Plant Phenology of the European Alps

Author(s):  
Helfried Scheifinger

Phenology is the study of the seasonal timing of life cycle events. The Belgian botanist Charles Morren introduced the term in 1853, which is a combination of two Greek words, φαίνω, which means to show, to bring to light, make to appear, and λόγος, which means study, discourse, or reasoning. The global change discussion has stimulated phenological research, which as a consequence greatly advanced as science and evolved to one of the main climate impact indicators. Many of the earliest systematic efforts to collect phenological observations took place in countries sharing the Alps, most of which are still operating phenological networks. These phenological data sets are generally freely available to researchers, and numerous essential contributions to the topic of phenology and climate have been built on those data sets. Plant physiological processes underlying the ability of the plants to adapt to the year-to-year variability of the climate still constitutes largely a black box. Since the experiments of René Antoine Ferchault de Reaumur in the 18th century, it is known that temperature constitutes the main environmental driver of the seasonal development of the mid- to high-latitude plants. Second to temperature, day length governs the seasonal cycle of some species as an additional factor. Therefore, temperature-driven phenological models are able to simulate the year-to-year variability of phenological entry dates accurately enough for various applications, such as climate change impact research or numerical pollen forecast models, where the beginning of flowering of some plants is linked with the release of allergic pollen into the atmosphere. Large-scale circulation patterns, like the North Atlantic Oscillation, determine the frequency and intensity of warm and cold spells and decadal temperature trends over Europe. Combined anthropogenic and natural forcings explain the advance of spring phenology over the last 50 years, which is also clearly discernible in the area of the Alps. The early phenological spring starts in Western Europe, whereas later in the season it makes progress with a stronger southerly component across the Alps. The combined temporal and spatial trends have been studied along elevational gradients. Trends toward earlier entry dates are stronger at higher elevations, which indicates that the elevational phenological gradient has weakened since the mid-20th century. Similarly, the vegetation response to temperature is observed to decrease when moving from high to low latitudes. In contrast, the temporal response of plant phenology to increasing temperatures is less clear. Some works indeed demonstrate a decreasing temperature sensitivity with increasing temperature, which is explained as a result of a reduced winter chilling that delays spring phenology or of a limiting effect due to a shorter photoperiod. Other works report no change of temporal temperature sensitivity with increasing temperatures. Indigenous midlatitude vegetation is able to withstand large temperature variations during winter and spring. The safety margin between last frost events, budding, and leaf emergence was found to be uniform across elevations and taxa, except for beech trees. The probability of freezing damage to natural vegetation is almost nil, but late frost risk constitutes a real threat to fruit growers. The ratio of phenological and last frost trends is ambiguous. An increase or decrease in frost risk depends on regions, elevations, and species. Vegetation at high altitudes is exposed to a harsh climate with a long-lasting snow cover, low temperatures, and a short growing season. Snowmelt is a necessary but insufficient requirement for the start of the growing season, which has to be supplemented by plant-specific temperature sums to activate the growth of most alpine and subalpine species. The seasonal cycle has to be completed within a short time. Advances in remote sensing technology have provided access to high-resolution landscape scale phenological information. Especially in remote areas, like the Alps, in situ observations could be supplemented by satellite observations. Observations from both methods, I -situ and remote sensing, have been applied to describe spring vegetation dynamics, but the correlation between these data sets have typically been weak because of differences in temporal and spatial scales and resolutions. A successfully combined description of the seasonal vegetation cycle is still lacking. The area of the European Alps offers a wealth of long chronicles, containing historical phenological observations some of which have been extracted and digitized. Grape harvest dates belong to the most readily available historical phenological observations, which have helped reconstruct summer temperatures as far back as the 15th century.

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 76
Author(s):  
Yahui Guo ◽  
Jing Zeng ◽  
Wenxiang Wu ◽  
Shunqiang Hu ◽  
Guangxu Liu ◽  
...  

