the growing and peak seasons in the arctic foothills region of Alaska. We compared deciduous shrub‐dominated and evergreen/graminoid‐dominated community‐level canopy phenology throughout the growing season using the normalized difference vegetation index (NDVI). We used a tundra plant‐community‐specific leaf area index (LAI) model to estimate LAI throughout the green season and a tundra‐specific NEE model to estimate the impact of greater deciduous shrub abundance and associated shifts in both leaf area and canopy phenology on tundra carbon flux. We found that deciduous shrub canopies reached the onset of peak greenness 13 days earlier and the onset of senescence 3 days earlier compared to evergreen/graminoid canopies, resulting in a 10‐day extension of the peak season. The combined effect of the longer peak season and greater leaf area of deciduous shrub canopies almost tripled the modeled net carbon uptake of deciduous shrub communities compared to evergreen/graminoid communities, while the longer peak season alone resulted in 84% greater carbon uptake in deciduous shrub communities. These results suggest that greater deciduous shrub abundance increases carbon uptake not only due to greater leaf area, but also due to an extension of the period of peak greenness, which extends the period of maximum carbon uptake.     

Evidence for facultative deciduousness in Colophospermum mopane in semi‐arid African savannas

Leaf phenology dictates the time available for carbon assimilation, transpiration and nutrient uptake in plants. Understanding the environmental cues that control phenology is therefore vital for predicting climate‐related changes to plant and ecosystem function. In contrast to temperate systems, and to a lesser degree, tropical forest systems, the cues initiating leaf drop in tropical savannas are poorly studied. We investigated the cues for leaf fall in a tropical monodominant arid savanna species, Colophospermum mopane, using an irrigation experiment. We tracked soil moisture, solar radiation, air temperature, leaf water status, leaf health and leaf carbon balance through the dry season in both irrigated and control plants. Water was the primary cue driving leaf loss of C. mopane rather than temperature or light. Trees watered throughout the dry season retained their canopies. These leaves remained functional and continued photosynthesis throughout the dry season. Leaf carbon acquisition rates did not decline with leaf age but were affected by soil moisture availability and temperature. Leaf loss did not occur when leaf carbon gain was zero, or when a particular leaf carbon threshold was reached. Colophospermum mopane is facultatively deciduous as water availability determines leaf drop in this widespread arid savanna species. Obligate deciduosity is not the only successful strategy in climates with a long dry season.     

Substantial variation in leaf senescence times among 1360 temperate woody plant species: implications for phenology and ecosystem processes

Background and Aims Autumn leaf senescence marks the end of the growing season in temperate ecosystems. Its timing influences a number of ecosystem processes, including carbon, water and nutrient cycling. Climate change is altering leaf senescence phenology and, as those changes continue, it will affect individual woody plants, species and ecosystems. In contrast to spring leaf out times, however, leaf senescence times remain relatively understudied. Variation in the phenology of leaf senescence among species and locations is still poorly understood.Methods Leaf senescence phenology of 1360 deciduous plant species at six temperate botanical gardens in Asia, North America and Europe was recorded in 2012 and 2013. This large data set was used to explore ecological and phylogenetic factors associated with variation in leaf senescence.Key Results Leaf senescence dates among species varied by 3 months on average across the six locations. Plant species tended to undergo leaf senescence in the same order in the autumns of both years at each location, but the order of senescence was only weakly correlated across sites. Leaf senescence times were not related to spring leaf out times, were not evolutionarily conserved and were only minimally influenced by growth habit, wood anatomy and percentage colour change or leaf drop. These weak patterns of leaf senescence timing contrast with much stronger leaf out patterns from a previous study.Conclusions The results suggest that, in contrast to the broader temperature effects that determine leaf out times, leaf senescence times are probably determined by a larger or different suite of local environmental effects, including temperature, soil moisture, frost and wind. Determining the importance of these factors for a wide range of species represents the next challenge for understanding how climate change is affecting the end of the growing season and associated ecosystem processes.     

Cryptic phenology in plants: Case studies,implications, and recommendations

Plant phenology—the timing of cyclic or recurrent biological events in plants—offers insight into the ecology, evolution, and seasonality of plant‐mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season‐initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are “cryptic”—that is, hidden from view (e.g., root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g., leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models.     

Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency

Leaf senescence in winter deciduous species signals the transition from the active to the dormant stage. The purpose of leaf senescence is the recovery of nutrients before the leaves fall. Photoperiod and temperature are the main cues controlling leaf senescence in winter deciduous species, with water stress imposing an additional influence. Photoperiod exerts a strict control on leaf senescence at latitudes where winters are severe and temperature gains importance in the regulation as winters become less severe. On average, climatic warming will delay and drought will advance leaf senescence, but at varying degrees depending on the species. Warming and drought thus have opposite effects on the phenology of leaf senescence, and the impact of climate change will therefore depend on the relative importance of each factor in specific regions. Warming is not expected to have a strong impact on nutrient proficiency although a slower speed of leaf senescence induced by warming could facilitate a more efficient nutrient resorption. Nutrient resorption is less efficient when the leaves senesce prematurely as a consequence of water stress. The overall effects of climate change on nutrient resorption will depend on the contrasting effects of warming and drought. Changes in nutrient resorption and proficiency will impact production in the following year, at least in early spring, because the construction of new foliage relies almost exclusively on nutrients resorbed from foliage during the preceding leaf fall. Changes in the phenology of leaf senescence will thus impact carbon uptake, but also ecosystem nutrient cycling, especially if the changes are consequence of water stress.     

Plant phenology and global climate change: Current progresses and challenges

Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground‐ and remote sensing‐ based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process‐based phenology modeling, and on the scaling of phenology from species to landscape‐level.     

Effects of precipitation and soil water potential on drought deciduous phenology in the Kalahari

We utilized an ecosystem process model to investigate the influence of precipitation and soil water potential on vegetation phenology in the semi‐arid, drought‐deciduous ecosystems in the Kalahari region of South Africa. The timing of leaf flush was assumed to be the first day during which a rainfall event exceeded that day's estimate of potential evapotranspiration after a defined dry season. Leaf senescence was assumed to be a dynamic feedback between soil water potential and net plant carbon gain and was determined by dynamically modeling the effects of concomitant trends in soil water potential and net primary production on leaf area index (LAI). Model predictions of LAI were compared with satellite‐derived normalized difference vegetation indices (NDVI) for 3 years at two sites along the Kalahari transect. The mean absolute error for the prediction of modeled leaf flush date compared with leaf flush dates estimated from NDVI were 10.0 days for the Maun site and 39.3 days for the Tshane site. Correlations between model predicted 10‐day average LAI and 10‐day composite NDVI for both Maun and Tshane were high (ρ=0.67 and 0.74, respectively, P<0.001), suggesting that this method adequately predicts intra‐annual leaf area dynamics in these dry tropical ecosystems.     

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf‐out times across groupings of species in a dynamic vegetation model

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf‐out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf‐out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970–2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf‐out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf‐out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.     

Extended leaf phenology: a secret of successful invaders?

Smith (2013), in this issue, reviews the consequences of extended leaf phenology of invasive plant species in native deciduous forests. How important is early leaf emergence and/or late leaf senescence for the success of non‐native species? What are the direct and indirect impacts on invaded communities and ecosystems? We are just at the very early stage in answering such questions.     

中国北方树木秋季物候的过程模拟及其区域分异归因

揭示温带落叶树木秋季物候的发生机理对提高生态系统固碳量和植被生产力的预估精度具有重要意义。该研究利用低温和光周期乘积模型模拟了1981-2014年中国北方温带90余个站点6个树种的叶始变色期和落叶末期, 并对逐站点-物种的最优模型进行了模拟精度评价, 分析了最优模型模拟精度的时空差异及其随水分梯度的空间变化。主要结果如下: (1)在诱导叶片衰老方面, 光周期缩短的影响通常大于温度降低的影响。据此建立的叶始变色期和落叶末期最优模型模拟的平均均方根误差分别为6.9 d和6.0 d, 模拟与观测时间序列呈显著正相关关系的比例分别为71.4%和83.6%; (2)最优模型对区域平均和多年平均叶始变色期和落叶末期模拟的绝对误差小于2.4 d, 但模拟日期的时空变幅通常小于观测日期, 这与秋季物候发生日期的高度时间变异性密切相关; (3)水分条件在一定程度上影响叶片衰老诱导途径的选择, 表现为光周期缩短诱导叶片衰老的叶始变色期最优模型所占比例在干旱和半干旱区大于湿润和半湿润区, 而最优模型的模拟精度在湿润和半湿润区高于干旱和半干旱区。该研究验证了低温和光周期乘积模型在中国温带地区的适用性, 并揭示了水分条件对秋季物候发生机理和模拟精度的影响。     

