TY - JOUR
T1 - Long-term effects of nitrogen deposition on vegetation in a deciduous forest near Munich, Germany
AU - Bernhardt-Römermann, M.
AU - Kudernatsch, T.
AU - Pfadenhauer, J.
AU - Kirchner, M.
AU - Jakobi, G.
AU - Fischer, A.
PY - 2007/12
Y1 - 2007/12
N2 - Question: What are the main reasons for changes in the spatial distribution of vegetation types during the last four decades? Location: Isolated small deciduous forest; surrounded by farmland in the northeast of Munich (Germany). Methods: Based on sequential vegetation mapping from the last four decades the spatial development of the vegetation was analysed. Additionally, environmental parameters (soil parameters, PAR, N-deposition) have been analysed to describe the different vegetation types. Results: By linking the vegetation types to environmental parameters, it was possible to identify N-deposition as the most important factor for the changes. In the 1960s to 1980s the replacement of vegetation types adapted to N-poor conditions by N-rich vegetation was very fast. A vegetation type containing species signifying soil impoverishment vanished totally, another vegetation type indicating nutrient poor conditions decreased dramatically. However, since 1985 up to now the decrease of N-poor vegetation types has slowed, but is still ongoing. As a reason for the decreased rate of replacement, we stressed changes in the vertical structure: From 1961 to 1985 both N-deposition as well as changes in vertical vegetation structure seem to be important. Since 1985 up to now only minor changes in vertical structure could be found; changes are mainly due to N-availability. Conclusion: In this paper, the limitations of different methods to detect vegetation changes are discussed. We focus on the potentials of historical vegetation data and vegetation maps. It is shown that valuable information on N-induced vegetation changes can be retrieved from historical vegetation data.
AB - Question: What are the main reasons for changes in the spatial distribution of vegetation types during the last four decades? Location: Isolated small deciduous forest; surrounded by farmland in the northeast of Munich (Germany). Methods: Based on sequential vegetation mapping from the last four decades the spatial development of the vegetation was analysed. Additionally, environmental parameters (soil parameters, PAR, N-deposition) have been analysed to describe the different vegetation types. Results: By linking the vegetation types to environmental parameters, it was possible to identify N-deposition as the most important factor for the changes. In the 1960s to 1980s the replacement of vegetation types adapted to N-poor conditions by N-rich vegetation was very fast. A vegetation type containing species signifying soil impoverishment vanished totally, another vegetation type indicating nutrient poor conditions decreased dramatically. However, since 1985 up to now the decrease of N-poor vegetation types has slowed, but is still ongoing. As a reason for the decreased rate of replacement, we stressed changes in the vertical structure: From 1961 to 1985 both N-deposition as well as changes in vertical vegetation structure seem to be important. Since 1985 up to now only minor changes in vertical structure could be found; changes are mainly due to N-availability. Conclusion: In this paper, the limitations of different methods to detect vegetation changes are discussed. We focus on the potentials of historical vegetation data and vegetation maps. It is shown that valuable information on N-induced vegetation changes can be retrieved from historical vegetation data.
KW - Forest herb layer
KW - Nitrogen gradient
KW - Photosynthetically active radiation
KW - Sequential vegetation mapping
KW - Soil analysis
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=45849146473&partnerID=8YFLogxK
U2 - 10.1111/j.1654-109X.2007.tb00439.x
DO - 10.1111/j.1654-109X.2007.tb00439.x
M3 - Article
AN - SCOPUS:45849146473
SN - 1402-2001
VL - 10
SP - 399
EP - 406
JO - Applied Vegetation Science
JF - Applied Vegetation Science
IS - 3
ER -