Soil moisture controls environmental processes and species distributions, but it is difficult to measure and interpolate across space. Topographic Wetness Index (TWI) derived from digital elevation ...model is therefore often used as a proxy for soil moisture. However, different algorithms can be used to calculate TWI and this potentially affects TWI relationship with soil moisture and species assemblages.
To disentangle insufficiently-known effects of different algorithms on TWI relation with soil moisture and plant species composition, we measured the root-zone soil moisture throughout a growing season and recorded vascular plants and bryophytes in 45 temperate forest plots. For each plot, we calculated 26 TWI variants from a LiDAR-based digital terrain model and related these TWI variants to the measured soil moisture and moisture-controlled species assemblages of vascular plants and bryophytes.
A flow accumulation algorithm determined the ability of the TWI to predict soil moisture, while the flow width and slope algorithms had only a small effects. The TWI calculated with the most often used single-flow D8 algorithm explained less than half of the variation in soil moisture and species composition explained by the TWI calculated with the multiple-flow FD8 algorithm. Flow dispersion used in the FD8 algorithm strongly affected the TWI performance, and a flow dispersion close to 1.0 resulted in the TWI best related to the soil moisture and species assemblages. Using downslope gradient instead of the local slope gradient can strongly decrease TWI performance.
Our results clearly showed that the method used to calculate TWI affects study conclusion. However, TWI calculation is often not specified and thus impossible to reproduce and compare among studies. We therefore provide guidelines for TWI calculation and recommend the FD8 flow algorithm with a flow dispersion close to 1.0, flow width equal to the raster cell size and local slope gradient for TWI calculation.
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•Topographic Wetness Index (TWI) quantifies terrain driven variation in soil moisture.•TWI can be calculated with different flow-routing, slope and flow width algorithms.•We compared these algorithms against measured soil moisture and plant composition.•TWI algorithm determines TWI ability to predict soil moisture and plant assemblages.•Best TWI uses Freeman flow algorithm, flow width equal cell size and local slope.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Context
Forest microclimates differ from regional macroclimates because forest canopies affect energy fluxes near the ground. However, little is known about the environmental drivers of understorey ...temperature heterogeneity and its effects on species assemblages, especially at landscape scales.
Objectives
We aimed to identify which temperature variables best explain the landscape-scale distribution of forest vegetation and to disentangle the effects of elevation, terrain attributes and canopy cover on understorey temperatures.
Methods
We measured growing season air temperature, canopy cover and plant community composition within 46 plots established across a 400-km
2
area in Czech Republic. We linked growing season maximum, mean and minimum temperatures with elevation, canopy cover and topographic proxies for heat load, topographic position, soil moisture and cold air drainage, and created fine-scale topoclimatic maps of the region. We compared the biological relevance of in situ measured temperatures and temperatures derived from fine-scaled topoclimatic maps and global WorldClim 2 maps.
Results
Maximum temperature was the best predictor of understorey plant species composition. Landscape-scale variation in maximum temperature was jointly driven by elevation and terrain topography (
R
adj
.
2
= 0.79) but not by canopy cover. Modelled maximum temperature derived from our topoclimatic maps explained significantly more variation in plant community composition than WorldClim 2 grids.
