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The CLUE-S model is a popular choice for modelling land use and land cover change from local to regional scales, but it spatially allocates the demand for only the total cover of each land class in the predicted map. In the present work, we introduce a CLUE-S variant that allocates demand at the more detailed level of land type transitions, the trans-CLUE-S model. We implemented this extension algorithmically in R, without the need of new parameters. By processing each row of the land transition matrix separately, the model allocates the demand of each land category’s transitions via the CLUE-S allocation routine for only the cells which were of that category in the map of the previous time step. We found that the trans-CLUE-S model had half the total and configuration disagreement of the CLUE-S predictions in an empirical landscape, and in simulated landscapes of different characteristics. Moreover, the trans-CLUE-S performance was less sensitive to the number of environmental predictors of land type suitability for allocating demand. Although trans-CLUE-S is computationally more demanding due to running a CLUE-S allocation for each land class, we appended the solution of a land-use assignment optimisation problem that facilitates the convergence and acceleration of allocation. We additionally provide R functions for: CLUE-S variants at other levels of demand resolution; random instead of environment-based allocation; and for simulating landscapes of desired characteristics. Our R code for the models and functions can contribute to more reproducible, transparent and accurate modelling, analysis and interpretation of land cover change.HighlightsThe trans-CLUE-S model employs demand at the finer level of land type transitionsThe trans-CLUE-S predictions were twice more accurate than the CLUE-S model’sThe trans-CLUE-S accuracy was less dependent on the amount of environmental dataAlgorithmic addition of a land assignment task enabled and sped up full convergenceR code is provided for our models and auxiliary functions

Aim: Vegetation types of Mediterranean thermophilous pine forests dominated by Pinus brutia, Pinus halepensis, Pinus pinaster and Pinus pinea were studied in various areas. However, a comprehensive formal vegetation classification of these forests based on a detailed data analysis has never been developed. Our aim is to provide the first broad-scale classification of these pine forests based on a large data set of vegetation plots. Location: Southern Europe, North Africa, Levant, Anatolia, Crimea and the Caucasus. Methods: We prepared a data set of European and Mediterranean pine forest vegetation plots. We selected 7,277 plots dominated by the cold-sensitive Mediterranean pine species Pinus brutia, Pinus halepensis, Pinus pinaster and Pinus pinea. We classified these plots using TWINSPAN, interpreted the ecologically and biogeographically homogeneous TWINSPAN clusters as alliances, and developed an expert system for automatic vegetation classification at the class, order and alliance levels. Results: We described Pinetea halepensis as a new class for the Mediterranean lowland to submontane pine forests, included in the existing Pinetalia halepensis order, and distinguished 12 alliances of native thermophilous pine forests, including four newly described and three informal groups merging supposedly native stands and old-established plantations. The main gradients in species composition reflect elevational vegetation belts and the west-east, and partly north-south, biogeographical differences. Both temperature and precipitation seasonality co-vary with these gradients. Conclusions: We provide the first formal classification at the order and alliance levels for all the Mediterranean thermophilous pine forests based on vegetation-plot data. This classification includes traditional syntaxa, which have been critically revised, and a new class and four new alliances. We also outline a methodological workflow that might be useful for other vegetation classification syntheses. The expert system, which is jointly based on pine dominance and species composition, is a tool for applying this classification in research and nature conservation survey, monitoring and management. Department of Botany and Zoology, Masaryk University; Free University of Bozen-Bolzano [TN201H]; Czech Science FoundationGrant Agency of the Czech Republic [19-28491X]; Plan Propio of the UCLM [2020-GRIN-29214]; European Social Fund (POCH); National Funds (MCTES) through a Fundacao para a Ciencia e a Tecnologia postdoctoral fellowship [SFRH/BPD/115057/2016, UIDB/04033/2020] GB was funded by the post-doc programme of the Department of Botany and Zoology, Masaryk University and by the Free University of Bozen-Bolzano through the CONplant project (TN201H), JD, IK, LT and MC by the Czech Science Foundation (19-28491X), FFG by the Plan Propio of the UCLM (2020-GRIN-29214), TMH by the European Social Fund (POCH), by National Funds (MCTES) through a Fundacao para a Ciencia e a Tecnologia postdoctoral fellowship (SFRH/BPD/115057/2016) and project no. UIDB/04033/2020.

