2019/12/01 by Alan R. Pearse, Pearse, Alan R., James McGree +11
Environmental Science · #Hydrology and Watershed Management Studies #Soil and Water Nutrient Dynamics #Hydrology and Sediment Transport Processes
paper · pdf · doi:10.48550/arxiv.1912.00540
Streams and rivers are biodiverse and provide valuable ecosystem services.\nMaintaining these ecosystems is an important task, so organisations often\nmonitor the status and trends in stream condition and biodiversity using field\nsampling and, more recently, autonomous in-situ sensors. However, data\ncollection is often costly and so effective and efficient survey designs are\ncrucial to maximise information while minimising costs. Geostatistics and\noptimal and adaptive design theory can be used to optimise the placement of\nsampling sites in freshwater studies and aquatic monitoring programs.\nGeostatistical modelling and experimental design on stream networks pose\nstatistical challenges due to the branching structure of the network, flow\nconnectivity and directionality, and differences in flow volume. Thus, unique\nchallenges of geostatistics and experimental design on stream networks\nnecessitates the development of new open-source software for implementing the\ntheory. We present SSNdesign, an R package for solving optimal and adaptive\ndesign problems on stream networks that integrates with existing open-source\nsoftware. We demonstrate the mathematical foundations of our approach, and\nillustrate the functionality of SSNdesign using two case studies involving real\ndata from Queensland, Australia. In both case studies we demonstrate that the\noptimal or adaptive designs outperform random and spatially balanced survey\ndesigns. The SSNdesign package has the potential to boost the efficiency of\nfreshwater monitoring efforts and provide much-needed information for\nfreshwater conservation and management.\n