Timely monitoring of the changes in coverage and growth conditions of vegetation (forest, grass) is very important for preserving the regional and global ecological environment. Vegetation information is mainly reflected by its spectral characteristics, namely, differences and changes in green plant leaves and vegetation canopies in remote sensing domains. The normalized difference vegetation index (NDVI) is commonly used to describe the dynamic changes in vegetation, but the NDVI sequence is not long enough to support the exploration of dynamic changes due to many reasons, such as changes in remote sensing sensors. Thus, the NDVI from different sensors should be scientifically combined using logical methods. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI are combined using the Savitzky–Golay (SG) method and then utilized to investigate the temporal and spatial changes in the vegetation of the Ruoergai wetland area (RWA). The dynamic spatial and temporal changes and trends of the NDVI sequence in the RWA are analyzed to evaluate and monitor the growth conditions of vegetation in this region. In regard to annual changes, the average annual NDVI shows an overall increasing trend in this region during the past three decades, with a linear trend coefficient of 0.013/10a, indicating that the vegetation coverage has been continuously improving. In regard to seasonal changes, the linear trend coefficients of NDVI are 0.020, 0.021, 0.004, and 0.004/10a for spring, summer, autumn, and winter, respectively. The linear regression coefficient between the gross domestic product (GDP) and NDVI is also calculated, and the coefficients are 0.0024, 0.0015, and 0.0020, with coefficients of determination (R2) of 0.453, 0.463, and 0.444 for Aba, Ruoergai, and Hongyuan, respectively. Thus, the positive correlation coefficients between the GDP and the growth of NDVI may indicate that increased societal development promotes vegetation in some respects by resulting in the planting of more trees or the promotion of tree protection activities. Through the analysis of the temporal and spatial NDVI, it can be assessed that the vegetation coverage is relatively large and the growth condition of vegetation in this region is good overall.


2017 ◽  
Vol 21 (9) ◽  
pp. 4747-4765 ◽  
Author(s):  
Clara Linés ◽  
Micha Werner ◽  
Wim Bastiaanssen

Abstract. The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation–anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.


Diversity ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 146
Author(s):  
Natascha D. Wagner ◽  
Li He ◽  
Elvira Hörandl

The genus Salix (willows), with 33 species, represents the most diverse genus of woody plants in the European Alps. Many species dominate subalpine and alpine types of vegetation. Despite a long history of research on willows, the evolutionary and ecological factors for this species richness are poorly known. Here we will review recent progress in research on phylogenetic relationships, evolution, ecology, and speciation in alpine willows. Phylogenomic reconstructions suggest multiple colonization of the Alps, probably from the late Miocene onward, and reject hypotheses of a single radiation. Relatives occur in the Arctic and in temperate Eurasia. Most species are widespread in the European mountain systems or in the European lowlands. Within the Alps, species differ ecologically according to different elevational zones and habitat preferences. Homoploid hybridization is a frequent process in willows and happens mostly after climatic fluctuations and secondary contact. Breakdown of the ecological crossing barriers of species is followed by introgressive hybridization. Polyploidy is an important speciation mechanism, as 40% of species are polyploid, including the four endemic species of the Alps. Phylogenomic data suggest an allopolyploid origin for all taxa analyzed so far. Further studies are needed to specifically analyze biogeographical history, character evolution, and genome evolution of polyploids.