Conclusions
Terrain topography creates landscape-scale variation in maximum temperature, which in turn controls plant species assembly within the forest understorey. Maximum temperature is therefore an important but neglected microclimatic driver of species distribution across landscapes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The accelerating rates of international trade, travel, and transport in the latter half of the twentieth century have led to the progressive mixing of biota from across the world and the number of ...species introduced to new regions continues to increase. The importance of biogeographic, climatic, economic, and demographic factors as drivers of this trend is increasingly being realized but as yet there is no consensus regarding their relative importance. Whereas little may be done to mitigate the effects of geography and climate on invasions, a wider range of options may exist to moderate the impacts of economic and demographic drivers. Here we use the most recent data available from Europe to partition between macroecological, economic, and demographic variables the variation in alien species richness of bryophytes, fungi, vascular plants, terrestrial insects, aquatic invertebrates, fish, amphibians, reptiles, birds, and mammals. Only national wealth and human population density were statistically significant predictors in the majority of models when analyzed jointly with climate, geography, and land cover. The economic and demographic variables reflect the intensity of human activities and integrate the effect of factors that directly determine the outcome of invasion such as propagule pressure, pathways of introduction, eutrophication, and the intensity of anthropogenic disturbance. The strong influence of economic and demographic variables on the levels of invasion by alien species demonstrates that future solutions to the problem of biological invasions at a national scale lie in mitigating the negative environmental consequences of human activities that generate wealth and by promoting more sustainable population growth.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Abstract
We report the first laboratory experiment dealing with the interaction of a cosmic dust simulant with positrons emitted from a
22
Na radioisotope. Measurements of a charge of micrometer SiO
...2
dust grains with an accuracy of one elementary charge
e
revealed +1 e steps due to positron annihilation inside the grain. The observed average rate of these charging events agrees well with prediction of a model based on the continuous slowing down approximation of energetic of positrons inside the grain. Less frequent charge steps larger than +1 e were attributed to emission of secondary electrons during positron slowing down. The determined coefficient of secondary electron emission is approximately inversely proportional to the grain radius. The experimental results led us to the formulation of a possible scenario of interstellar dark clouds charging.
Recent studies using vegetation plots have demonstrated that habitat type is a good predictor of the level of plant invasion, expressed as the proportion of alien to all species. At local scale, ...habitat types explain the level of invasion much better than alien propagule pressure. Moreover, it has been shown that patterns of habitat invasion are consistent among European regions with contrasting climates, biogeography, history and socioeconomic background. Here we use these findings as a basis for mapping the level of plant invasion in Europe. European Union and some adjacent countries. We used 52,480 vegetation plots from Catalonia (NE Spain), Czech Republic and Great Britain to quantify the levels of invasion by neophytes (alien plant species introduced after ad 1500) in 33 habitat types. Then we estimated the proportion of each of these habitat types in CORINE land-cover classes and calculated the level of invasion for each class. We projected the levels of invasion on the CORINE land-cover map of Europe, extrapolating Catalonian data to the Mediterranean bioregion, Czech data to the Continental bioregion, British data to the British Isles and combined Czech-British data to the Atlantic and Boreal bioregions. The highest levels of invasion were predicted for agricultural, urban and industrial land-cover classes, low levels for natural and semi-natural grasslands and most woodlands, and the lowest levels for sclerophyllous vegetation, heathlands and peatlands. The resulting map of the level of invasion reflected the distribution of these land-cover classes across Europe. High level of invasion is predicted in lowland areas of the temperate zone of western and central Europe and low level in the boreal zone and mountain regions across the continent. Low level of invasion is also predicted in the Mediterranean region except its coastline, river corridors and areas with irrigated agricultural land.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NMLJ, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. ...Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Microclimates have been recognised as one of the key drivers in global change biology. Durable microclimate loggers, detailed in‐situ measurements and sophisticated modelling tools are ...increasingly available, but a lack of standardised workflows for microclimate data handling hinders synthesis across the studies and thus progress in the global change biology. To overcome these limitations, we developed an R package
myClim
for microclimate data processing, storage and analyses. The
myClim
package supports complete workflow for microclimate data handling, including reading raw logger data files, their preprocessing and cleaning, time‐series' aggregation, calculation of ecologically relevant microclimatic variables, data export and storage.
The
myClim
package stores data in a size‐efficient, hierarchical structure which respects the hierarchy of field microclimate measurement (locality > loggers > sensors). For imported microclimatic data,
myClim
provides an informative summary and automatically detects and corrects common issues like duplicated and wrongly ordered measurements. The
myClim
package also provides advanced functions for microclimate data aggregation to various timescales (e.g. days, months, years or growing seasons) as well as tools for sensor calibration, data conversion and joining of multiple microclimatic time series.
The
myClim
package provides advanced functions for standardised calculation of ecologically relevant microclimatic variables like freezing and growing degree days, snow cover period, soil volumetric water content and atmospheric vapour pressure deficit. Calculated microclimatic variables are stored efficiently in
myClim
data format and can be easily exported to long or wide tables for further analyses and visualisations.
