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A simple and effective method to collect leaves and seeds from tall trees
Author(s) -
Youngentob Kara N.,
Zdenek Christina,
Gorsel Eva
Publication year - 2016
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12554
Subject(s) - climbing , sampling (signal processing) , rope , tree (set theory) , computer science , agricultural engineering , mathematics , environmental science , biology , engineering , ecology , algorithm , mathematical analysis , filter (signal processing) , computer vision
Summary Collecting leaves or seeds from tall trees is a difficult task that many plant physiologists, ecologists, geneticists and forest managers encounter repeatedly. Tree branches are often much higher than a cutting pole or saw can reach. When this happens, the most common solutions involve the use of sharp‐shooters, cherry pickers (a.k.a. bucket trucks) or tree climbers. All of these methods can be expense, logistically complicated, and often involve additional permits and licences. We present a cost‐effective and simple alternative for collecting leaves and seeds from tall trees using an arborist throw‐line launcher. An arborist throw‐line launcher is traditionally used to throw a rope over high branches for tree climbing. However, the same instrument can be used to collect leaves and seeds from trees without the need for climbing. In the course of sampling over 4000 trees from a variety of species across multiple continents, we have developed several techniques to optimize leaf and seed sampling with a throw‐line launcher at heights up to 40 m. We present these techniques along with several time‐saving tips and tricks to increase sampling efficiency and reduce the occurrence of lost weight bags, broken ropes, and hung branches that will not fall. These techniques remove many of the limitations commonly associated with sampling leaves and seeds from tall trees with more traditional methods. Without these limitations, the costs, risks and time associated with this type of data collection are reduced.