Remote sensing of protected areas to derive baseline vegetation functioning characteristics

Question: How can we derive baseline/reference situations to evaluate the impact of global change on terrestrial ecosystem functioning? Location: Main biomes (steppes to rain forests) of Argentina. Methods: We used AVHRR/NOAA satellite data to characterize vegetation functioning. We used the seasonal dynamics of the Normalized Difference Vegetation Index (NDVI), a linear estimator of the fraction of the photosynthetic active radiation intercepted by vegetation (f_PAR), and the surface temperature (Ts), for the period 1981–1993. We extracted the following indices: NDVI integral (NDVI‐I), NDVI relative range (R_rel), NDVI maximum value (V_max), date of maximum NDVI (D_max) and actual evapotranspiration. Results: f _PAR varied from 2 to 80%, in relation to changes in net primary production (NPP) from 83 to 1700 g.m‐².yr^‐1. NDVI‐I, Vmax and f_PAR had positive, curvilinear relationships to mean annual precipitation (MAP), NPP was linearly related to MAP. Tropical and subtropical biomes had a significantly lower seasonality (R_rel) than temperate ones. D_max was not correlated with the defined environmental gradients. Evapotranspiration ranged from 100 to 1100 mm.yr^‐1. Interannual variability of NDVI attributes varied across the temperature and precipitation gradients. Conclusions: Our results may be used to represent baseline conditions in evaluating the impact of land use changes across environmental gradients. The relationships between functional attributes and environmental variables provide a way to extrapolate ecological patterns from protected areas across modified habitats and to generate maps of ecosystem functioning.     

The link between landscape pattern and vegetation naturalness on a regional scale

The land use and land cover pattern of landscapes are key elements of basic landscape structure; accordingly, this pattern has an important role in landscape management, nature conservation and preservation. In Hungary, the naturalness of the vegetation was surveyed between 2003 and 2006, and the vegetation-based Natural Capital Index (NCI) was calculated for almost the entire area of the country. This field-based database gave us the unique opportunity to analyse the statistical connection between the naturalness of the vegetation and the landscape (land cover) pattern on a regional scale. In our study, we analysed the efficiency of the regional-level CORINE Land Cover (CLC) database for the estimation of the naturalness of the vegetation. This connection was analysed at the country scale using every (2272) Flora Mapping Unit (FMU), or 5.5 × 6.5 km quadrate, of Hungary. We calculated the shape-, edge- and size-related landscape indices for all FMUs on a landscape level (including all CLC patches) and a class level (the land cover polygons were classified according to their land cover characteristics and their level of hemeroby). We determined the Spearman’s correlations to reveal the statistical connections between the landscape metric parameters and the NCI values. All of the investigated area-weighted landscape indices: Main Patch Size, (MPS), Main Fractal Dimension Index, (MFDI), Total Edge (TE), Main Shape Index (MSI) and Number of Shape Characteristic Points (NSCP) on the landscape level showed a significant statistical connection with the NCI, but the sign of its correlation with the NCI contrasted with the findings from previous studies on a larger scale. Our study shows that scale has a strong impact on the sign of the correlation between the naturalness of the vegetation and the landscape structure. On a class level, particularly the shape-related landscape indices of the “Forest and semi-natural areas” showed statistically significant correlations with the NCI. The correlation strongly depended on the method of classification of the CLC polygons. Furthermore, the spatial pattern of the land-cover-type-based CLC polygon categories showed higher correlation values with the NCI than CLC polygon classes, which were categorized according to their hemeroby state. These results show that although the sign of the spatial pattern change in the main land cover classes is scale-dependent, they can be used to estimate the increase or decrease in the naturalness of the vegetation better than the spatial changes of the hemeroby-level-based landscape pattern. We can predict the change in the naturalness of vegetation based on the spatial changes in the land cover pattern.     