Monitoring of habitat types conservation status is an essential task in the frame of the European policy for biodiversity conservation. The parameters to be assessed for the purposes of habitat types’ conservation status assessment are described in several European documents, but the methodology for their determination has not yet been standardized or optimized. This study presents methods for the assessment of the actual status and the future prospects of structure and functions of habitat types. Specifically, it presents a bottom–up approach for the assessment of these two parameters at different spatial scales. In the proposed method, conservation status assessment is based on a classification of habitat types to subtypes, with the latter representing the basic monitoring entities. The conservation status is assessed by recording: (i) the presence/absence of specific indicators of structure and functions per habitat type, and (ii) the presence/absence, abundance, and vitality of the typical species of the habitat subtypes. The typical species are determined objectively using algorithms and fidelity coefficient values. The conservation status and future prospects of structure and functions (including the typical species) are estimated quantitatively with the help of numerical methods and algorithms, but their assignment to conservation status classes is based on thresholds defined by experts. Assessments are made at the local scale, but can be upscaled to coarser ones (up to the national level). The proposed methods have been applied in Greece and were effective both in terms of results obtained and costs needed.

An increase in drought could cause shifts in species composition and vegetation structure. In forests it limits the occurrence of drought sensitive tree species which become replaced by drought tolerant tree species and forest communities. Under temperate macroclimatic conditions, European beech (Fagus sylvatica L.) naturally dominates the forested landscape, except on extremely shallow soil in combination with high irradiation. On these sites beech reaches its drought limit, and is replaced by forests dominated by species like downy Oak (Quercus pubescens s.l.) and English Oak (Quercus petraea L). Phytosociological and ecological data were collected in the transition (ecotone) between European beach stands and stands of more drought tolerant species in order to quantify the drought intensity threshold, above which beech is replaced by drought tolerant species. It was shown that favourable topographic and soil conditions partially compensated the unsuitable climatic conditions for beech. The ecotone between these forest types was found to be characterized by shallow soils with an available soil water storage capacity of 73 l/m² or less, and an irradiation intensity of 6000 MJ/m2 or more during the growing season. This indicates that under conditions of climate change beech would naturally still remain the dominant tree species on the majority of central European forest sites.

Accurate estimates of forest inventory parameters are essential to assess the potential hazards of wildfire and obtain above-ground biomass and carbon sequestration data that help develop strategies for the sustainable management of forests. This study aims to assess the accuracy of estimation of forest inventory parameters, such as diameter at breast height (DBH) and tree height, obtained using a Terrestrial Laser Scanner (TLS) in a Mediterranean coniferous stand in western Greece. DBH values measured in the field were compared with those derived from a TLS using the Computree algorithm for automatic DBH detection, and resulted in a coefficient of determination ( $$R^{2})$$ that ranged from 0.75 to 0.96 at the plot level. The average $$R^{2}$$ and RMSE values of 0.80 and 1.07 m, respectively, were obtained when comparing the tree heights recorded by TLS and field data. Finally, the feasibility of TLS to estimate total dry biomass was investigated by comparing the TLS-derived total dry biomass values with those derived from field estimates using an allometric equation. The average estimate of biomass per hectare according to the TLS inventory data was 373.17 Mg/ha while that from field observations was 366.82 Mg/ha. The results confirm that TLS can provide non-destructive, high-resolution and precise determination of forest inventory parameters. The outcomes of this research will help researchers to better comprehend deviations in the accuracy of forest inventory variable retrieval resulting from the variation in the processing parameters supplied and additionally boost decision-making in forest management.

