Identification of Years with Extreme Vegetation State in Central Europe Based on Remote Sensing and Meteorological Data

Background and Purpose: Determination of an extreme year from the aspect of the vegetation activity using only meteorological data might be ambiguous and not adequate. Furthermore, in some ecosystems, e.g. forests, the response is not instantly visible, but the effects of the meteorological anomaly can be seen in the following year. The aim of the present paper is to select and characterize typical and anomalous years using satellite-based remote sensing data and meteorological observations during the recent years of 2000-2014 for Central Europe, based on the response of the vegetation. Materials and Methods: In the present study vegetation characteristics were described using remotely sensed official products of the MODerate resolution Imaging Spectroradiometer (MODIS), namely NDVI, EVI, FPAR, LAI, GPP, and NPP, with 8-day temporal and 500 meter spatial resolution for the period of 2000-2014. The corresponding mean temperature and precipitation data (on the same grid) were derived from the Open Database for Climate Change Related Impact Studies in Central Europe (FORESEE) daily meteorological dataset. Land cover specific anomalies of the meteorological and vegetation characteristics were created and averaged on a country-scale, where the distinction between the main land cover types was based on the synergetic use of MODIS land cover and Coordination of Information on the Environment (CORINE) Land Cover 2012 datasets. Results: It has been demonstrated that the anomaly detection based solely on basic meteorological variables is ambiguous since the strength of the anomaly depends on the selected integration time period. In contrast, the effect-based approach exploiting the available, state-of-the-art remote sensing based vegetation indices is a promising tool for the characterization of the anomalous behaviour of the different land cover types. The selection of extreme years was performed in an explicit way using percentile analysis on pixel level. Conclusions: Plant status in terms of both positive and negative anomalies shows strong land cover dependency in Central Europe. This is most likely due to the differences in heat and drought resistance of the vegetation, and species composition. The selection of country-specific extreme years can serve as a basis for forthcoming research

Fine-scale variation in projected climate change presents opportunities for biodiversity conservation in Europe

Climate change is a major threat to global biodiversity, although projected changes show remarkable geographical and temporal variability. Understanding this variability allows for the identification of regions where the present-day conservation objectives may be at risk or where opportunities for biodiversity conservation emerge. We use a multi-model ensemble of regional climate models to identify areas with significantly high and low climate stability persistent throughout the 21st century in Europe. We then confront our predictions with the land coverage of three prominent biodiversity conservation initiatives at two scales. The continental-scale assessment shows that areas with the least stable future climate in Europe are likely to occur at low and high latitudes, with the Iberian Peninsula and the Boreal zones identified as prominent areas of low climatic stability. A follow-up regional scale investigation shows that robust climatic refugia exist even within the highly exposed southern and northern macro-regions. About 23-31 % of assessed biodiversity conservation sites in Europe coincide with areas of high future climate stability, we contend that these sites should be prioritised in the formulation of future conservation priorities as the stability of future climate is one of the key factors determining their conservation prospects. Although such focus on climate refugia cannot halt the ongoing biodiversity loss, along with measures such as resilience-based stewardship, it may improve the effectiveness of biodiversity conservation under climate change

Natural disturbance regimes as a guide for sustainable forest management in Europe

