A simulated map of the potential natural forest vegetation of Switzerland

Using empirical data (ca. 7500 phytosociological releves), a simple, probabilistic ‘vegetation-site’ model was developed, to simulate geographical distribution of 71 forest community types, representing the potential natural vegetation (PNV) of Switzerland. The model was interfaced to a geographic information system (GIS) and used to generate a numerical vegetation map, on the basis of digital maps of 12 environmental variables including climatic conditions (temperature and precipitation), topography (elevation, slope, aspect), and soil parameters (soil pH and physical soil parameters). The predicted distribution of forest communities was compared with several vegetation maps, prepared for some subregions of Switzerland by means of traditional field methods. Similarity ranged from 50 to 80 %, depending on the community type, level of vegetational hierarchy and the geographical region. The current resolution and accuracy of the simulated vegetation map allows us to study the vegetational patterns on the level of the entire country or its major geographical and climatic regions. The simulated vegetation map is potentially an important tool in ecological risk assessment studies concerning the possible impacts of climate change on the ecological potential of forest sites and biological diversity of forest communities.     

Vegetation and environmental patterns on soils derived from Hawkesbury Sandstone and Narrabeen substrata in Ku-ring-gai Chase National Park,New South Wales

Abstract The vegetation patterns in the Central Coast region of New South Wales have been extensively studied with respect to single environmental variables, particularly soil nutrients. However, few data are available on the effects of multiple environmental variables. This study examines the relationships between vegetation and multiple environmental variables in natural vegetation on two underlying rock types, Hawkesbury Sandstone and Narrabeen Group shales and sandstones, in Ku-ring-gai Chase National Park, Sydney. Floristic composition and 17 environmental factors were characterized using duplicate 500 m2 quadrats from 50 sites representing a wide range of vegetation types. The patterns in vegetation and environmental factors were examined through multivariate analyses: indicator species analysis was used to provide an objective classification of plant community types, and the relationships between vegetation and environmental factors within the two soil types were examined through indirect and direct gradient analyses. Eleven plant communities were identified, which showed strong agreement with previous studies. The measured environmental factors showed strong correlations with vegetation patterns: within both soil types, the measured environmental variables explained approximately 32–35% of the variation in vegetation. No single measured environmental variable adequately described the observed gradients in vegetation; rather, vegetation gradients showed strong correlations with complex environmental gradients. These complex environmental gradients included nutrient, moisture, and soil physical and site variables. These results suggest that a simple ‘nutrient’ hypothesis regarding vegetation patterns in the Central Coast region is inadequate to explain variation in vegetation within soil types.     

Mountain summer farms in Røldal,western Norway –; vegetation classification and patterns in species turnover and richness

This paper discusses vegetation types and diversity patterns in relation to environment and land-use at summer farms, a characteristic cultural landscape in the Norwegian mountains. Floristic data (189 taxa) were collected in 130 4-m² sample plots within 12 summer farms in Røldal, western Norway. The study was designed to sample as fully as possible the range of floristic, environmental, and land-use conditions. Vegetation types delimited by two-way indicator species analysis were consistent with results from earlier phytosociological studies. Detrended correspondence analysis and canonical correspondence analysis show that rather than being distinct vegetation types, the major floristic variation is structured along a spatial gradient from summer farm to the surrounding heathland vegetation. Species richness (alpha diversity) was modelled against environmental variables by generalized linear modelling and compositional turnover (beta diversity) by canonical correspondence analysis. Most environmental factors made significant contributions, but the spatial distance-to-farm gradient was the best predictor of both species richness and turnover. While summer farms reduce mean species richness at the plot scale, the compositional heterogeneity of the upland landscapes is increased, thereby creating ‘ecological room’ for additional vegetation types and species. Within an overall similarity across scales, soil variables (pH, base saturation, LOI, phosphate and nitrogen) differed considerably in their explanatory power for richness and turnover. A difference between ‘productivity limiting’ factors and ‘environmental sieves’ is proposed as an explanation. Species turnover with altitude is relatively low in grasslands as compared to heaths.     