The objective of this paper is to document the role of fire in shaping the landscape by identifying links between historical fire records and the current landscape indicating that fire favors certain land use/land cover (LULC) types. We geo-referenced fire records taken from 1922 to 2000 in Aitoloakarnania, the largest prefecture -in terms of surface area- of Greece and compared the past LULC classes where fires burned to the present landscape. The outputs indicated a shift of the historic fire ignition points from natural to agricultural-related LULC classes since a significant proportion of fire incidents that, according to the fire records, burnt natural vegetation units is currently located in agricultural landscape units. Additionally, a significant proportion of the fire-affected land cover classes retain their character thus supporting the argument that these classes, especially fire-prone or fire-resistant, have developed mechanisms to cope with fire. In such ecosystems the role of fire is to maintain rather than transform land cover classes. The findings of this research lead us to conclude that fire can be perceived as a long-term landscape modifier in the Mediterranean, although its effects may vary from region to region because of differences in regeneration patterns among the main land cover types, topographic constraints and local fire histories. Historical fire records extending back to the early 20th century proved to provide valuable information that can reveal interesting patterns of fire burning history and explain present land cover and use patterns. This knowledge, documented from historical records, can be used to develop fire management and land cover/land use management planning.

Large thematic databases of vegetation plots are increasingly needed for vegetation studies and biodiversity research. In this paper, we present the CircumMed Pine Forest Database (GIVD ID: EU-00-026), which in November 2018, comprised records from 6317 pine-dominated vegetation plots (relevés) and associated vegetation types from 20 countries of the Mediterranean Basin, Near East and Crimea. These vegetation plots were collected through a detailed literature search for plots not previously included in the European Vegetation Archive (EVA), in order to fill geographic gaps in data coverage. The database comprises Mediterranean (including Oromediterranean) pine-forest vegetation plots from both published and unpublished sources. All vegetation plots are georeferenced, although coordinates vary in accuracy. The database is accessible through EVA or from its Custodian. We anticipate the CircumMed Pine Forest Database will be a valuable resource for various types of broad-scale studies in the fields of vegetation classification, plant invasion ecology, macroecology and biological conservation. Abbreviations: EU = European Union; EVA = European Vegetation Archive; EVS = European Vegetation Survey; GIVD = Global Index of Vegetation-Plot Databases.

Historical fire records and meteorological observations spanning over one century (1894–2010) were assembled in a database to collect long-term fire and weather data in Greece. Positive/negative events of fire occurrence on an annual basis were considered as the years where the annual values of the examined parameters were above (positive values) or below (negative values) the 95% confidence limits around the trend line of the corresponding parameter. To analyse the association of positive/negative events of fire occurrence with meteorological extremes, we proceeded with a cross-tabulation analysis based on a Monte Carlo randomization. Positive/negative values of total annual precipitation were randomly associated with the corresponding values of burned areas, and significant associations were observed for seasonal precipitation totals (spring and fire season). Fire season precipitation is the dominant factor coinciding with negative values of area burned, while years with high spring precipitation coincide with years with large areas burned. These results demonstrate the dual role of precipitation in controlling a fire's extent through fuel build-up and dryness. Additionally, there is a clear outperformance of precipitation-related variables compared with temperature-related weather revealing that, at least in Greece, total area burned at the national scale is controlled by precipitation totals rather than air temperature. This analysis improves our understanding of the underlying mechanisms of fire regimes and provides valuable information concerning the development of models relating fire activity to weather parameters, which are essential when facing a changing climate that may be associated with shifts in various aspects of the typical fire regimes of ecosystems. Our results may allow fire managers to more easily incorporate the effect of extreme weather conditions into long-term planning strategies. They contribute to the exploration of fire–climate relationships and may become more important if climate change scenarios are used to predict the occurrence of future extreme weather taking into consideration that climate change is discussed on the basis of changes of extremes rather than changes in means.

Climate and weather play an important role in shaping fire activity patterns by controlling fuel productivity and fire spread, respectively. Additionally, climate is a key factor controlling primary productivity while different climate zones are expected to support different vegetation formations, that on their turn, include different fuel types. The use, therefore, of an underlying phytogeographical framework would provide more comprehensive outputs in exploring fire activity patterns at national scales, instead of using administrative units that could include various types of non-ecological divisions. Within this concept, we examined the recent fire activity of the main forest formations occurring in Greece and we explored their relationships with various weather parameters and indexes. Correlations of number of fires with weather variables, especially among the vegetation formations that summarize most of the human influence were lax, yet burned area showed significant correlations mainly with fire season precipitation totals. The precipitation related variables generally outperformed the temperature-related variables in correlating with both number of fires and burned area. Climatic indexes, which embody the combined effects of precipitation and air temperature, reflected improved correlations, but not to the extent that could allow for the promotion of their use in further modeling.