Satellite observation to assess dengue risk due to Aedes aegypti and Aedes albopictus in a subtropical city of Argentina

Earth observation environmental features measured through remote sensing and models of vector mosquitoes species Aedes aegypti and Ae. albopictus provide an advancement with regards to dengue risk in urban environments of subtropical areas of Argentina. The authors aim to estimate the effect of landscape coverage and spectral indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Water Index [NDWI] and Normalized Difference Built-up Index [NDBI]) on the larvae abundance of Ae. aegypti and Ae. albopictus in Eldorado, Misiones, Argentina using remote satellite sensors. Larvae of these species were collected monthly (June 2016 to April 2018), in four environments: tire repair shops, cemeteries, dwellings and an urban natural park. The proportion of landscape coverage (water, urban areas, bare soil, low vegetation and high vegetation) was determined from the supervised classification of Sentinel-2 images and spectral indices, calculated. The authors developed spatial models of both vector species by generalized linear mixed models. The model's results showed that Ae. aegypti larvae abundance was better modelled by NDVI minimum values, NDBI maximum values and the interaction between them. For Ae. albopictus proportion of bare soil, low vegetation and the interaction between both variables explained better the abundance.     

Seasonally different response of photosynthetic activity to daytime and night‐time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night‐time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day‐ vs. night‐time temperatures. For instance, while higher daytime temperature (T_max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T_max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10⁶ km²) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T_max, increases in T_max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night‐time temperature (T_min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day‐ and night‐time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation‐climate models.     

Quantitative comparison of the diversity of landscapes with actual vs. potential natural vegetation

Abstract. In the past 20 years, several metrics have been developed to quantify various aspects of landscape structure and diversity in space and time, and most have been tested on grid‐based thematic maps. Once landscape patterns have been quantified, their effects on ecological functions can be explained if the expected pattern in the absence of specific processes is known. This type of expected pattern has been termed a neutral landscape model. In the landscape‐ecological literature, researchers traditionally adopt random and fractal computer‐generated neutral landscape models to verify the expected relationship between a given ecological process and landscape spatial heterogeneity. Conversely, little attention has been devoted to distribution patterns of potential natural vegetation (PNV) as an ecological baseline for the evaluation of pattern‐process interactions at the landscape scale. As an application for demonstration, we propose a neutral model based on PNV as a possible reference for a quantitative comparison with actual vegetation (AC V) distribution. Within this context, we introduce an evenness‐like index termed ‘actual‐to‐potential entropy ratio’ (H_A/P = H_ACV/H_PNV, where H is Shannon's entropy). Results show that, despite the hypothetical character of most PNV maps, the use of PNV distribution as a baseline for a quantitative comparison with ACV distribution may represent a first step towards a general model for the evaluation of the effects of disturbance on vegetation patterns and diversity.     

Contrasting habitat use of morphologically similar bat species with differing conservation status in south‐eastern Australia

The east‐coast free‐tailed bat Mormopterus norfolkensis Gray, 1839 is a threatened insectivorous bat that is poorly known and as such conservation management strategies are only broadly prescribed. Insectivorous bats that use human‐modified landscapes are often adapted to foraging in open microhabitats. However, few studies have explored whether open‐adapted bats select landscapes with more of these microhabitat features. We compared three morphologically similar and sympatric, molossid bats (genus Mormopterus) with different conservation status in terms of their association with vegetation, climate, landform and land‐use attributes at landscape and local habitat element scales. We predicted that these species would use similar landscape types, with semi‐cleared and low density urban landscapes used more than forested and heavily cleared landscapes. Additionally, we explored which environmental variables best explained the occurrence of each species by constructing post‐hoc models and habitat suitability maps. Contrary to predictions, we found that the three species varied in their habitat use with no one landscape type used more extensively than other types. Overall, M. norfolkensis was more likely to occur in low‐lying, non‐urban, riparian habitats with little vegetation cover. Mormopterus species 2 occupied similar habitats, but was more tolerant of urban landscapes. In contrast, Mormopterus species 4 occurred more often in cleared than forested landscapes, particularly dry landscapes with little vegetation cover. The extensive use of coastal floodplains by the threatened M. norfolkensis is significant because these habitats are under increasing pressure from human land‐uses and the predicted increase in urbanization is likely to further reduce the amount of suitable habitat.     