Changes in predictor influence with time and with vegetation type identity in a post-abandonment situation

Variation in the explanatory potential of separate variable groups describing past vegetation patterns and/or abiotic environment were investigated using data from two points in time for three vegetation types, which are variants of the steppe grassland component of the forest steppe biome. First, we compared the predictive power of environmental variables assessed by the performance of generalised linear models (GLMs) explaining the distribution of three vegetation types in 1988 and 2002. Second, we fitted models based on conceptual hypotheses to explain vegetation distribution in 2002. Specifically, we wanted to examine, whether (i) current abiotic topo-environment, (ii) past neighbourhood configuration, or (iii) historical vegetation patterns or a combination of these determine best the current distribution of vegetation types. We developed basic predictor sets for each hypothesis, and using GLMs we tested to what degree these predictor sets were capable of explaining the currently observed patterns of individual vegetation types. We compared model accuracy by AUC and TSS values. Predictive performance of models changed both with time and with vegetation type. The analyses of changes over time showed that two of the three vegetation types had come closer to an equilibrium with abiotic conditions, while the third had moved farther away from equilibrium. Knowledge of past conditions was sufficient to predict the distribution of one of the three investigated vegetation types alone, thus no topo-environmental predictors were needed to successfully predict this type. The other two vegetation types were best explained by current topo-environmental predictors. We conclude that historical conditions clearly improve predictive models, though there may be variation in their contribution to models of different vegetation types and this may depend on how far vegetation types are from an equilibrium state.     

Effects of Vegetation Traits on Habitat Preferences of Frugivorous Birds in Atlantic Rain Forest

Structural and floristic components of vegetation and fruit production were examined to evaluate the relative importance of each vegetation aspect on patterns of habitat use and to determine whether differences in degree of frugivory would affect sensitivity of birds to vegetation components. Abundances of 12 bird species were quantified in four different habitat types in the Southeastern Atlantic rain forest of Brazil using captures with mist nets. Structural and floristic traits and fruit production were sampled within plots along the mist net lines. Best explanations for the variation in species abundance were obtained by different combinations of the vegetation components (generalized linear models, Akaike information criterion; R ² mean values = 0.48, Δ AIC c = 0). Although each species had a particular preference for some vegetation variables, floristic components stood out in those relationships, generating models with a stronger explanatory capacity ( R ² > 0.40) and higher levels of empirical support (Δ AIC c = minimum values). The variation in bird sensitivities to the floristic component was associated with bird dependence on a fruit diet: there was a correlation between the explanatory capacity of models built with only floristic composition and a species' degree of frugivory (Spearman rank correlation, r = 0.66, P = 0.04), indicating that floristics had a higher effect in more frugivorous birds. For the other vegetation components, there was no clear pattern with statistical support. These results indicate that sensitivities of bird species to vegetation aspects are associated with their dependence on a fruit diet.     

Firescape ecology: how topography determines the contrasting distribution of fire and rain forest in the south‐west of the Tasmanian Wilderness World Heritage Area

Aim To test the hypothesis that ‘islands’ of fire‐sensitive rain forest are restricted to topographic fire refugia and investigate the role of topography–fire interactions in fire‐mediated alternative stable state models. Location A vegetation mosaic of moorland, sclerophyll scrub, wet sclerophyll eucalypt forest and rain forest in the rugged, fire‐prone landscapes of south‐west Tasmania, Australia. Methods We used geospatial statistics to: (1) identify the topographic determinants of rain forest distribution on nutrient‐poor substrates, and (2) identify the vegetation and topographic variables that are important in controlling the spatial pattern of a series of very large fires (> 40,000 ha) that were mapped using Landsat Thematic Mapper (TM) satellite imagery. Results Rain forest was more likely to be found in valleys and on steep south‐facing slopes. Fires typically burned within highly flammable treeless moorland and stopped on boundaries with less flammable surrounding vegetation types such as wet sclerophyll forest and rain forest. Controlling for the effect of vegetation, fires were most likely to burn on flats, ridges and steep north‐facing slopes and least likely to burn in valleys and on steep south‐facing slopes. These results suggest an antagonism between fire and rain forest, in which rain forest preferentially occupies parts of the landscape where fire is least likely to burn. Main conclusions The distribution of rain forest on nutrient‐poor substrates was clearly related to parts of the landscape that are protected from fire (i.e. topographic fire refugia). The relative flammability of vegetation types at the landscape scale offers support to the proposed hierarchy of fire frequencies (moorland > scrub > wet sclerophyll > rain forest) that underpins the ecological models proposed for the region. The interaction between fire occurrence and a range of topographic variables suggests that topography plays an important role in mediating the fire–vegetation feedbacks thought to maintain vegetation mosaics in south‐west Tasmania. We suggest that these fire–topography interactions should be included in models of fire‐mediated alternative stable vegetation states in other fire‐prone landscapes.     