In the Mediterranean region, natural vegetation has been strongly affected by human activities for thousands of years. During the last decades, there has been a notable tendency for abandonment of marginal agricultural land that is further associated with a number of ecological consequences. In this study we recorded and mapped the temporal changes of land use/land cover (LULC) classes that were further aggregated into major process-based changes for the period 1945-2009 in Aetoloakarnania prefecture, Greece. LULC mapping was based on aerial photographs acquired in 1945, 1960, 1985-1986 and 2007-2009. Object-based image analysis allowed the classification of the region's LULC classes and, consecutively, the assessment of process-based LULC changes for each time period. The results indicated that agricultural land increased during the first post-war years while abandonment of agricultural land took place during more recent decades, especially after the period 1960-1985. The observed land abandonment is combined with a simultaneous densification of shrublands and forests. Radical socio-economic changes that took place in the 1960's include the migration of rural populations towards big cities and the beginning of the development of the tourist industry. We argue that these socio-economic changes play an important role in shaping the observed LULC changes.

Maps depicting the spatially explicit fire history of an area, including variables such as fire frequency and fire return interval, are important tools promoting the understanding of processes associated with wildfires (fire ignition and spread), the assessment of the impacts of wildland fires on landscape dynamics, and decisions on appropriate management practices. Remote sensing is a cost- and time-effective alternative to automatically assess a vast amount of spatial information and produce various thematic maps. The aim of this study was to reconstruct the recent fire history of Attica region (Greece), in a spatially explicit mode by means of remote sensing techniques using a series of Landsat images acquired from 1984 to 2011. The results show that the fire scar perimeters were captured with high accuracy. Regression modelling shows that the differences between the area burned estimated from satellite data and that recorded by the forest service can be explained (86.3% of the variance) by the number ...

Owing to the difficulties in measuring daily reference potential evapotranspiration, its estimation by means of the ASCE Penman-Monteith approach and various other empirical equations that are less demanding in terms of input data is favoured for various applications in vegetation science and climatology. This study presents the development of a Visual Basic software that can be used for the estimation of the daily PETref by means of the standardized ASCE Penman-Monteith equation for both short (clipped grass) and tall (full-cover alfalfa) crops and thirteen additional empirical equations. Statistical measures of goodness of fit are also calculated to make it easier for users to compare and detect the empirical equations that have the minimum bias of estimation against the ASCE Penman-Monteith equation.

Knowledge of reference potential evapotranspiration (PETref) conditions is important for a number of vegetation- and hydro- logical-related applications. Direct estimations of PETref are difficult and require sophisticated instrumentation. The Food and Agriculture Organization (FAO), therefore, proposed a method for the estimation of PETref using only meteorological data. This equation has been widely accepted as the standard method for the estimation of PETref because of its good fit with measured values. Nevertheless, it requires several meteorological variables (e.g., wind speed), which are rarely available. Where such data are not available, its application is hampered. To overcome this problem, a number of simpler, empirical equations requiring only a fraction of the meteorological input variables required by the FAO PETref have been developed. Before using these equations, it is important to evaluate their performance and choose the equation that will have the lowest possible bias in the estimation of PETref. Using daily meteorological observations obtained from seven meteorological stations on the island of Crete (southern Greece), the performance of 13 empirical equations (radiation- and temperature-based) for the estimation of PETref has been evaluated against the estimations of PETref using the FAO equation. Performance was evaluated on a daily and a monthly basis, and five different measures of goodness offit were used. The results showed that when the use of the FAO equation is not possible because of the unavailability of data, some empirical methods can serve as appropriate alternatives. The radiation-based equations generally performed better than those that included only temperature-related input variables. The equations proposed by Hansen and Turc were the most useful because they had an average monthly absolute error ranging from 5.7 to 17.7 mm and 5.5 to 19.2 mm, respectively. DOI: 10.1061/(ASCE)IR.1943-4774.0000283. © 2011 American Society of Civil Engineers. CE Database subject headings: Evapotranspiration; Evaluation; Performance characteristics; Validation; Greece. Author keywords: Evapotranspiration; Evaluation; Performance characteristics; Validation.