Dette er den aksepterte versjonen av en artikkel publisert i Ecological Applications. Den blir tilgjengelig fra og med 28.03.2023 etter en embargoperiode på 12 måneder. Du finner den publiserte artikkelen her: https://doi.org/10.1002/eap.2596. / This is the postprint version of the article published in Ecological Applications. It will be available 28.03.2023 after an embargo period of 12 months.You can find the published article here: https://doi.org/10.1002/eap.2596.In Europe, forest management has controlled forest dynamics to sustain commodity production over multiple centuries. Yet over-regulation for growth and yield diminishes resilience to environmental stress as well as threatens biodiversity, leading to increasing forest susceptibility to an array of disturbances. These trends have stimulated interest in alternative management systems, including natural dynamics silviculture (NDS). NDS aims to emulate natural disturbance dynamics at stand and landscape scales through silvicultural manipulations of forest structure and landscape patterns. We adapted a “Comparability Index” (CI) to assess convergence/divergence between natural disturbances and forest management effects. We extended the original CI concept based on disturbance size and frequency by adding the residual structure of canopy trees after a disturbance as a third dimension. We populated the model by compiling data on natural disturbance dynamics and management from 13 countries in Europe, covering four major forest types (i.e., spruce, beech, oak, and pine-dominated forests). We found that natural disturbances are highly variable in size, frequency, and residual structure, but European forest management fails to encompass this complexity. Silviculture in Europe is skewed toward even-aged systems, used predominately (72.9% of management) across the countries assessed. The residual structure proved crucial in the comparison of natural disturbances and silvicultural systems. CI indicated the highest congruence between uneven-aged silvicultural systems and key natural disturbance attributes. Even so, uneven-aged practices emulated only a portion of the complexity associated with natural disturbance effects. The remaining silvicultural systems perform poorly in terms of retention compared to tree survivorship after natural disturbances. We suggest that NDS can enrich Europe’s portfolio of management systems, for example where wood production is not the primary objective. NDS is especially relevant to forests managed for habitat quality, risk reduction, and a variety of ecosystem services. We suggest a holistic approach integrating NDS with more conventional practices.acceptedVersio

Influence of estimation neighbourhood selection on result of spatial interpolation

The selection of data points to be included in the estimation is a key problem in the application of spatial interpolation. A common practce to define a single search strategy for an entire area being estimated is not always a good approach. What works in certain areas of a particular data set may not work in others. The solution is to restrict the data point selection to a subset of the data, changing with the estimated point, and thus called a moving neighbourhood. Sophisticated neighbourhood algorithms have been devised to reach a compromise between near and far sample point. They ussualy include all points within the first ring and then more distance points, following the strategy that attempts to sample all directions as uniformly as possible, while keeping the number of points as low as possible. Deciding which samples are relevant for estimation of a particular point may be more important than the choice of an estimation method.What is the optimum design of a moving neighbourhood? This question turns out to be rather complex. Short of the theory presented in the paper can only give some quidelines