Legume diversity patterns in west central Africa: influence of species biology on distribution models

Objectives

Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning.

Methodology

Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types.

Results/Conclusions

Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused.     

Ecosystem CO2 production during winter in a Swedish subarctic region: the relative importance of climate and vegetation type

General circulation models consistently predict that regional warming will be most rapid in the Arctic, that this warming will be predominantly in the winter season, and that it will often be accompanied by increasing snowfall. Paradoxically, despite the strong cold season emphasis in these predictions, we know relatively little about the plot and landscape‐level controls on tundra biogeochemical cycling in wintertime as compared to summertime. We investigated the relative influence of vegetation type and climate on CO₂ production rates and total wintertime CO₂ release in the Scandinavian subarctic. Ecosystem respiration rates and a wide range of associated environmental and substrate pool size variables were measured in the two most common vegetation types of the region (birch understorey and heath tundra) at four paired sites along a 50 km transect through a strong snow depth gradient in northern Sweden. Both climate and vegetation type were strong interactive controls on ecosystem CO₂ production rates during winter. Of all variables tested, soil temperature explained by far the largest amount of variation in respiration rates (41–75%). Our results indicate that vegetation type only exerted an influence on respiration when snow depth was below a certain threshold (～1 m). Thus, tall vegetation that enhanced snow accumulation within that threshold resulted in more effective thermal insulation from severe air temperatures, thereby significantly increasing respiratory activity. At the end of winter, within several days of snowmelt, gross ecosystem photosynthesis rates were of a similar magnitude to ecosystem respiration, resulting in significant net carbon gain in some instances. Finally, climate and vegetation type were also strong interactive controls on total wintertime respiration, suggesting that spatial variations in maximum snowdepth may be a primary determinant of regional patterns of wintertime CO₂ release. Together, our results have important implications for predictions of how the distribution of tundra vegetation types and the carbon balances of arctic ecosystems will respond to climate change during winter because they indicate a threshold (～1 m) above which there would be little effect of increased snow accumulation on wintertime biogeochemical cycling.     

Elevational gradient and vegetation‐environmental relationships in the central Hyrcanian forests of northern Iran

Tertiary‐relict Hyrcanian (Caspian) forest along the shores of the southern Caspian Sea is a center of biodiversity. Still, there is little information on plant diversity patterns in this area. This study evaluated plant diversity, variation in life forms, and geographical distribution of the zonal vegetation types and their relationships with environmental variables, in the educational and experimental forest of Kheyrudkenar, an important protected area in the central Hyrcanian forest of northern Iran. For this purpose, 226 vegetation plots of 400 m² were laid out along two altitudinal transects from the lowlands (100 m a.s.l.) to the timberline (2000 m a.s.l.). Four vegetation types were identified using modified TWINSPAN, indirect and direct gradient analyses. Species‐related (species diversity indices, life form and phytogeographical elements) and environmental variables (climate, topographic and soil variables) were calculated and subjected to one‐way ANOVA among the vegetation types. Both constrained (CCA) and unconstrained (DCA) ordination analyses showed an almost identical variation of the floristic composition along their axes and demonstrated that there are two main gradients in the Hyrcanian forest. Elevation together with annual precipitation and mean annual temperature were the most important factors controlling the floristic composition in the area. Topographic features such as slope inclination and heat index were found to be important within an elevation zone/vegetation type. Soil physical and chemical properties were of secondary importance for the separation of the vegetation types. This knowledge will be useful for forest management and conservation practices in the Hyrcanian area with its distinct and unique flora and vegetation.     