A global prognostic scheme of leaf onset using satellite data

Leaf phenology describes the seasonal cycle of leaf functioning. Although it is essential for understanding the interactions between the biosphere, the climate, and biogeochemical cycles, it has received little attention in the modelling community at global scale. This article focuses on the prediction of spatial patterns of the climatological onset date of leaf growth for the decade 1983–93. It examines the possibility of extrapolating existing local models of leaf onset date to the global scale. Climate is the main variable that controls leaf phenology for a given biome at this scale, and satellite observations provide a unique means to study the seasonal cycle of canopies. We combine leaf onset dates retrieved from NOAA/AVHRR satellite NDVI with climate data and the DISCover land‐cover map to identify appropriate models, and determine their new parameters at a 0.5° spatial resolution. We define two main regions: at temperate and high latitudes leaf onset models are mainly dependent on temperature; at low latitudes they are controlled by water availability. Some local leaf onset models are no longer relevant at the global scale making their calibration impossible. Nevertheless, we define our unified model by retaining the model that best reproduced the spatial distribution of leaf onset dates for each biome. The main spatial patterns of leaf onset date are well simulated, such as the Sahelian gradient due to aridity and the high latitude gradient due to frost. At temperate and high latitudes, simulated onset dates are in good agreement with climatological observations; 62% of treated grid‐cells have a simulated leaf onset date within 10 days of the satellite observed onset date (which is also the temporal resolution of the NDVI data). In tropical areas, the subgrid heterogeneity of the phenology is larger and our model's predictive power is diminished. The difficulties encountered in the tropics are due to the ambiguity of the satellite signal interpretation and the low reliability of rainfall and soil moisture fields.     

The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models

Autumn senescence regulates multiple aspects of ecosystem function, along with associated feedbacks to the climate system. Despite its importance, current understanding of the drivers of senescence is limited, leading to a large spread in predictions of how the timing of senescence, and thus the length of the growing season, will change under future climate conditions. The most commonly held paradigm is that temperature and photoperiod are the primary controls, which suggests a future extension of the autumnal growing season as global temperatures rise. Here, using two decades of ground‐ and satellite‐based observations of temperate deciduous forest phenology, we show that the timing of autumn senescence is correlated with the timing of spring budburst across the entire eastern United States. On a year‐to‐year basis, an earlier/later spring was associated with an earlier/later autumn senescence, both for individual species and at a regional scale. We use the observed relationship to develop a novel model of autumn phenology. In contrast to current phenology models, this model predicts that the potential response of autumn phenology to future climate change is strongly limited by the impact of climate change on spring phenology. Current models of autumn phenology therefore may overpredict future increases in the length of the growing season, with subsequent impacts for modeling future CO₂ uptake and evapotranspiration.     

The phenology of leaf quality and its within‐canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per‐area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO₂ assimilation. We developed a two‐fraction leaf (sun and shade), two‐layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leaf quantity, quality, and within‐canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground‐based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two‐fraction leaf, two‐layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance‐derived CO₂ assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO₂ assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.     

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.     

Smell the change: On the potential of gas‐chromatographic ion mobility spectrometry in ecosystem monitoring

Plant volatile organic compounds (pVOCs) are being recognized as an important factor in plant–environment interactions. Both the type and amount of the emissions appear to be heavily affected by climate change. A range of studies therefore has been directed toward understanding pVOC emissions, mostly under laboratory conditions (branch/leaf enclosure). However, there is a lack of rapid, sensitive, and selective analytical methods, and therefore, only little is known about VOC emissions under natural, outdoor conditions. An increased sensitivity and the identification of taxon‐specific patterns could turn VOC analysis into a powerful tool for the monitoring of atmospheric chemistry, ecosystems, and biodiversity, with far‐reaching relevance to the impact of climate change on pVOCs and vice versa. This study for the first time investigates the potential of ion mobility spectrometry coupled to gas‐chromatographic preseparation (GC‐IMS) to dramatically increase sensitivity and selectivity for continuous monitoring of pVOCs and to discriminate contributing plant taxa and their phenology. Leaf volatiles were analyzed for nine different common herbaceous plants from Germany. Each plant turned out to have a characteristic metabolite pattern. pVOC patterns in the field would thus reflect the composition of the vegetation, but also phenology (with herbaceous and deciduous plants contributing according to season). The technique investigated here simultaneously enables the identification and quantification of substances characteristic for environmental pollution such as industrial and traffic emissions or pesticides. GC‐IMS thus has an enormous potential to provide a broad range of data on ecosystem function. This approach with near‐continues measurements in the real plant communities could provide crucial insights on pVOC‐level emissions and their relation to climate and phenology and thus provide a sound basis for modeling climate change scenarios including pVOC emissions.     

Seasonality and phenology alter functional leaf traits

In plant ecophysiology, functional leaf traits are generally not assessed in relation to phenological phase of the canopy. Leaf traits measured in deciduous perennial species are known to vary between spring and summer seasons, but there is a knowledge gap relating to the late-summer phase marked by growth cessation and bud set occurring well before fall leaf senescence. The effects of phenology on canopy physiology were tested using a common garden of over 2,000 black cottonwood (Populus trichocarpa) individuals originating from a wide geographical range (44–60ºN). Annual phenological events and 12 leaf-based functional trait measurements were collected spanning the entire summer season prior to, and following, bud set. Patterns of seasonal trait change emerged by synchronizing trees using their date of bud set. In particular, photosynthetic, mass, and N-based traits increased substantially following bud set. Most traits were significantly different between pre-bud set and post-bud set phase trees, with many traits showing at least 25 % alteration in mean value. Post-bud set, both the significance and direction of trait–trait relationships could be modified, with many relating directly to changes in leaf mass. In Populus, these dynamics in leaf traits throughout the summer season reflected a shift in whole plant physiology, but occurred long before the onset of leaf senescence. The marked shifts in measured trait values following bud set underscores the necessity to include phenology in trait-based ecological studies or large-scale phenotyping efforts, both at the local level and larger geographical scale.     