Vegetations-Umwelt-Beziehungen in Rasengesellschaften der Zentralslowakei

A systematic survey of grassland communities in central Slovakian sub-montane and montane regions (including the Kremnické vrchy Mts., Starohorské vrchy Mts., Veľká Fatra Mts., and Zvolenská kotlina Basin) was performed between 1996 and 2007. The main aim was to identify main environmental gradients in the studied vegetation and to estimate the most important individual variables responsible for the variation of their species composition. Along with the floristic composition, the environmental variables were either recorded in the field (altitude, slope, aspect), calculated (solar radiation, climatic data, and phytochorological affinity), or derived from available maps or GIS digital data layers (type of bedrock, soil parameters). These environmental variables were used as supplementary in the detrended correspondence analysis (DCA) or explanatory in the canonical correspondence analysis (CCA). The affiliation of individual phytosociological relevés to associations was estimated by an electronic expert system for Slovak grassland communities. Altogether, 15 xero-, sub-xero- and mesophilous grassland associations were distinguished. Wet and fen meadows were analysed at the level of alliances. Unconstrained ordination revealed moisture and nutrient gradients as most important for the data set. By means of constrained ordination, the variability of the studied vegetation could be explained by a set of geological, topographic, phytochorological and derived climatic variables, although the percentage of explained variance was rather low and did not exceed 12% for all significant factors combined. Among individual variables, the geological bedrock type, climatic water balance, solar radiation, and slope played the most important role in determining the distribution and variability of individual grassland communities. Affinity to phytochorions determined according to local air temperature gradients was also significant. Soil properties played only a subordinate role in our analyses. The analysis of a more homogeneous subset of the data without wetland relevés gave similar results as the analysis of the complete data set. The differences in results of constrained and unconstrained ordinations are discussed together with the potential reasons for extremely high proportion of unexplained variance revealed by the variation partitioning methods.Wir haben die Rasengesellschaften in den submontanen und montanen Regionen der Zentralslowakei (mit den Mittelgebirgszügen Kremnické vrchy, Starohorské vrchy und Veľká Fatra sowie dem Zvolenská kotlina-Becken) im Zeitraum 1996–2007 systematisch untersucht. Ziel war es, die hauptsächlichen Umweltgradienten und die wesentlichen Variablen zu bestimmen, welche für die Unterschiede in der Artenzusammensetzung verantwortlich sind. Die betrachteten Umweltvariablen wurden entweder gemeinsam mit der Artenzusammensetzung im Gelände erhoben (Höhe, Hangneigung und -exposition), berechnet (Strahlungsgenuss, Klimaparameter, phytochorologische Zugehörigkeit) oder aus verfügbaren GIS-Karten entnommen (Gesteinart, Bodenparameter). Diese Umweltvariablen wurden als passive Variablen in trendbereinigten Korrespondenzanalysen (DCAs) und als erklärende Variablen in kanonischen Korrespondenzanalysen (CCAs) verwendet. Die Zuordnung einzelner Vegetationsaufnahmen zu Assoziationen erfolgte mit Hilfe des Slowakischen Elektronischen Expertensystems für Rasengesellschaften. Insgesamt wurden 15 Assoziationen von Volltrockenrasen, Halbtrockenrasen und mesophilem Grünland unterschieden. Feuchtwiesen und Niedermoorgesellschaften wurden auf der Ebene von Verbänden analysiert. Die DCAs zeigten, dass der Feuchtigkeits- und der Nährstoffgradient die größte Bedeutung für die floristische Differenzierung innerhalb der betrachteten Aufnahmen haben. Nach den CCAs kann die Variabilität in der Artenzusammensetzung durch eine Gruppe von geologischen, topografischen, phytochorologischen und abgeleiteten Klimavariablen erklärt werden, wenngleich der Anteil erklärter Varianz mit maximal 12 % recht niedrig war. Als Einzelvariablen waren Gesteinstyp, klimatische Wasserbilanz, Strahlungsgenuss und Hangneigung am bedeutsamsten. Die Zugehörigkeit zu einem Wuchsgebiet (Phytochorion), welche anhand der regionalen Temperaturgadienten ermittelt wurde, war ebenfalls signifikant. Dagegen spielten Bodeneigenschaften nur eine untergeordnete Rolle. Die Analyse eines reduzierten, homogeneren Datensets ohne die Feuchtgebietsaufnahmen ergab qualitativ ähnliche Ergebnisse wie jene für den Gesamtdatensatz. Abschließend werden die Unterschiede zwischen den Ergebnissen von DCAs und CCAs erläutert und Gründe für den geringen Anteil erklärter Varianz diskutiert

MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests

International audienceContext Variation in photosynthetic activity of trees induced by climatic stress can be effectively evaluated using remote sensing data. Although adverse effects of climate on temperate forests have been subjected to increased scrutiny, the suitability of remote sensing imagery for identification of drought stress in such forests has not been explored fully.Aim The study seeks to evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests, and to explore the differences in stress response of oaks and beech.MethodsWe identified 8 oak and 13 beech pure and mature stands, each covering between 4 and 13 MODIS pixels. For each pixel, we extracted a time series of MODIS NDVI from 2000 to 2010. We identified all sequences of continuous unseasonal NDVI decline to be used as the response variable indicative of environmental stress. Neural network-based regression modelling was then applied to identify the climatic variables that best explain observed NDVI declines. Results Tested variables explained 84–97 % of the variation in NDVI, whilst air temperature-related climate extremes were found to be the most influential. Beech showed a linear response to the most influential climatic predictors, while oak responded in a unimodal pattern suggesting a better coping mechanism.Conclusions MODIS NDVI has proved sufficiently sensitive as a stand-level indicator of climatic stress acting upon temperate broadleaf forests, leading to its potential use in predicting drought stress from meteorological observations and improving parameterisation of forest stress indices