Meteorological data series from Swiss long-term forest ecosystem research plots since 1997

The Canadian Forest Service (CFS) has organized a National Forest Ecosystem Research Network of Sites (FERNS). These sites are focussed on the study of sustainable forest management practices and ecosystem processes at the stand level. Network objectives are to promote this research nationally and internationally, provide linkages among sites, preserve the long-term research investments already made on these sites and provide a forum for information exchange and data sharing. The 17 individual sites are representative of six ecozones across Canada and address the common issue of silvicultural solutions to problems of sustainable forest management. While the CFS coordinates and promotes FERNS, the network consists of local autonomous partners nationwide who benefit from the FERNS affiliation through increased publicity for their sites. Key words: long-term, silviculture, network, interdisciplinary, ecozone, ecosystem processes

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A new concept in sustainable forest management – the need for forest ecosystem and landscape research

Journal of Forest Science ◽

10.17221/4650-jfs ◽

2012 ◽

Vol 50 (No. 11) ◽

pp. 520-525 ◽

Cited By ~ 1

Author(s):

J. Kulhavý

Keyword(s):

Forest Ecosystem ◽

Sustainable Forest Management ◽

Forest Ecology ◽

Research Programme ◽

Economic Research ◽

Ecosystem Research ◽

The Czech Republic ◽

Landscape Research ◽

The Individual

The greatest advance in ecosystem research was made in the last century. The development and acceptance of forest ecology by foresters occurred because it provided a means for recognizing, understanding, classifying and mapping the natural variation of forests. Forest ecology involved studies at the individual, population, community, and ecosystem levels but such studies always needed to involve the ecosystem concept. Today, the new concept of “ecosystem and landscape forestry” integrating ecological and socio-economic research has been developed on the basis of EU COST Action E-25 European Network for a Long-term Forest Ecosystem and Landscape Research Programme. An analysis has been carried out of the present situation in forest research in the Czech Republic. The need for forest ecosystem and landscape research is obvious.

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Large-scale lysimeter site St. Arnold, Germany: analysis of 40 years of precipitation, leachate and evapotranspiration

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-5-2623-2008 ◽

2008 ◽

Vol 5 (4) ◽

pp. 2623-2656 ◽

Cited By ~ 2

Author(s):

N. Harsch ◽

M. Brandenburg ◽

O. Klemm

Keyword(s):

Large Scale ◽

Evaporation Rate ◽

Deciduous Forest ◽

Meteorological Data ◽

Regional Climate ◽

Coniferous Forest ◽

Primary Objective ◽

Secular Trends ◽

Data Series

Abstract. This study deals with a lysimetrical-meteorological data series collected on the large-scale lysimeter site "St. Arnold", Germany, from November 1965 to April 2007. The particular relevance of this data rests both upon its perdurability and upon the fact that the site is comprised of a grassland basin, an oak/beech and a pine basin1. Apart from analyzing secular trends of the meteorological measurements, the primary objective of this study is the evaluation of precipitation in connection with leachate quantities and potential and actual evapotranspiration. The latter are based upon the Penman and the Penman-Monteith approaches, respectively. The main results of this survey are that, on a long-term average, the grassland basin turns more than half (53%) of its annually incoming precipitation into leachate and only 36% into water vapour, while the deciduous forest exhibits a rather balanced ratio with 37% for leachate and 44% for evapotranspiration, and the evergreen coniferous forest shows the highest evaporation rate (56%) and the lowest leachate rate (28%). Concerning these water balances, considerable differences both between basins and between seasons stand out. While summer periods exhibit high evapotranspiration rates for the forests and moderate ones for the grassland, winter periods are characterised by considerable leachate quantities for grassland and the deciduous forest and moderate ones for the coniferous forest. Following the analysis of the climatic development in St. Arnold, trends towards a milder and more humid regional climate were detected. 1According to a survey conducted by Lanthaler in 2006, only 1% of all European lysimeters are planted with forests. Leading varieties are fields (63%) and grassland (21%).

