Zoning of forest health conditions based on a set of soil, topographic and vegetation parameters

Zirlewagen, Dietmar; Raben, G.; Weise, Markus

doi:10.1016/j.foreco.2007.02.038

Cited by 33 publications

(21 citation statements)

References 26 publications

(31 reference statements)

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“…For those phases showing a significant and at least medium correlation (r ≥ 0.5), phenological maps for each period (1961 to 1990, 1971 to 2000, 1991 to 2009, 2031 to 2060 and 2071 to 2100) were calculated in a GIS by regression kriging [67,68]. The regression equation derived for each phase and period was thereby applied to the long-term mean temperature grids to calculate a surface map for the respective phenophase.…”

Section: Statistical Analysesmentioning

confidence: 99%

Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change

2014

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. These shifts were stronger in Hesse (8 days) than in Germany (6 days). As winter phases tend to shift towards the end of the year, a prolongation of the vegetation period of up to 3 weeks was observed. More than 70% of the phases were correlated with air temperature by r ≥ 0.5, more than 50% even by r ≥ 0.7. Since the 1990s, phenological shifts and regional differences in phase onsets amplified. In many cases, the shifts between 2071 to 2100 and 1961 to 1990 are expected to be at least twice as high as those between 1991 to 2009 and 1961 to 1990. Conclusions: The presented approach allows revealing statistical relationships between air temperatures and phenological onsets. Thus, shifts in plant phenology are an appropriate bioindicator to map early signs of ecosystem transitions under climate change. The phenological records allow estimating future trends of plant phenological development. Using phenological maps as presented in this article, efficient adaption strategies may be planned and implemented in terms of, e.g. adjusting delineation, shape and allocation of protected areas.

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Section: Statistical Analysesmentioning

confidence: 99%

Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change

2014

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“…Norway spruce was selected as it represents the predominant forest species in this region; in addition, spruce needles were confirmed to be well suited for detection of contamination (Suchara et al 2011). The authors selected four research sites dominated by mature Norway spruce forests (natural forest sites) of similar age (Table 1); this was important criteria as the stand age is the most important factor for defoliation (Zirlewagen et al 2007). The stands were located at a maximum distance of 12 km from the active lignite open-pit mines ( Fig.…”

Section: Test Sitementioning

confidence: 99%

Assessing forest health via linking the geochemical properties of a soil profile with the biochemical parameters of vegetation

Kopačková

Lhotáková

Oulehle

et al. 2014

Int. J. Environ. Sci. Technol.

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The transfer of chemical elements/compounds within the soil-plant chain is a part of the biochemical cycling, and this system is controlled by biotic and abiotic factors which determine the final mobility and availability of chemical variables. Heavy metal contamination and low pH are stress factors that lead to changes in the contents of important foliage compounds, which can be used as nonspecific indicators of plant stress. In this study, Norway spruce forests in the Sokolov region, being a part of the ''Black Triangle,'' were selected to assess geochemical and biochemical interactions in the natural soil/plant system. The authors studied the relationship between soil and spruce needle contents of macronutrients and potentially toxic elements and tested whether the soil parameters and their vertical distribution within a soil profile (two organic and two mineral horizons) affect foliage biochemical parameters (contents of photosynthetic pigments, phenolic compounds and lignin). Factor analysis was used to identify underlying variables that explained the pattern of correlations within and between the biochemical and geochemical datasets. Aluminum (Al) and arsenic (As) were identified as toxic elements with high bio-availability for spruce trees, and both were taken up by trees and translocated to the foliage. The correlations between two toxic element contents in needles (Al and As) and the contents of soluble phenolic compounds and total carotenoid to chlorophyll ratio suggest that these latter two biochemical parameters, which both proved to be sensitive to the soil geochemical conditions, can serve as suitable non-specific stress markers.

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“…In 2006, the soil condition of the "Conventwald" watershed was assessed at four depths (0-10 cm, 10-30 cm, 30-60 cm, and 60-90 cm) using a 40 m × 40 m systematic grid with 56 sampling points (Figs Wilpert (2004) and Zirlewagen et al (2007). In this study, the available digital elevation model provided a grid-cell resolution of 1 m. Besides digital terrain attributes in high spatial resolution reflecting geomorphic, climatic, and hydrologic processes, as well as stand-related parameters were tested as auxiliary variables in the regression models.…”

Section: Soil Inventories and Upscaling Approachmentioning

confidence: 99%

“…Their validity is related to the environmental effects which existed up until the point and time of the sampling campaign. If the interrelations between soil chemical status and environmental aspects have changed in the meantime, these alterations cannot be included in scenario models and cannot be forecasted (Zirlewagen et al, 2007), unless a new upscaling model including the new state of soil development is set up.…”

Section: Introductionmentioning

confidence: 99%

Upscaling spatio‐temporal patterns of cation fluxes in acid forest soils

Zirlewagen

Wilpert²

2010

Z. Pflanzenernähr. Bodenk.

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One main problem with current research on spatio-temporal modeling of ion fluxes in forest soils is the separation of space and time effects in the soil-monitoring concept. This article describes an approach to overcome this weakness. Time trends of point information on soil-solution data (base-cation concentrations and fluxes) are scaled by linking them to soil-chemical data which is available in higher spatial resolution and can be upscaled to an area base. This approach is based on a combined evaluation of bulk soil and soil-solution data using both statistical and process-oriented methods. Multiple-linear-regression analyses coupled with geostatistics were developed to predict spatial patterns of exchangeable cation percentages. In a second step, empirical ion-distribution coefficients were adapted according to Gapon using data of suctioncup plots and bulk-soil samples. Seasonally adjusted time-series data of soil-solution chemistry were then connected with the maps of the predicted exchangeable-cation percentages by means of the Gapon equations. This evaluation step provided both time-and space-dependent maps of cation concentrations in the soil solution. Finally, using the results of a water-budget model it was possible to derive spatio-temporal patterns of soil cation fluxes. Methodological limitations and the results of verification processes are discussed. The methods described can only be used in acidic soils and should not be used in soil layers rich in humus, since adsorption to C compounds differs from adsorption to clay minerals. The time increments of the models should be not shorter than yearly in order to suppress annual periodicity. Although the Gapon equations were not based on laboratory-determined exchange solutions at quasi-equilibrium, but rather on field data from the suction-cup technique, the exchangeable-cation percentages showed steady functions of selectivity coefficients. The methods tested at a watershed scale may be flexible enough to be applied at other scales as well.

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Zoning of forest health conditions based on a set of soil, topographic and vegetation parameters

Cited by 33 publications

References 26 publications

Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change

Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change

Assessing forest health via linking the geochemical properties of a soil profile with the biochemical parameters of vegetation

Upscaling spatio‐temporal patterns of cation fluxes in acid forest soils

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