Modeling landscape patterns of understory tree regeneration in the Pacific Northwest,USA

Abstract. Vegetation maps serve as the basis for spatial analysis of forest ecosystems and provide initial information for simulations of forest landscape change. Because of the limitations of current remote sensing technology, it is not possible to directly measure forest understory attributes across large spatial extents. Instead we used a predictive vegetation mapping approach to model Tsuga heterophylla and Picea sitchensis seedling patterns in a 3900‐ha landscape in the Oregon Coast Range, USA, as a function of Landsat TM imagery, aerial photographs, digital elevation models, and stream maps. Because the models explained only moderate amounts of variability (R² values of 0.24–0.56), we interpreted the predicted patterns as qualitative spatial trends rather than precise maps. P. sitchensis seedling patterns were tightly linked to the riparian network, with highest densities in coastal riparian areas. T. heterophylla seedlings exhibited complex patterns related to topography and overstory forest cover, and were also spatially clustered around patches of old‐growth forest. We hypothesize that the old growth served as refugia for this fire‐sensitive species following wildfires in the late 19th and early 20th centuries. Low levels of T. heterophylla regeneration in hardwood‐dominated forests suggest that these patches may succeed to shrublands rather than to conifer forest. Predictive models of seedling patterns could be developed for other landscapes where georeferenced inventory plots, remote sensing data, digital elevation models, and climate maps are available.     

Transition zones between vegetation patches in a heterogeneous Arctic landscape: how plant growth and photosynthesis change with abundance at small scales

Arctic vegetation is often highly heterogeneous, consisting of mosaics of vegetation patches. Vegetation transition zones at the boundaries between patches can therefore make up a significant proportion of the landscape, yet performance of plants in transition zones, compared with their main patches, has not been previously investigated. Not only does this limit our understanding of plant productivity in highly heterogeneous landscapes, this knowledge is also needed to improve our understanding of the controls on Arctic ecosystem productivity, and improve modelling uncertainty in estimates of landscape C fluxes. We investigated changes in annual growth and photosynthetic capacity (A _max) of two widely distributed dwarf shrubs (Empetrum hermaphroditum and Vaccinium uliginosum) in these species’ own patches where they dominate, in transition zones at their patch edges and vegetation beyond these in vegetation where the species had lowest abundance. Maximum shoot growth occurred not in the study species’ own patches but in patches where both species mixed with a taller dwarf shrub Betula nana. Here shoot growth was 23 and 25% higher for E. hermaphroditum and V. uliginosum, respectively, compared to within their own patches. However, A _max was maintained at similar levels at all sites, with a slight tendency toward increased rates in vegetation towards more nutrient-rich, wetter areas compared to the species’ own patches, despite these more nutrient-rich areas having greater shading. There was only a very minor tendency towards decreased A _max in vegetation towards drier, more exposed areas compared to the species’ own patches. We show that, despite large changes in abundance and growth, A _max is not highly variable at small scales, meaning that variation in A _max is unlikely to be a large source of error when modelling whole-landscape C fluxes using measurements made within patches.     

Naturally Saline Boreal Communities as Models for Reclamation of Saline Oil Sand Tailings

Reclaimed landscapes after oil sands mining have saline soils; yet, they are required to have similar biodiversity and productivity as the predisturbance nonsaline landscape. Given that many species in the boreal forest are not tolerant of salinity, we studied the effects of soil salinity on plant communities in natural saline landscapes to understand potential plant responses during the reclamation process. Vegetation–soil relationships were measured along transects from flooded wetlands to upland forest vegetation in strongly saline, slightly saline, nonsaline, and reclaimed boreal landscapes. In strongly saline landscapes, surface soil salinity was high (>10 dS/m) in flooded, wet‐meadow, and dry‐meadow vegetation zones as compared to slightly saline (<5 dS/m) and nonsaline (<2 dS/m) landscapes. Plant communities in these vegetation zones were quite different from nonsaline boreal landscapes and were dominated by halophytes common to saline habitats of the Great Plains. In the shrub and forest vegetation zones, surface soil salinity was similar between saline and nonsaline landscapes, resulting in similar plant communities. In strongly saline landscapes, soils remained saline at depth through the shrub and forest vegetation zones (>10 dS/m), suggesting that forest vegetation can establish over saline soils as long as the salts are below the rooting zone. The reclaimed landscape was intermediate between slightly saline and nonsaline landscapes in terms of soil salinity but more similar to nonsaline habitats with respect to species composition. Results from this study suggest it may be unrealistic to expect that plant communities similar to those found on the predisturbance landscape can be established on all reclaimed landscapes after oil sands mining.     