Environmental variation and moose Alces alces density as determinants of spatio-temporal heterogeneity in browsing

Understanding temporal variation in habitat selection and browsing intensity by large herbivores is fundamental because of their large impact on the ecosystems. I studied the annual variation in winter browsing pressure on young trees and habitat selection by moose Alces alces over a ten year period. Specifically, the relationships between browsing pressure on Scots pine Pinus sylvestris and two birch species ( Betula ssp.) and three explanatory variables – 1) availability of forage, 2) moose density (estimated by pellet group counts) and 3) snow cover was studied. At a larger spatial scale (forest stand level) the relationship between moose habitat selection between three different habitat types (forest <30 yr, forest>30 yr and mire) and two explanatory variables, 1) snow condition and 2) moose density, were studied. Browsing pressure on Scots pine, the dominating food plant, was related to forage availability, moose density and snow condition. No significant relationships between any of the three explanatory variables and browsing pressure on the two birch species were found. Moose selection for certain habitats varied between years and was affected by number of days with >0.10 m of snow.
Habitat selection was not significantly related to moose density and the relationship between overall moose density and habitat specific moose densities was proportional within the studied density range. These findings have implications for understanding varying browsing patterns – and will affect both the ability to predict herbivores' effect on the forest ecosystem. A snow dependent browsing pattern also indicates that one can expect a long term decrease in browsing pressure on the tree and shrub layer as a consequence of the ongoing large-scale climate change.     

Contrasting effects of mosaic structure on alpha and beta diversity of bird assemblages in a human‐modified landscape

Habitat loss and fragmentation are key processes causing biodiversity loss in human‐modified landscapes. Knowledge of these processes has largely been derived from measuring biodiversity at the scale of ‘within‐habitat’ fragments with the surrounding landscape considered as matrix. Yet, the loss of variation in species assemblages ‘among’ habitat fragments (landscape‐scale) may be as important a driver of biodiversity loss as the loss of diversity ‘within’ habitat fragments (local‐scale). We tested the hypothesis that heterogeneity in vegetation cover is important for maintaining alpha and beta diversity in human‐modified landscapes. We surveyed bird assemblages in eighty 300‐m‐long transects nested within twenty 1‐km² vegetation ‘mosaics’, with mosaics assigned to four categories defined by the cover extent and configuration of native eucalypt forest and exotic pine plantation. We examined bird assemblages at two spatial scales: 1) within and among transects, and 2) within and among mosaics. Alpha diversity was the mean species diversity within‐transects or within‐mosaics and beta diversity quantified the effective number of compositionally distinct transects or mosaics. We found that within‐transect alpha diversity was highest in vegetation mosaics defined by continuous eucalypt forest, lowest in mosaics of continuous pine plantation, and at intermediate levels in mosaics containing eucalypt patches in a pine matrix. We found that eucalypt mosaics had lower beta diversity than other mosaic types when ignoring relative abundances, but had similar or higher beta diversity when weighting with species abundances. Mosaics containing both pine and eucalypt forest differed in their bird compositional variation among transects, despite sharing a similar suite of species. This configuration effect at the mosaic scale reflected differences in vegetation composition among transects. Maintaining heterogeneity in vegetation cover could help to maintain variation among bird assemblages across landscapes, thus partially offsetting local‐scale diversity losses due to fragmentation. Critical to this is the retention of remnant native vegetation.     

