Ned Horning

Predicting distributions of known and unknown reptile species in Madagascar

Despite the importance of tropical biodiversity, informative species distributional data are seldom available for biogeographical study or setting conservation priorities. Modelling ecological niche distributions of species offers a potential soluion; however, the utility of old locality data from museums, and of more recent remotely sensed satellite data, remains poorly explored, especially for rapidly changing tropical landscapes. Using 29 modern data sets of environmental land coverage and 621 chameleon occurrence localities from Madagascar (historical and recent), here we demonstrate a significant ability of our niche models in predicting species distribution. At 11 recently inventoried sites, highest predictive success (85.1%) was obtained for models based only on modern occurrence data (74.7% and 82.8% predictive success, respectively, for pre-1978 and all data combined). Notably, these models also identified three intersecting areas of over-prediction that recently yielded seven chameleon species new to science. We conclude that ecological niche modelling using recent locality records and readily available environmental coverage data provides informative biogeographical data for poorly known tropical landscapes, and offers innovative potential for the discovery of unknown distributional areas and unknown species.

Shrub Cover on the North Slope of Alaska: a circa 2000 Baseline Map

Abstract In situ observations show increases in shrub cover in different arctic regions in recent decades and have been cited to explain the increases in arctic vegetation productivity revealed by satellite remote sensing. A widespread increase in shrub cover, particularly tall shrub cover, is likely to profoundly alter the tundra biome because of its influence on biogeochemical cycling and feedbacks to climate. To monitor changes in shrub cover, aid field studies, and inform ecosystem models, we mapped shrub cover across the North Slope of Alaska. First, images from the IKONOS and SPOT satellite sensors were used to detect tall (>1 m) and short shrub presence at high resolution (<5 m grid cells) in different parts of the domain. The resulting maps were then used to train a Random Forest regression algorithm that mapped total and tall shrub cover, expressed as a percent of the total surface area, at 30 m resolution from a mosaic of Landsat scenes. The final shrub cover maps correspond well with field measurements (r2  =  0.7, root mean square error  =  17%, N  =  24) and compared well with the existing vegetation type maps of the study area and a gridded temperature data set not used in the map generation.

Chapter Ten Free and Open Source Geospatial Tools for Environmental Modelling and Management

Abstract Geospatial (geographical) software systems (GIS) are used for creating, viewing, managing, analysing and utilising geospatial data. Geospatial data can include socioeconomic, environmental, geophysical, and technical data about the Earth and societal infrastructure and it is pivotal in environmental modelling and management (EMM). Desktop, web-based, and embedded geospatial systems have become an essential part of EMM, providing pre- or post-processing of geospatial data, analysis and visualisation of results or a graphical user interface (GUI). Many local, regional, national, and international efforts are underway to create geospatial data infrastructures and tools for viewing and using geospatial data. When environmental attribute data is linked to these infrastructures, powerful tools for environmental management are instantly created. The growing culture of free/libre and open source software (FOSS) provides an alternative approach to software development for the field of GIS (FOSS4G). To provide an overview of FOSS4G for EMM, we analyse platforms, software stacks, and EMM workflows. In the FOSS world the barriers to interoperability are low and thus the software stack tends to be thicker than in the proprietary platform. The FOSS4G world thrives on the evolution of software stacks and platforms. We provide examples of software stacks built from current FOSS4G that support EMM workflows and highlight the advantages of FOSS4G solutions including opportunities to redistribute resulting modelling tools freely to end-users and to support general goals of openness and transparency with respect to modelling tools.

Assessment of Mining Extent and Expansion in Myanmar Based on Freely-Available Satellite Imagery

Using freely-available data and open-source software, we developed a remote sensing methodology to identify mining areas and assess recent mining expansion in Myanmar. Our country-wide analysis used Landsat 8 satellite data from a select number of mining areas to create a raster layer of potential mining areas. We used this layer to guide a systematic scan of freely-available fine-resolution imagery, such as Google Earth, in order to digitize likely mining areas. During this process, each mining area was assigned a ranking indicating our certainty in correct identification of the mining land use. Finally, we identified areas of recent mining expansion based on the change in albedo, or brightness, between Landsat images from 2002 and 2015. We identified 90,041 ha of potential mining areas in Myanmar, of which 58% (52,312 ha) was assigned high certainty, 29% (26,251 ha) medium certainty, and 13% (11,478 ha) low certainty. Of the high-certainty mining areas, 62% of bare ground was disturbed (had a large increase in albedo) since 2002. This four-month project provides the first publicly-available database of mining areas in Myanmar, and it demonstrates an approach for large-scale assessment of mining extent and expansion based on freely-available data.

Open data and open source for remote sensing training in ecology

Abstract Remote sensing is one of the most important tools in ecology and conservation for an effective monitoring of ecosystems in space and time. Hence, a proper training is crucial for developing effective conservation practices based on remote sensing data. In this paper we aim to highlight the potential of open access data and open source software and the importance of the inter-linkages between these and remote sensing training, with an interdisciplinary perspective. We will first deal with the importance of open access data and then we provide several examples of Free and Open Source Software (FOSS) for a deeper and more critical understanding of its application in remote sensing.