Different responses of attic-dwelling bat species to landscape naturalness

Although the general role of bats and the tolerance of many species to urbanized areas is well known, the relationship between urban roosts and their surrounding landscapes having different degrees of naturalness still requires our attention, mainly in species that are the most adapted to human-made structures. We used extensive data from attic-dwelling bat surveillance conducted throughout Slovakia to assess species responses to the degree of naturalness of the landscape surrounding their anthropogenic roosts. Using generalized linear mixed-effects modelling, we found that some bats established their nursery colonies in either a habitat with a higher proportion of forests mostly at sub-mountain/mountain altitudes (R. hipposideros, P. auritus, M. emarginatus), or they preferred lowlands with a predominance of arable land (E. serotinus, P. austriacus). Furthermore, higher habitat heterogeneity and the proportion of grassland were positively associated with the occurrence of P. auritus; however, negative associations with these habitat variables were found in E. serotinus. The predicted suitability of an area for bats to establish nursery colonies suggests the existence of two regions with different bat species composition in the study area: a region of the Pannonian Lowlands and a less urbanized mountain region of the Carpathian Mountains. Our study thus showed that landscape naturalness is a determining factor for roost-site selection by bats preferring anthropogenic roosts; however, some bat species did not express specific preferences according to the tested environmental variables, and other ecological traits in the evaluated species should be considered.     

Relationship between small-scale structural variability and simulated vegetation productivity across a regional moisture gradient in southern Africa

The observed variability in vegetation structure within landscapes was used as the basis for model estimates of the range of annual productivity of landscape patches at four sites along a moisture gradient in southern Africa ranging from 879 to 365 mm mean annual rainfall. Principal components of patch‐scale variability in leaf area, woody biomass and vertical leaf profiles were derived from intensive characterization of the small‐scale spatial structure of woody vegetation at each site. For each site, the mean and extremes of the principal component distribution parameterized an ecophysiology model of vegetation productivity. Vegetation was most heterogeneous at intermediate locations along the rainfall gradient. Variability in vegetation structure led to a range of annual productivity within one site (600 mm) that accounted for 68% of the total range in mean productivity across all sites. Patch‐scale estimates of tree productivity were found to be primarily correlated to annual rainfall (r²=0.66, P=0.001) and not woody leaf area (r²=0.01, P=0.75), while grass productivity was found to be related to values of woody leaf area (r²=0.77, P<0.001) and not annual rainfall (r²=0.11, P=0.29). This result indicates that life‐form interactions have a significant role in controlling vegetation productivity across the rainfall gradient. The findings of this study emphasize the importance of considering heterogeneity rather than mean structure when modeling productivity, particularly when considering dynamic vegetation structure, where differences between landscape patches may not be well represented in the mean structure.     

A new technique for estimating rates of carboxylation and electron transport in leaves of C3 plants for use in dynamic global vegetation models

The possible responses of the terrestrial biosphere to future CO₂ increases and associated climatic change are being investigated using dynamic global vegetation models (DG VMs) which include the Farquhar et al. (1980) biochemical model of leaf assimilation as the primary means of carbon capture. This model requires representative values of the maximum rates of Rubisco activity, V_max, and electron transport, J_max, for different vegetation types when applied at the global scale. Here, we describe an approach for calculating these values based on measurements of the maximum rate of leaf photosynthesis (A_max) ¹³C discrimination. The approach is tested and validated by comparison with measurements of Rubisco activity assayed directly on wild-type and transgenic Nicotiana tabacum (tobacco) plants with altered Rubisco activity grown under ambient and elevated CO₂ mole fractions with high and low N-supply. V_max and J_max values are reported for 18 different vegetation types with global coverage. Both variables were linearly related reinforcing the idea of optimal allocation of resources to photosynthesis (light harvesting vs. Rubisco) at the global scale. The reported figures should be of value to the further development of vegetation and ecosystem models employing mechanistic DGVMs.     

