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Martyn, T. E.

Publications and source records attributed to Martyn, T. E..

2 recordsLinked to original sources

Non-destructive spatial mapping of vegetation plots: a re-introduction of the pantograph

O_LINon-destructive spatial mapping of herbaceous plants is often not possible with many modern imaging techniques, especially in systems with highly structured, dense herbaceous canopies. For this purpose we suggest using a modern version of the classic pantograph, a simple instrument that allows precisely scaled drawings. The pantograph version we describe here was specifically designed for small-scale herbaceous vegetation mapping. C_LIO_LISpecifically, our pantograph design is useful for rapidly collecting accurate, spatially explicit data at the scale of 0.1-2 m2 and includes a paired drawing board for easy use in field conditions. C_LIO_LIWe tested the design and technique on 100 annual plant plots that ranged in total density and in plant stature. Based on this mapping trial, we present guidelines for effective manual mapping and map digitization. C_LIO_LIA pantograph is a useful and inexpensive to make tool for non-destructively spatially mapping individual herbaceous plants in the field. Here, we present instructions for the design and fabrication of our modern pantograph, board, and pencil attachment designed specifically for researchers wanting to include small-scale spatial context in their research. C_LI

ecology↗

Estimating interaction matrices from performance data for diverse systems

O_LINetwork theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases non-linearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. C_LIO_LIWe present a novel modelling framework which estimates the strength of pairwise interactions in diverse horizontal systems, using measures of species performance in the presence of varying densities of their potential interaction partners. C_LIO_LIOur method allows us to directly estimate pairwise effects when they are statistically identifiable and approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and are non-symmetrical. C_LIO_LIThe advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology. C_LI

ecology↗