On the variation explained by ordination and constrained ordination axes

Abstract. Total inertia (TI), the sum of eigenvalues for all ordination axes, is often used as a measure of total variation in a data set. By use of simulated data sets, I demonstrate that lack-of-fit of data to the response model implicit in any eigenvector ordination method results in polynomial distortion ordination axes, with eigenvalues that normally contribute 30–70% to TI (depending on data set properties). The amount of compositional variation extracted on ecologically interpretable ordination axes (structure axes) is thus underestimated by the eigenvalue-to-total-inertia ratio. I recommend that the current use of total inertia as a measure of compositional variation is discontinued. Eigenvalues of structure axes can, however, be used with some caution to indicate their relative importance. I also demonstrate that when the total inertia is partitioned on different sets of explanatory variables and unexplained variation by use of (partial) constrained ordination, (35) 50–85% of the variation ‘unexplained’ by the supplied explanatory variables represents lack-of-fit of data to model. Thus, the common interpretation of ‘unexplained variation’ as random variation (‘noise’) or coenoclinal variation caused by unmeasured explanatory variables, is generally inappropriate. I recommend a change of focus from the variation-explained-to-total inertia ratio and ‘unexplained’ variation to relative amounts of variation explained by different sets of explanatory variables.     

贡嘎山海拔梯度上不同植被类型土壤甲烷氧化菌群落结构及多样性

甲烷是仅次于CO₂的第二大温室气体.森林表层土壤中甲烷好氧氧化作用是大气甲烷重要的汇,在碳循环和减缓全球变暖方面起着重要作用.研究不同植被类型土壤中甲烷氧化菌的群落结构及多样性,有助于更好地理解植被演替、人为干扰和不同土地利用背景下甲烷氧化菌群落组成和多样性变化与地上植被之间的相互关系.本研究在贡嘎山东坡海拔梯度上的4种不同植被类型中采集了92个土壤样品,利用Miseq测序技术和生物信息学方法评估了甲烷氧化菌群落组成及多样性在4种不同植被类型间的变化,并探讨了其变异的潜在原因.结果表明: 常绿阔叶林和针阔叶混交林土壤中甲烷氧化菌的群落结构较为相似,暗针叶林和灌丛草甸土壤甲烷氧化菌的群落结构较为相似.4种不同植被生态系统中,针阔叶混交林土壤中的甲烷氧化菌α多样性显著高于其他3种植被生态系统(P＜0.001),且暗针叶林和灌丛草甸土壤中甲烷氧化菌β多样性显著高于常绿阔叶林和针阔叶混交林(P＜0.001).Spearman相关分析表明,不同类型甲烷氧化菌的相对丰度对环境变化的响应模式不同.造成α多样性差异的主要因子可能是土壤总氮、电导率和土壤温度.偏Mantel检验分析和冗余分析(RDA)表明,常绿阔叶林和针阔叶混交林土壤甲烷氧化菌多样性受环境因子的影响较大,而暗针叶林和灌丛草甸土壤中甲烷氧化细菌多样性变化可能存在其他潜在的影响因素或者机制.降水可能是造成低海拔常绿阔叶林和针阔叶混交林与高海拔暗针叶林和灌丛草甸土壤甲烷氧化细菌群落结构差异的主要原因.贡嘎山海拔梯度上不同植被类型土壤中甲烷氧化菌的群落结构和多样性变化可能主要是由于土壤理化性质和气候变化综合作用的结果.     

Classification and phytogeographical differentiation of oriental beech forests in Turkey and Bulgaria

Floristic differentiation of the oriental beech (Fagus orientalis Lipsky) forests in Turkey and Bulgaria was investigated and the role of geographical and topographical factors in this differentiation was assessed. After geographical and ecological stratification of the available 922 relevés, 288 remained. Classification, by applying cluster analysis, resulted in seven vegetation units defined by species composition which represent the geographical and ecological variation of Fagus orientalis forests. DCA ordination was applied to these units by passively projecting their chorological structure, as supplementary variables. For more detailed interpretation of vegetation types with similar geographic distribution patterns, PCA was applied by passively projecting the chorological elements, life-forms and topographical factors as supplementary variables. Seven vegetation units representing the geographical and ecological variety of Fagus orientalis forests were described. Four vegetation units represent the core area of Fagus orientalis distribution on the western and middle coast of the Black Sea region (Euxine region); the remaining three types represent the distribution in the eastern Black Sea region (Colchic region), the distribution in western and southern Anatolia under the influence of the Mediterranean climate and the distribution in the transitional zone from the Euxine region to the continental parts of Inner Anatolia, respectively. The four vegetation types in Euxine region reflect the decreasing effect of Black Sea towards Inner Anatolia, as well as altitudinal differences, except the forest type representing forests on calcareous sites. The other three vegetation units represent ravine, lowland to montane and altimontane forests in Euxine region. Fagus orientalis forests could be distinguished by their floristic composition, their chorological elements and life-forms spectra, which reflect a geographical and ecological gradients.     