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Large-scale lysimeter site St. Arnold, Germany: analysis of 40 years of precipitation, leachate and evapotranspiration

Hydrology and Earth System Sciences ◽

10.5194/hess-13-305-2009 ◽

2009 ◽

Vol 13 (3) ◽

pp. 305-317 ◽

Cited By ~ 13

Author(s):

N. Harsch ◽

M. Brandenburg ◽

O. Klemm

Keyword(s):

Large Scale ◽

Evaporation Rate ◽

Deciduous Forest ◽

Meteorological Data ◽

Regional Climate ◽

Coniferous Forest ◽

Primary Objective ◽

Data Series ◽

Long Term Trends

Abstract. This study deals with a lysimetrical-meteorological data series collected on the large-scale lysimeter site "St. Arnold", Germany, from November 1965 to April 2007. The particular relevance of this data rests both upon its perdurability and upon the fact that the site is comprised of a grassland basin, an oak/beech and a pine basin. Apart from analyzing long term trends of the meteorological measurements, the primary objective of this study is to investigate the water balance in grassland and forested basins, in particular comparing the precipitation term to leachate quantities and potential and actual evapotranspiration. The latter are based upon the Penman and the Penman-Monteith approaches, respectively. The main results of this survey are that, on a long-term average, the grassland basin turns more than half (53%) of its annually incoming precipitation into leachate and only 36% into water vapour, while the deciduous forest exhibits a ratio of 37% for leachate and 56% for evapotranspiration, and the evergreen coniferous forest shows the highest evaporation rate (65%) and the lowest leachate rate (26%). Concerning these water balances, considerable differences both between basins and between seasons stand out. While summer periods exhibit high evapotranspiration rates for the forests and moderate ones for the grassland, winter periods are characterised by considerable leachate quantities for grassland and the deciduous forest and moderate ones for the coniferous forest. Following the analysis of the climatic development in St. Arnold, trends towards a milder and more humid regional climate were detected.

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Snow Water Equivalents exclusively from Snow Heights and their temporal Change: The ΔSNOW.MODEL

10.5194/egusphere-egu2020-11298 ◽

2020 ◽

Author(s):

Michael Winkler ◽

Harald Schellander

Keyword(s):

Meteorological Data ◽

Temporal Frequency ◽

R Package ◽

Data Series ◽

Snow Water ◽

Meteorological Input ◽

Semi Empirical ◽

Height Data ◽

Process Based Models

<p>Snow heights have been measured at lots of places over many years and decades, often at daily resolution. In many cases the data series have no gaps and are of high quality. In recent times, remote sensing provides more and more maps of snow heights, sometimes at high temporal frequency as well. However, most of these snow height data series lack information about snow water equivalents (SWEs), and they often come without sufficient meteorological data to run sophisticated, process-based snow models to simulate SWEs. Statistical SWE models, on the other hand, are subject to regional calibration parameters and cannot model SWEs of distinct days. Nevertheless, for many applications (hydrology, climatology, structural design,&#8230;) SWE-series are very valuable.</p><p>The &#916;SNOW.MODEL presented, is a semi-empirical layer-model that simulates SWEs exclusively from snow heights and their temporal changes. It is computationally cheap and is provided as an easy-to-use R-package. Like statistical snow models, the &#916;SNOW.MODEL does not need any meteorological input, but simulates more accurate SWE values: Statistical models typically show root mean square differences between observations and model values of 20-50 kg/m&#178;, biases of maximum seasonal SWE of +50 to +100 kg/m&#178;, and timing offsets for seasonal maximum SWE of -15 to 0 days. The &#916;SNOW.MODEL reaches 15-30 kg/m&#178;, -20 to +20 kg/m&#178;, and -3 to +5 days, respectively. These scores are comparable with those of process based models, though they are calculated without the need of further meteorological or geographical data except snow height. Therefore, the &#916;SNOW.MODEL can be used to assign highly reliable means and maxima of SWE as well as durations of high snow loads to long-term and historic snow height data, and it can simulate SWEs of distinct days with a comparatively high precision. In some (promising) respect the &#916;SNOW.MODEL bridges the gap between process-based and statistical snow models.</p>

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