Remote Sensing for Biodiversity

Remote sensing (RS)—taking images or other measurements of Earth from above—provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding trends, and also provides key input into assessments, international agreements, and conservation management. Historically, RS data have often been expensive and hard to use, but changes over the last decade have resulted in massive amounts of global data being available at no cost, as well as significant (if not yet complete) simplification of access and use. This chapter provides a baseline set of information about using RS for conservation applications in three realms: terrestrial, marine, and freshwater. After a brief overview of the mechanics of RS and how it can be applied, terrestrial systems are discussed, focusing first on ecosystems and then moving on to species and genes. Marine systems are discussed next in the context of habitat extent and condition and including key marine-specific challenges. This is followed by discussion of the special considerations of freshwater habitats such as rivers, focusing on freshwater ecosystems, species, and ecosystem services.

Losing a jewel-Rapid declines in Myanmar's intact forests from 2002-2014

New and rapid political and economic changes in Myanmar are increasing the pressures on the country’s forests. Yet, little is known about the past and current condition of these forests and how fast they are declining. We mapped forest cover in Myanmar through a consortium of international organizations and environmental non-governmental groups, using freely-available public domain data and open source software tools. We used Landsat satellite imagery to assess the condition and spatial distribution of Myanmar’s intact and degraded forests with special focus on changes in intact forest between 2002 and 2014. We found that forests cover 42,365,729 ha or 63% of Myanmar, making it one of the most forested countries in the region. However, severe logging, expanding plantations, and degradation pose increasing threats. Only 38% of the country’s forests can be considered intact with canopy cover >80%. Between 2002 and 2014, intact forests declined at a rate of 0.94% annually, totaling more than 2 million ha forest loss. Losses can be extremely high locally and we identified 9 townships as forest conversion hotspots. We also delineated 13 large (>100,000 ha) and contiguous intact forest landscapes, which are dispersed across Myanmar. The Northern Forest Complex supports four of these landscapes, totaling over 6.1 million ha of intact forest, followed by the Southern Forest Complex with three landscapes, comprising 1.5 million ha. These remaining contiguous forest landscape should have high priority for protection. Our project demonstrates how open source data and software can be used to develop and share critical information on forests when such data are not readily available elsewhere. We provide all data, code, and outputs freely via the internet at (for scripts: https://bitbucket.org/rsbiodiv/; for the data: http://geonode.themimu.info/layers/geonode%3Amyan_lvl2_smoothed_dec2015_resamp)

Adding structure to land cover – using fractional cover to study animal habitat use

BackgroundLinking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis.We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio–temporal scales.ResultsWe analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump–shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges.ConclusionThe application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer.

Biocultural approaches to developing well-being indicators in Solomon Islands

To meet local and global aspirations toward sustainable resource management, we must first understand what success looks like. At global levels, well-being can be narrowly defined, which may clash with local values and cause adverse impacts. Melanesia is home to a complex mosaic of resource management systems, and finding locally appropriate indicators of success poses particular challenges. We propose that biocultural approaches can assist in developing grounded and appropriate well-being indicators. Biocultural approaches frame issues from the perspectives of place-based communities and work with resource users to develop desired outcomes. In doing so, biocultural approaches recognize links between people and the environment and seek to understand feedbacks between social and ecological components. Biocultural approaches may help to improve the fit between local aspirations and national or international actions and can also cocreate knowledge that draws on local knowledge and practice as well as western science. Here, we report on one such approach in Western Province, Solomon Islands, where rural communities are weighing a variety of trade-offs around the use of natural resources. The work encompasses four locations and seeks to define local needs and priorities, develop appropriate local indicators of success, assess indicator baselines, and catalyze appropriate action. Implementation challenges have included scaffolding between local and national levels and the diversity of the four locations. These have, however, been offset by the engaged nature of indicator creation, which assists communities in planning toward action around local definitions of wellbeing.

Environmental Modeling Using Open Source Tools

Environmental Modeling Using Open Source Tools ARI JOLMA1, DANIEL P. AMES2, NED HORNING3, HELENA MITASOVA4, MARKUS NETELER5, AARON RACICOT6, TIM SUTTON7 1 Helsinki University of Technology, Espoo, Finland 2 Department of Geosciences, Geospatial Software Lab, Idaho State University, Pocatello, ID, USA 3 Center for Biodiversity and Conservation, American Museum of Natural History, New York, NY, USA 4 Department of Marine, Earth and Atmospheric Sciences (MEAS), North Carolina State University, Raleigh, NC, USA 5 Center for Scientific and Technologic Research, The Trentino Cultural Institute, Trento, Italy 6 Ecotrust, Portland, OR, USA 7 Reference Center on Environmental Information, Campinas, Brazil