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

Post‐fire regeneration in alpine heathland: Does fire severity matter?

Fire severity is thought to be an important determinant of landscape patterns of post‐fire regeneration, yet there have been few studies of the effects of variation in fire severity at landscape scales on floristic diversity and composition, and none within alpine vegetation. Understanding how fire severity affects alpine vegetation is important because fire is relatively infrequent in alpine environments. Globally, alpine ecosystems are at risk from climate change, which, in addition to warming, is likely to increase the severity and frequency of fire in south‐eastern Australia. Here we examine the effects of variation in fire severity on plant diversity and vegetation composition, 5 years after the widespread fires of 2003. We used floristic data from two wide‐spread vegetation types on the Bogong High Plains: open heathland and closed heathland. Three alternative models were tested relating variation in plant community attributes (e.g. diversity, ground cover of dominant species, amount of bare ground) to variation in fire severity. The models were (i) ‘linear’, attributes vary linearly with fire severity; (ii) ‘intermediate disturbance’, attributes are highest at intermediate fire severity and lowest at both low‐ and high‐severity; and (iii) ‘null’, attributes are unaffected by fire severity. In both heathlands, there were few differences in floristic diversity, cover of dominant species and community composition, across the strong fire severity gradient. The null model was most supported in the vast majority of cases, with only limited support for either the linear and intermediate disturbance models. Our data indicate that in both heathlands, vegetation attributes in burnt vegetation were converging towards that of the unburnt state. We conclude that fire severity had little impact on post‐fire regeneration, and that both closed and open alpine heathlands are resilient to variation in fire severity during landscape scale fires.     

Modelling potential impacts of climate change on the spatial distribution of zonal forest communities in Switzerland

Abstract. A spatially explicit, climate-sensitive vegetation model is presented to simulate both present and future distribution of potential natural vegetation types in Switzerland at the level of zonal forest communities. The model has two versions: (1) a ‘basic’ version using geographical region, aspect, bedrock (represented by soil pH), and elevation, and (2) a ‘climate-sensitive’ version obtained by replacing elevation (complex environmental gradient) with temperature (climatic factor). Version 2 is used to predict vegetation response under different (today's and projected) climatic conditions. Two regional climate scenarios are applied: (1) assuming an annual mean temperature increase of 1.1 — 1.4 °C, and (2) assuming an increase of 2.2 — 2.75 °C. Both scenarios result in significant changes of the spatial vegetation patterns as compared with today's climatic conditions. In scenario 1, ca. 33 % of the sample points remain unchanged in terms of the simulated zonal forest community; in scenario 2, virtually all sample points change. The most noticeable changes occur on the Swiss Plateau with Carpinion forests (zonal vegetation of present colline belt) expanding to areas that are occupied today by submontane and low-montane Fagus forests. To estimate the reliability of the simulation, quantitative (comparison with field mapping) and qualitative (comparison with climate types in the Alpine region) tests are performed and the main limitations of the approach are evaluated.     

Spectral analysis discerns pattern and feedback in natural‐ and anthropogenic‐disturbed boreal black spruce forests

