Implementation of machine-learning classification in remote sensing: An applied review
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …
sensed imagery. The strengths of machine learning include the capacity to handle data of …
Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis
Measures of genetic structure among individuals or populations collected at different spatial
locations across a landscape are commonly used as surrogate measures of functional (ie …
locations across a landscape are commonly used as surrogate measures of functional (ie …
[HTML][HTML] Climate change rapidly warms and acidifies Australian estuaries
Climate change is impacting ecosystems worldwide. Estuaries are diverse and important
aquatic ecosystems; and yet until now we have lacked information on the response of …
aquatic ecosystems; and yet until now we have lacked information on the response of …
[HTML][HTML] Gut microbiota in Parkinson's disease: temporal stability and relations to disease progression
Background Several publications have described differences in cross-sectional
comparisons of gut microbiota between patients with Parkinson's disease and control …
comparisons of gut microbiota between patients with Parkinson's disease and control …
Root traits explain rhizosphere fungal community composition among temperate grassland plant species
While it is known that interactions between plants and soil fungi drive many essential
ecosystem functions, considerable uncertainty exists over the drivers of fungal community …
ecosystem functions, considerable uncertainty exists over the drivers of fungal community …
Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological …
IJ Wang - Evolution, 2013 - academic.oup.com
Understanding the effects of landscape heterogeneity on spatial genetic variation is a
primary goal of landscape genetics. Ecological and geographic variables can contribute to …
primary goal of landscape genetics. Ecological and geographic variables can contribute to …
Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity
RT Buxton, MF McKenna, M Clapp, E Meyer… - Conservation …, 2018 - Wiley Online Library
Passive acoustic monitoring could be a powerful way to assess biodiversity across large
spatial and temporal scales. However, extracting meaningful information from recordings …
spatial and temporal scales. However, extracting meaningful information from recordings …
Landscape genetics: where are we now?
Landscape genetics has seen rapid growth in number of publications since the term was
coined in 2003. An extensive literature search from 1998 to 2008 using keywords associated …
coined in 2003. An extensive literature search from 1998 to 2008 using keywords associated …
[HTML][HTML] Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types
Background Few studies have examined post-fire vegetation recovery in temperate forest
ecosystems with Landsat time series analysis. We analyzed time series of Normalized Burn …
ecosystems with Landsat time series analysis. We analyzed time series of Normalized Burn …
Modeling species distribution and change using random forest
Although inference is a critical component in ecological modeling, the balance between
accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; …
accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; …