Lec 9-2: Finding the Right Scale

Ecological Neighborhoods

concept describing genera procedures for determining how organisms respond to landscape heterogeneity (neighborhood is defined by movement)

properties of ecological neighborhoods

1. A specific ecological process

2. timescale appropriate to that process

3. spatial activity of an organism during that time

organism-centric approach

addresses scale by incorporating a species idiosyncratic view of the world based on animal size

organism-centric approach equation

maximum body length + lifespan = spatial extension of organism

what theory expands on the organism-centric approach?

network theory

network theory

theory says that we store related ideas in separate categories, or files, called nodes

multiscale approaches

often best at dealing with widespread ecological complexity

when is the multiscale approach most commonly used?

most common in disease ecology

spatial context

landscape structure and composition of an area surrounding a study site

how does spatial context advance ecological neighborhoods?

the landscape surrounding a used resource provided the environmental context for understanding organismal response to that resource

domains of scale

- provides a leeway in selecting scale; you don't have to concreate select the appropriate scale from the jump

- if there is a pattern at every scale, how is one to find trends?

unappreciated impediments

attributes of scale are insufficient by themselves to understand animal responses to changing resource reflected by changing landscapes (number system mismatch)

number system mismatch

unavoidable structural mismatches between large and small number systems in regards to statistical analyses

issues with big data, repeatability, and reliability

volume, variety, velocity, veracity, and value

volume

the crude amount of data; the larger the volume the harder to validate

variety

having heterogeneity of sources for data; data is collected in different ways and have different variances associated with them

velocity

the speed of generation of data; being mindful of the temporal scale of data collection (large scale problems like climate change)

veracity

data quality; how do you ensure that the data has been collected to the highest standard

value

ties all points together; what do we actually get out of/learn from the data