The two major disturbance types of boreal black spruce forest in north–central Quebec, Canada – natural disturbance by wildfire and anthropogenic disturbance by harvest – may affect processes of recovery differently and leave distinct post‐disturbance soil and vegetation spatial patterns. We tested whether 1) spatial patterns of physico‐chemical soil organic layer properties, black spruce diameter and density, and understory ericaceous shrub cover, differ between these two principal disturbance types; 2) operations associated with forest harvest result in distinct, regular spatial patterns of these same variables related to presence of machine trails; and 3) ericaceous shrub presence is a potential factor contributing to the legacy of spatial patterns after harvest. We explored these patterns on black spruce‐feathermoss forest stands, including fire‐origin stands (18 and 98 years) and stands originating from harvest (16 and 62 years) in central Quebec, Canada. We used two spatial analysis methods, spectral analysis and principal component analysis in the frequency domain, to characterize and relate spatial patterns of these soil and vegetation variables, measured along 50‐m transects on each site. Spatial patterns of distribution of soil and vegetation variables were different on the burned and the harvested forest sites. Wildfire gave rise to spatial patterns in soil and vegetation variables at multiple scales, reflecting the complexity generated by variable burn intensity. Patterns following forest harvest were mainly related to the regular structure defined by trails created by logging operations. In contrast to burned sites, ericaceous shrub patterns on harvested sites were strongly associated with spatial arrangements of spruce diameter and density, promoting absence of canopy closure and persistence of trails. Moreover, different spatial signatures did not converge in the long‐term (62–98 years) between the two disturbance types. The divergence in spatial structure between natural and anthropogenic disturbances has implications for ecosystem structure and function in the longer term.     

Why do some species have geographically varying responses to fire history?

A capacity to predict the effects of fire on biota is critical for conservation in fire‐prone regions as it assists managers to anticipate the outcomes of different approaches to fire management. The task is complicated because species’ responses to fire can vary geographically. This poses challenges, both for conceptual understanding of post‐fire succession and fire management. We examine two hypotheses for why species may display geographically varying responses to fire. 1) Species’ post‐fire responses are driven by vegetation structure, but vegetation – fire relationships vary spatially (the ‘dynamic vegetation’ hypothesis). 2) Regional variation in ecological conditions leads species to select different post‐fire ages as habitat (the ‘dynamic habitat’ hypothesis). Our case study uses data on lizards at 280 sites in a ～ 100 000 km² region of south‐eastern Australia. We compared the predictive capacity of models based on 1) habitat associations, with models based on 2) fire history and vegetation type, and 3) fire history alone, for four species of lizards. Habitat association models generally out‐performed fire history models in terms of predictive capacity. For two species, habitat association models provided good discrimination capacity even though the species showed geographically varying post‐fire responses. Our results support the dynamic vegetation hypothesis, that spatial variation in relationships between fire and vegetation structure results in regional variation in fauna–fire relationships. These observations explain how the widely recognised ‘habitat accommodation’ model of animal succession can be conceptually accurate yet predictively weak.     

New approaches to understanding late Quaternary climate fluctuations and refugial dynamics in Australian wet tropical rain forests

Aim We created spatially explicit models of palaeovegetation stability for the rain forests of the Australia Wet Tropics. We accounted for the climatic fluctuations of the late Quaternary, improving upon previous palaeovegetation modelling for the region in terms of data, approach and coverage of predictions. Location Australian Wet Tropics. Methods We generated climate‐based distribution models for broad rain forest vegetation types using contemporary and reconstructed ‘pre‐clearing’ vegetation data. Models were projected onto previously published palaeoclimate scenarios dating to c. 18 kyr bp . Vegetation stability was estimated as the average likelihood that a location was suitable for rain forest through all climate scenarios. Uncertainty associated with model projections onto novel environmental conditions was also tracked. Results Upland rain forest was found to be the most stable of the wet forest vegetation types examined. We provide evidence that the lowland rain forests were largely extirpated from the region during the last glacial maximum, with only small, marginally suitable fragments persisting in two areas. Models generated using contemporary vegetation data underestimated the area of environmental space suitable for rain forest in historical time periods. Model uncertainty resulting from projection onto novel environmental conditions was low, but generally increased with the number of years before present being modelled. Main conclusions Climate fluctuations of the late Quaternary probably resulted in dramatic change in the extent of rain forest in the region. Pockets of high‐stability upland rain forest were identified, but extreme bottlenecks of area were predicted for lowland rain forest. These factors are expected to have had a dramatic impact on the historical dynamics of population connectivity and patterns of extinction and recolonization of dependent fauna. Finally, we found that models trained on contemporary vegetation data can be problematic for reconstructing vegetation patterns under novel environmental conditions. Climatic tolerances and the historical extent of vegetation may be underestimated when artificial vegetation boundaries imposed by land clearing are not taken into account.