Net ecosystem exchange of CO2 with rapidly changing high Arctic landscapes

High Arctic landscapes are expansive and changing rapidly. However, our understanding of their functional responses and potential to mitigate or enhance anthropogenic climate change is limited by few measurements. We collected eddy covariance measurements to quantify the net ecosystem exchange (NEE) of CO₂ with polar semidesert and meadow wetland landscapes at the highest latitude location measured to date (82°N). We coupled these rare data with ground and satellite vegetation production measurements (Normalized Difference Vegetation Index; NDVI) to evaluate the effectiveness of upscaling local to regional NEE. During the growing season, the dry polar semidesert landscape was a near‐zero sink of atmospheric CO₂ (NEE: ?0.3 ± 13.5 g C m^?2). A nearby meadow wetland accumulated over 300 times more carbon (NEE: ?79.3 ± 20.0 g C m^?2) than the polar semidesert landscape, and was similar to meadow wetland NEE at much more southerly latitudes. Polar semidesert NEE was most influenced by moisture, with wetter surface soils resulting in greater soil respiration and CO₂ emissions. At the meadow wetland, soil heating enhanced plant growth, which in turn increased CO₂ uptake. Our upscaling assessment found that polar semidesert NDVI measured on‐site was low (mean: 0.120–0.157) and similar to satellite measurements (mean: 0.155–0.163). However, weak plant growth resulted in poor satellite NDVI–NEE relationships and created challenges for remotely detecting changes in the cycling of carbon on the polar semidesert landscape. The meadow wetland appeared more suitable to assess plant production and NEE via remote sensing; however, high Arctic wetland extent is constrained by topography to small areas that may be difficult to resolve with large satellite pixels. We predict that until summer precipitation and humidity increases enough to offset poor soil moisture retention, climate‐related changes to productivity on polar semideserts may be restricted.     

A vegetation-based method to map climatic variation in the arctic–boreal transition area of Finnmark, north-easternmost Norway

Aim To develop a new method for bioclimate mapping where the vegetation layer is the main source of climate information. Location The study area includes four subareas, all situated on the Varangerhalvøya peninsula in Finnmark, north‐easternmost Norway (70–71° N). The four subareas were chosen to represent most of the climatic, topographic, geomorphologic and botanic diversity along the arctic–boreal gradient in the area. The four meteorological stations in the area show a climatic gradient with mean July temperature ranging from 10.1 to 12.3 °C. Methods The new vegetation‐based method is based on the fact that most plant species and plant communities both in the Arctic and adjacent areas have a distribution pattern limited by temperature to some extent. The vegetation is mapped using Landsat TM data and a contextual correction process in a geographic information system. The mapped vegetation units are defined as temperature indicators based on their total distribution patterns and the temperature indicator value of their high frequency and dominant species. The indicator value and degree of cover of all thermophilous vegetation units, within each 500 × 500 m study unit, are combined in a Vegetation‐based Index of Thermophily, VI_tm. This new vegetation‐based method is based on the same basic idea as a recently published floristic‐based method for calculating a Floristic‐based Index of Thermophily, FI_tm. The VI_tm values are tested by comparison with the FI_tm values, and temperature data collected in the field during two growing seasons, and the differences are interpreted ecologically. Results Twenty‐one of the mapped vegetation units were defined as thermophilous and categorized in five groups of temperature indicators. The VI_tm values showed a strong positive linear relationship with the temperatures measured during the years 2001 and 2002, with r² values of 0.79 and 0.85, respectively. The VI_tm values show a high linear relationship (r² = 0.76) with the 71 study units where the FI_tm values were calculated. As interpreted from the relationship with temperature measurements and FI_tm values, the vegetation‐based method seems to work at a broad range of ecological conditions, with very dry, acidic sites being the most important exception. The VI_tm values are related to growing degree‐days of a normal year, and the four subareas are mapped, showing a diversity of 13 bioclimatic classes. The birch forest line is estimated to occur at about 980 °C‐days. The results show climatic gradients with temperatures increasing from the cold coast towards the interior, from wind‐exposed convex hills towards wind‐protected valleys, and from mountain plateaux towards south‐facing lowlands. The north‐easternmost study site at the coast is positioned within the arctic shrub tundra zone. Main conclusions The vegetation‐based method shows a strong positive correlation both with measured temperatures and the floristic‐based method within a broad range of different ecological conditions. The vegetation‐based method has the potential for bioclimatic mapping of large areas in a cost‐effective way. The floristic‐based method has higher accuracy and is more flexible than the vegetation‐based method, and the two methods seem to complement each other.     