Variation in evergreen and deciduous species leaf phenology in Assam, India

In the present study phenological activities such as leaf and shoot growth, leaf pool size and leaf fall were observed for 3 years (March 2007–March 2010) in 19 tree species (13 evergreen and 6 deciduous species) in a wet tropical forest in Assam, India. The study area receives total annual average rainfall of 2,318 mm of which most rain fall (>70 %) occurs during June–September. Both the plant groups varied significantly on most of the shoot and leaf phenology parameters. In general, growth in deciduous species initiated before the evergreen species and showed a rapid shoot growth, leaf recruitment and leaf expansion compared to evergreen species. Leaf recruitment period was significantly different between evergreen (4.2 months) and deciduous species (6.8 months). Shoot elongation rate was also significantly different for evergreen and deciduous species (0.09 vs. 0.14 cm day^?1 shoot^?1). Leaf number per shoot was greater for deciduous species than for evergreen species (34 vs. 16 leaves). The average leaf life span of evergreen species (328 ± 32 days) was significantly greater than that of deciduous species (205 ± 16 days). The leaf fall in deciduous species was concentrated during the winter season (Nov–Feb), whereas evergreens retained their leaves until the next growing season. Although the climate of the study area supports evergreen forests, the strategies of the deciduous species such as faster leaf recruitment rate, longer leaf recruitment time, faster shoot elongation rate during favorable growing season and short leaf life span perhaps allows them to coexist with evergreen species that have the liberty to photosynthesize round the year. Variations in phenological strategies perhaps help to reduce the competition among evergreen and deciduous species for resources in these forests and enable the coexistence of both the groups.     

Antagonistic effects of growing season and autumn temperatures on the timing of leaf coloration in winter deciduous trees

Autumn phenology remains a relatively neglected aspect in climate change research, which hinders an accurate assessment of the global carbon cycle and its sensitivity to climate change. Leaf coloration, a key indicator of the growing season end, is thought to be triggered mainly by high or low temperature and drought. However, how the control of leaf coloration is split between temperature and drought is not known for many species. Moreover, whether growing season and autumn temperatures interact in influencing the timing of leaf coloration is not clear. Here, we revealed major climate drivers of leaf coloration dates and their interactions using 154 phenological datasets for four winter deciduous tree species at 89 stations, and the corresponding daily mean/minimum air temperature and precipitation data across China's temperate zone from 1981 to 2012. Results show that temperature is more decisive than drought in causing leaf coloration, and the growing season mean temperature plays a more important role than the autumn mean minimum temperature. Higher growing season temperature and lower autumn minimum temperature would induce earlier leaf coloration date. Moreover, the mean temperature over the growing season correlates positively with the autumn minimum temperature. This implies that growing season mean temperature may offset the requirement of autumn minimum temperature in triggering leaf coloration. Our findings deepen the understanding of leaf coloration mechanisms in winter deciduous trees and suggest that leaf life‐span control depended on growing season mean temperature and autumn low temperature control and their interaction are major environmental cues. In the context of climate change, whether leaf coloration date advances or is delayed may depend on intensity of the offset effect of growing season temperature on autumn low temperature.     

南京地区落叶栎林木本植物叶物候研究

叶物候参数长期以来被认为与植物的碳获取的最大化有关,能反映物种的资源利用策略。温带地区因为寒冷冬天的限制,延长叶寿命成为一些物种进行生长发育和繁衍的基础。为探讨叶寿命延长的可能途径(早出叶、晚落叶,或两者兼有),该研究以南京地区两个落叶栎(Quercus spp.)林为研究对象,观测了其中木本植物的出叶物候、落叶物候,并分析了它们与叶寿命之间的关系。结果发现:1)不同物种的出叶开始时间相差较大,出叶早的物种早结束出叶过程;2)不同物种的落叶开始时间相差较大,早开始落叶的物种,落叶持续时间较长,落叶结束时间则相对集中。3)相关分析和回归分析都表明,叶寿命与出叶时间和落叶时间显著关联,但早出叶对叶寿命的延长可能更为重要,因为早出叶相对于晚落叶在物种资源利用上比较具有优势。4)不同物种的出叶时间和落叶时间没有显著相关,可能因为出叶过程和落叶过程是由不同的启动因子引起。这说明延长叶寿命不一定同时通过早出叶和晚落叶来达到。