2021 ◽  
Author(s):  
Florian Betz ◽  
Magdalena Lauermann ◽  
Bernd Cyffka

<p>In fluvial geomorphology as well as in freshwater ecology, rivers are commonly seen as nested hierarchical systems functioning over a range of spatial and temporal scales. Thus, for a comprehensive assessment, information on various scales is required. Over the past decade, remote sensing based approaches have become increasingly popular in river science to increase the spatial scale of analysis. However, data-scarce areas have been mostly ignored so far despite the fact that most remaining free flowing – and thus ecologically valuable – rivers worldwide are located in regions characterized by a lack of data sources like LiDAR or even aerial imagery. High resolution satellite data would be able to fill this data gap, but tends to be too costly for large scale applications what limits the ability for comprehensive studies on river systems in such remote areas. This in turn is a limitation for management and conservation of these rivers.</p><p>In this contribution, we suggest an approach for river corridor mapping based on open access data only in order to foster large scale geomorphological mapping of river corridors in data-scarce areas. For this aim, we combine advanced terrain analysis with multispectral remote sensing using the SRTM-1 DEM along with Landsat OLI imagery. We take the Naryn River in Kyrgyzstan as an example to demonstrate the potential of these open access data sets to derive a comprehensive set of parameters for characterizing this river corridor. The methods are adapted to the specific characteristics of medium resolution open access data sets and include an innovative, fuzzy logic based approach for riparian zone delineation, longitudinal profile smoothing based on constrained quantile regression and a delineation of the active channel width as needed for specific stream power computation. In addition, an indicator for river dynamics based on Landsat time series is developed. For each derived river corridor parameter, a rigor validation is performed. The results demonstrate, that our open access approach for geomorphological mapping of river corridors is capable to provide results sufficiently accurate to derive reach averaged information. Thus, it is well suited for large scale river characterization in data-scarce regions where otherwise the river corridors would remain largely unexplored from an up-to-date riverscape perspective. Such a characterization might be an entry point for further, more detailed research in selected study reaches and can deliver the required comprehensive background information for a range of topics in river science.</p>


2021 ◽  
Author(s):  
Luz Karime Atencia ◽  
María Gómez del Campo ◽  
Gema Camacho ◽  
Antonio Hueso ◽  
Ana M. Tarquis

<p>Olive is the main fruit tree in Spain representing 50% of the fruit trees surface, around 2,751,255 ha. Due to its adaptation to arid conditions and the scarcity of water, regulated deficit irrigation (RDI) strategy is normally applied in traditional olive orchards and recently to high density orchards. The application of RDI is one of the most important technique used in the olive hedgerow orchard. An investigation of the detection of water stress in nonhomogeneous olive tree canopies such as orchards using remote sensing imagery is presented.</p><p>In 2018 and 2019 seasons, data on stem water potential were collected to characterize tree water state in a hedgerow olive orchard cv. Arbequina located in Chozas de Canales (Toledo). Close to the measurement’s dates, remote sensing images with spectral and thermal sensors were acquired. Several vegetation indexes (VI) using both or one type of sensors were estimated from the areas selected that correspond to the olive crown avoiding the canopy shadows.</p><p>Nonparametric statistical tests between the VIs and the stem water potential were carried out to reveal the most significant correlation. The results will be discussing in the context of robustness and sensitivity between both data sets at different phenological olive state.</p><p><strong>ACKNOWLODGEMENTS</strong></p><p>Financial support provided by the Spanish Research Agency co-financed with European Union FEDER funds (AEI/FEDER, UE, AGL2016-77282-C3-2R project) and Comunidad de Madrid through calls for grants for the completion of Industrial Doctorates, is greatly appreciated.</p>


2012 ◽  
Vol 27 (3) ◽  
pp. 263-271 ◽  
Author(s):  
Monica Cristina Damião Mendes ◽  
Iracema F. A. Cavalcanti ◽  
Dirceu Luis Herdies

An assessment of blocking episodes over the Southern Hemisphere, selected from the Era-40 and NCEP/NCAR reanalysis are presented in this study. Blocking can be defined by an objective index based on two 500 hPa geopotential height meridional gradients. The seasonal cycle and preferential areas of occurrence are well reproduced by the two data sets. In both reanalysis used in this study, South Pacific and Oceania were the preferred regions for blocking occurrence, followed by the Atlantic Ocean. However the results revealed differences in frequencies of occurrences, which may be related to the choice of assimilation scheme employed to produce the reanalysis data sets. It is important to note that the ERA 40 and NCEP/NCAR reanalysis were produced using consistent models and assimilation schemes throughout the whole reanalyzed period, which are different for each set.


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