Photosynthesis of ground vegetation in different aged pine forests: Effect of environmental factors predicted with a process‐based model

Question: How do stand age and environmental factors affect the species‐specific photosynthesis of ground vegetation? Location: Five different aged pine forests in Southern Finland. Methods: We measured photosynthesis of common species of ground vegetation during the growing season of 2006. Results: The measured vascular species, especially those with annual leaves, had a clear seasonal cycle in their measured photosynthetic activity (P_maxⁱ). A simple model that uses site‐specific temperature history, soil moisture and recent frost as input data was able to predict the changes in photosynthetic activity in dwarf shrubs with perennial leaves. The P_maxⁱ values of mosses did not have a clear seasonal cycle, but low values occurred after rain‐free periods and high values after precipitation. We modified the model for mosses and included temporary rain events. The model was able to predict most of the large changes in P_maxⁱ of mosses resulting from varying weather events but there was still some uncertainty, which was probably due to difficulties in measuring fluxes over a moss population. Conclusions: Temperature history, recent frosts and soil moisture determine the changes in P_maxⁱ of dwarf shrubs with perennial leaves. The P_maxⁱ of mosses depends mostly on recent precipitation.     

Gross primary productivity and transpiration flux of the Australian vegetation from 1788 to 1988 AD: effects of CO2 and land use change

We present a novel approach to estimating the transpiration flux and gross primary productivity (GPP) from Normalized Difference Vegetation Index, leaf functional types, and readily available climate data. We use this approach to explore the impact of variations in the concentration of carbon dioxide in the atmosphere ([CO₂]) and consequent predicted changes in vegetation cover, on the transpiration flux and GPP. There was a near 1 : 1 relationship between GPP estimated with this transpiration flux approach and that estimated using a radiation‐use efficiency (RUE) approach. Model estimates are presented for the Australian continent under three vegetation–[CO₂] scenarios: the present vegetation and hypothetical ‘natural’ vegetation cover with atmospheric CO₂ concentration ([CO₂]) of 350 μmol mol^?1 (pveg₃₅₀ and nveg₃₅₀), and for the ‘natural’ vegetation with [CO₂] 280 μmol mol^?1 (nveg₂₈₀). Estimated continental GPP is 6.5, 6.3 and 4.3 Gt C yr^?1 for pveg₃₅₀, nveg₃₅₀ and nveg₂₈₀, respectively_. The corresponding transpiration fluxes are 232, 224 and 190 mm H₂O yr^?1. The contribution of the raingreen and evergreen components of the canopy to these fluxes are also estimated.     

