Traditional agroforestry on forested land : a comprehensive analysis of its distribution pattern in the 19th century

Varování

Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Fakultu sociálních studií. Oficiální stránka publikace je na webu muni.cz.
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SZABÓ Péter DINIZ Écio Souza HOUŠKA Jakub

Rok publikování 2024
Druh Článek v odborném periodiku
Časopis / Zdroj Agroforestry Systems
Fakulta / Pracoviště MU

Fakulta sociálních studií

Citace
www https://link.springer.com/article/10.1007/s10457-023-00894-4
Doi http://dx.doi.org/10.1007/s10457-023-00894-4
Klíčová slova Agroforestry; Hay cutting; Litter raking; Forest grazing; Forest management
Přiložené soubory
Popis Traditional agroforestry on agricultural land was common in the past in Central Europe. However, much less is known about agroforestry on forested land, especially because it was often banned by forestry authorities during the 20th century. We used data from the so-called stable cadastre to map the occurrence of agroforestry uses (litter raking, hay cutting and forest grazing) on forested land in the mid-19th century in Moravia (eastern part of the Czech Republic, ca. 27,000 km(2)) in high spatial resolution. We combined machine learning algorithms and logistic models to reveal which environmental, land use and forest management factors could be linked to the occurrence of individual agroforestry uses. Results showed that agroforestry on forested land was very common in the 19th century: only 9.2% of townships with forests had no agroforestry uses. The distribution of agroforestry uses was clearly connected to environmental factors and to the availability of agricultural products that agroforestry uses were meant to supplement (e.g. hay cutting in forests was the most common in townships with large forests and few grasslands). However, the ubiquity of some uses (especially litter raking) made it more difficult to arrive at straightforward conclusions. In addition, we discussed the limitations inherent in the stable cadastre and how these might influence the interpretation of the results.
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