LecoS - A QGIS plugin for automated landscape ecology analysis

The quantification of landscape structures is an important part in many ecological analysis dealing with GIS derived satellite data. This paper introduces a new free and open-source tool for conducting landscape ecology analysis. LecoS is able to compute a variety of basic and advanced landscape metrics in an automatized way by iterating through an optional provided vector layer. It is integrated into the QGIS processing framework and can thus be used as a stand-alone tool or within bigger complex models. Finally a potential case-study is demonstrated, which tries to quantify pollinators responses on landscape derived metrics at various scales. Key-words: QGIS, automation, landscape ecology, landscape metrics, Python, GIS tools, pollinators Introduction: The use of free and open-source software in ecological research has gained increasing attention in the last years (Steiniger & Hay, 2009; Boyd & Foody, 2011). Freely available open-source software has several advantages in research such as that the computational and statistical background of the analysis can be independently investigated and verified. Furthermore free software can enhance biological research and knowledge transfer in developing countries, where financial constraints can prevent the access to proprietary alternatives (Steiniger & Hay, 2009). Within ecological research the field of landscape ecology features a number of free and open-source tools (Steiniger & Hay, 2009). Scientific studies in landscape ecology study the relationship between spatial patterns and ecological processes on a variety of spatial and organizational levels (Turner, 1989; Wu, 2006). Landscapes are here often seen as mosaics of differently structured and composed land-cover patches which are potentially connected by spatial dynamics (Pickett & Cadenasso, 1995). The landscape structure can be quantified by size, shape, configuration, number and position of land use patches within a landscape. Those quantified values and metrics are invaluable for various fields of ecological research like for instance studies on the influence of habitat fragmentation on wildlife (Fahrig 2003). Landscape metrics are usually derived from classified land-cover datasets using specialist software and graphical information systems (GIS). See Steiniger & Hay (2009) for an extensive overview of freely available open-source software for landscape ecologists. Out of those software products FRAGSTAT is most likely the most comprehensible software package for the calculation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 PeerJ PrePrints | https://peerj.com/preprints/116v2/ | v2 received: 9 Dec 2013, published: 9 Dec 2013, doi: 10.7287/peerj.preprints.116v2 P re P rin ts of landscape and patch metrics (McGarigal & Marks, 1995; McGarigal et al., 2012). However the analysis in FRAGSTAT is separated from the visualization in a GIS program and does not run natively on all operating systems such as Mac-OS or Linux derivatives. Other widely used open-source software suites include the r.li extension for GRASS GIS (Baker & Cai, 1992) and SDMTools for the R software suite (VanDerWal et al., 2012). Those solution however depend on prior raster formating and cropping or can not be used in complex hierarchical models without knowledge of programming or scripting. Here a new tool is introduced which is capable of analyzing various landscape and patch metrics within a freely available open-source GIS suite and is thus being able to combine the ability of calculating complex landscape metrics within sophisticated GIS models. Landscape ecology analysis in QGIS The QGIS project provides a free and open source desktop and server environment and ships with all functionalities of a modern GIS system (QGIS Development Team, 2013). It furthermore allows the easy extension of its core functions through user-written plugins, which can be downloaded within the desktop suite. Since the last stable version – codename 'Dufour' – the popular spatial data processing framework SEXTANTE has been integrated into QGIS. This new 'Processing toolbox' not only integrates existing geoprocessing functions into a similar toolbox as in the prominent ArcGIS suite, it also allows the creation of automatized models, which are able to combine several individual spatial calculations into single sequential models. Additionally, users are able to add their own python or R scripts to the Processing toolbox. Here a new plugin for QGIS called LecoS (Landscape ecology Statistics) is introduced. It makes heavy use of the scientific python libraries SciPy and Numpy (Jones et al., 2001; Oliphant, 2007) to calculate basic and advanced landscape metrics and provides several functions to conduct landscape analysis. Up to now over 16 different landscape metrics are supported. LecoS furthermore comes with two different interfaces. Core functions like the computation of landscape metrics have their own graphical interface, while more advanced functionalities are only supported in the QGIS Processing toolbox. Table 1: List of functions to date (Version 1.9.2). All functions need installed python-osgeo, python-scipy and python-pil bindings within QGIS 2.0.1 Dafour. Name Interface (Graphical|Processing) Description Landscape preparation Create random landscape (Distribution) no | yes Allows to create a new raster layer based on a chosen statistical distribution. The user can specify the 40 41 42 43