Adopting
myClim
can facilitate large‐scale syntheses, boost data sharing and increase the comparability and reproducibility of microclimatic studies. The stable version of
myClim
is available on CRAN (
https://cran.r‐project.org/web/packages/myClim
) and the development version is available on GitHub (
https://github.com/ibot‐geoecology/myClim
).
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Severe canopy-removing disturbances are native to many temperate forests and radically alter stand structure, but biotic legacies (surviving elements or patterns) can lend continuity to ecosystem ...function after such events. Poorly understood is the degree to which the structural complexity of an old-growth forest carries over to the next stand. We asked how pre-disturbance spatial pattern acts as a legacy to influence post-disturbance stand structure, and how this legacy influences the structural diversity within the early-seral stand.
Two stem-mapped one-hectare forest plots in the Czech Republic experienced a severe bark beetle outbreak, thus providing before-and-after data on spatial patterns in live and dead trees, crown projections, down logs, and herb cover.
Post-disturbance stands were dominated by an advanced regeneration layer present before the disturbance. Both major species, Norway spruce (Picea abies) and rowan (Sorbus aucuparia), were strongly self-aggregated and also clustered to former canopy trees, pre-disturbance snags, stumps and logs, suggesting positive overstory to understory neighbourhood effects. Thus, although the disturbance dramatically reduced the stand's height profile with ~100% mortality of the canopy layer, the spatial structure of post-disturbance stands still closely reflected the pre-disturbance structure. The former upper tree layer influenced advanced regeneration through microsite and light limitation. Under formerly dense canopies, regeneration density was high but relatively homogeneous in height; while in former small gaps with greater herb cover, regeneration density was lower but with greater heterogeneity in heights.
These findings suggest that pre-disturbance spatial patterns of forests can persist through severe canopy-removing disturbance, and determine the spatial structure of the succeeding stand. Such patterns constitute a subtle but key legacy effect, promoting structural complexity in early-seral forests as well as variable successional pathways and rates. This influence suggests a continuity in spatial ecosystem structure that may well persist through multiple forest generations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Tree mortality caused by bark beetle infestation has significant effects on the ecology and value of both natural and commercial forests. Therefore, prediction of bark beetle infestations is critical ...in forest management. Existing predictive models, however, rarely consider the influence of long-term stressors on forest susceptibility to bark beetle infestation. In this study we introduce pre-disturbance spectral trajectories from Landsat Thematic Mapper (TM) imagery as an indicator of long-term stress into models of bark beetle infestation together with commonly used environmental predictors. Observations for this study come from forests in the central part of the Šumava Mountains, in the border region between the Czech Republic and Germany, Central Europe. The areas of bark beetle-infested forest were delineated from aerial photographs taken in 1991 and in every year from 1994 to 2000. The environmental predictors represent forest stand attributes (e.g., tree density and distance to the infested forest from previous year) and common abiotic factors, such as topography, climate, geology, and soil. Pre-disturbance spectral trajectories were defined by the linear regression slope of Tasseled Cap components (Wetness, Brightness and Greenness) calculated from a time series of 16 Landsat TM images across years from 1984 until one year before the bark beetle infestation. Using logistic regression and multimodel inference, we calculated predictive models separately for each single year from 1994 to 2000 to account for a possible shift in importance of individual predictors during disturbance. Inclusion of two pre-disturbance spectral trajectories (Wetness slope and Brightness slope) significantly improved predictive ability of bark beetle infestation models. Wetness slope had the greatest predictive power, even relative to environmental predictors, and was relatively stable in its power over the years. Brightness slope improved the model only in the middle of the disturbance period (1996). Importantly, these pre-disturbance predictors were not correlated with other predictors, and therefore bring additional explanatory power to the model. Generally, the predictive power of most fitted model decreases as time progresses and models describing the initial phase of bark beetle outbreaks appear more reliable for conducting near-future predictions. The pre-disturbance spectral trajectories are valuable not only for assessing the risk of bark beetle infestation, but also for detection of long-term gradual changes even in non-forest ecosystems.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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