Vegetation classification enables inferring mesoscale spatial variation in plant invasibility

Factors Affecting Spatial Variation of Classification Uncertainty in an Image Object-based Vegetation Mapping

Inferring Mesoscale Models of Neural Computation

Recent years have seen dramatic progress in the development of techniques for measuring the activity and connectivity of large populations of neurons in the brain. However, as these techniques grow ever more powerful—allowing us to even contemplate measuring every neuron in entire brains—a new problem arises: how do we make sense of the mountains of data that these techniques produce? Here, we ...

Spatial Variation as a Tool for Inferring Temporal Variation and Diagnosing Types of Mechanisms in Ecosystems

Ecological processes, like the rise and fall of populations, leave an imprint of their dynamics as a pattern in space. Mining this spatial record for insight into temporal change underlies many applications, including using spatial snapshots to infer trends in communities, rates of species spread across boundaries, likelihood of chaotic dynamics, and proximity to regime shifts. However, these a...

Spatial and temporal variation in plant hydraulic traits and their relevance for climate change impacts on vegetation.

Plant hydraulics mediate terrestrial woody plant productivity, influencing global water, carbon, and biogeochemical cycles, as well as ecosystem vulnerability to drought and climate change. While inter-specific differences in hydraulic traits are widely documented, intra-specific hydraulic variability is less well known and is important for predicting climate change impacts. Here, I present a c...

Object-based spatial classification of forest vegetation with IKONOS imagery

Object-based image analysis (OBIA) is employed to classify forest types, including deciduous, evergreen and mixed forests, in a U.S. National Park unit using very high spatial resolution (VHR) IKONOS satellite imagery. This research investigates the effect of scale on segmentation quality and object-based forest type classification. Average local variance and spatial autocorrelation analyses ar...