The aim of this study was to prove that altitudinal variability of average monthly and annual precipitation is better summarised when the altitude observed within a radius of several kilometres around a meteorological station is taken into consideration, instead of the altitude of the station itself. The use of the variable Z′, which combines the altitude of the closest mountain with its distance from the station, is compared against the use of altitude alone in simple linear and multiple quadratic regression equations for the altitudinal interpolation of precipitation over Greece. The data-set comprised precipitation observations from 516 meteorological stations. The comparison between the two variables is discussed on the basis of the resulting determination coefficients (R2) and standard errors of estimate (S). For all seasons, except summer, it was found that the variable Z′ improves the predictive ability of the regression equations, thus showing its potential for further use in interpolation procedures.

Question: What components of drought influence the drought limit of Fagus sylvatica forests? This study contributes to the ongoing discussion regarding the future of Fagus as a major component of central European forests. Location: The drought limit of F. sylvatica at its ecotone with forest dominated by Quercus pubescens, Q. petraea and their hybrids in two limestone regions (Klettgau, Schwabische Alb) in southwestern Germany was compared. Methods: Vegetation releves were classified and a gradient analysis was performed. The vegetation pattern was analysed with several drought relevant variables. Classification trees were used to determine the drought limits of the Fagus forest. Results: The Fagus, Quercus and the ecotone forests were floristically characterized. The lower humidity in the submontane Klettgau, compared to the montane Schwabische Alb, was compensated for by greater soil moisture (ASWSC). Therefore, Fagus forest in the Schwabische Alb grew on sites with ASWSC values similar to thos...

The use of spatially explicit fire spread models to assess fire propagation and behaviour has several applications for fire management and research. We used the FARSITE simulator to predict the spread of a set of wildfires that occurred along an east–west gradient of the Euro-Mediterranean countries. The main purpose of this work was to evaluate the overall accuracy of the simulator and to quantify the effects of standard vs custom fuel models on fire simulation performance. We also analysed the effects of different fuel models and slope classes on the accuracy of FARSITE predictions. To run the simulations, several input layers describing each study area were acquired, and their effect on simulation outputs was analysed. Site-specific fuel models and canopy inputs were derived either from existing vegetation information and field sampling or through remote-sensing data. The custom fuel models produced an increase in simulation accuracy, and results were nearly unequivocal for all the case studies examined. We suggest that spatially explicit fire spread simulators and custom fuel models specifically developed for the heterogeneous landscapes of Mediterranean ecosystems can help improve fire hazard mapping and optimise fuel management practices across the Euro-Mediterranean region.

Historical fire records and meteorological observations, spanning more than 1 century (1894–2010), were gathered and assembled in a database, to provide long-term fire–weather associations. We investigated the relationships between forest fire activity and meteorological parameters and sought to find temporal patterns and trends in these historical records and to identify any linkages between meteorological parameters and fire occurrence in the eastern Mediterranean region. Trend analysis of the time series revealed a statistically significant increase in the number of fires and air temperature, particularly after the mid-1970s. Fire occurrence, expressed as the annual number of fires and total burnt area, was strongly correlated with the mean maximum and the absolute maximum air temperature which, in turn, was related to the occurrence of summer heat waves. Total burnt area was also strongly negatively correlated with fire-season precipitation, and positively correlated with 2-year-lagged annual and summer precipitation, underlying the effect of precipitation in controlling fuel production and moisture. These findings support the argument that although annually lagged precipitation totals may have a marginal effect on fire risk by influencing biomass production and accumulation, the lag0 weather parameters are the main drivers of fire spread by directly controlling fuel moisture.