The first pollen diagram from the Hoher Fläming, Brandenburg (Germany)

A 72 cm peat core from a spring mire reveals 3300 years of vegetation history in the Hoher Fläming, a landscape formed by the penultimate glaciation in southeastern Brandenburg. Primeval beech-oak forest dominated from a.d. 550 to 1200, prior to local forest clearance. Existing maps showing the natural and potential natural vegetation as pine and oak need to be revised. Local woodland cutting in the 12th century and grassland use since the 15th century affected the development of the helokrene (spring-fed) mire deposits from alder carr to mesotrophic fen vegetation and then to the present-day Sphagnum fallax-Juncus acutiflorus wet meadows. Vegetation and mire history link together the Hoher Fläming and adjacent landscapes on a northwest-southeast gradient of suboceanic to subcontinental climate. Moreover it represents a geographical and altitudinal transition of lowland and hill vegetation from 30 to 200 m a.s.l. to the montane belts of the palynologically well investigated Harz mountains. However, regarding some trees and herbs, the Hoher Fläming does not belong to the Hercynian region and type of vegetation.     

Vegetation and landscape connectivity control wildfire intervals in unmanaged semi‐arid shrublands and woodlands in Australia

Aim The aim of this study was to determine how spatial variation in vegetation type and landscape connectivity influence fire intervals in a semi‐arid landscape with low relief and complex mosaics of woodland and shrubland vegetation. Location Our study focused on a 15,500‐km² area of relatively undisturbed and unmanaged land in south‐western Australia, referred to as the Lake Johnston region. Methods We modelled fire‐interval data from a 67‐year (1940–2006) digital fire history database using a two‐parameter Weibull function, and tested for the effects of vegetation type and landscape connectivity on estimates of the length of fire intervals (Weibull parameter b) and the dependence of fire intervals on fuel age (Weibull parameter c). Results Vegetation type and landscape connectivity significantly influenced fire interval probability distributions. Fire intervals in shrublands (dense low shrub assemblage) were typically shorter (b = 46 years) and more dependent on fuel age (c = 2.33) than most other vegetation types, while fire intervals in open eucalypt woodlands were much longer (b = 405 years) and were less dependent on fuel age (c = 1.36) than in shrub‐dominated vegetation types. Areas adjacent to or surrounded by salt lakes burnt less frequently (b = 319 years) and fire intervals were less dependent on fuel age (c = 1.48) compared with more exposed areas (e.g. b < 101 years, c > 1.68). Fire intervals in thickets (dense tall shrub assemblage) were longer (b = 101 years) than would be expected from fuel loads, most likely because they were protected from fire by surrounding fuel‐limited woodlands. Main conclusions Fire intervals in south‐western Australia are strongly influenced by spatial variation in vegetation (fuel structure) and landscape connectivity. The importance of fuel structure as a control of fire intervals in south‐western Australia contrasts with other landscapes, where topographical gradients or climatic influences may override the effects of underlying vegetation. We found that, regardless of low relief, topographical features such as large salt lake systems limited the connectivity and spread of fire among landscape units in an analogous manner to lakes or mountainous features elsewhere.     

Accuracy of the AVHRR vegetation index as a predictor of biomass,primary productivity and net CO2 flux

The Normalized Difference Vegetation Index (NDVI) or greenness index, based on the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA-7 satellite, has been widely interpreted as a measure of regional to global vegetation patterns. This study provides the first rigorous, quantitative evaluation of global relationships between the NDVI and geographically representative vegetation data-bases, including field metabolic measurements and carbon-balance results from global simulation models. Geographic reliability of the NDVI is judged by comparing NDVI values for different surface types with a general global trend and by statistical analysis of relationships to biomass amounts, net and gross primary productivity, and actual evapotranspiration. NDVI data appear to be relatively reliable predictors of primary productivity except in areas of complex terrain, for seasonal values at high latitudes, and in extreme deserts. The strength of the NDVI-productivity relationship seems comparable to that of earlier climate-based productivity models. Little consistent relationship was found, across different vegetation types, between NDVI and biomass amounts or net biospheric CO₂ flux.Abbreviations AET= Actual Evapotranspiration - AVHRR= Advanced Very High Resolution Radiometer - GPP= Gross Primary Production - GVI= Global Vegetation Index - NDVI= Normalized Difference Vegetation Index - NPP= Net Primary Production