![Goals of the Talk (Paper) ,[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Remote Sensing and Individual-Based Ecology
- 1. Remote Sensing vs. Individual-Based Ecology
- 3. Goals of the Talk (Paper) Ecology Remote Sensing Complexity
- 4. Remote Sensing Remote Sensing: “ The collection and interpretation of information about an object without physical contact with the object; eg, satellite imaging, aerial photography, and open path measurements.” -- www.waterquality.de/hydrobio.hw/RTERMS.HTM
- 29. Remote Sensing and IBEcology from High-resolution remote sensing of intertidal ecosystems: A low-cost technique to link scale-dependent patterns and processes. Guichard and Bourget (2000) Limnol. Oceanogr.
Editor's Notes
- More specifically.
- More specifically.
- Experimentation and Observation central to traditional scientific methodology ‘ Controlling variables’ central to experimentation and observation. You measure the effect of something by changing that thing while holding all other things constant. But in ecological systems, there are a lot of things to hold constant, and they tend to be difficult to control. Traditional ecological sampling can be highly precise: age of an animal, diameter of a trunk, chemical content of a stream, but sampling ecosystems can be highly laborious. You have to go there, and you have to get to each spot independantly. Consequently you tend to have a limited number of sample sizes. LOW N. HIGH VARIABILITY IN MANY DIMENSIONS. PRECISE MEASUREMENTS.
- Experimentation and Observation central to traditional scientific methodology ‘ Controlling variables’ central to experimentation and observation. You measure the effect of something by changing that thing while holding all other things constant. But in ecological systems, there are a lot of things to hold constant, and they tend to be difficult to control. Traditional ecological sampling can be highly precise: age of an animal, diameter of a trunk, chemical content of a stream, but sampling ecosystems can be highly laborious. You have to go there, and you have to get to each spot independantly. Consequently you tend to have a limited number of sample sizes. LOW N. HIGH VARIABILITY IN MANY DIMENSIONS. PRECISE MEASUREMENTS.
- There is a recognition in ecology that spatial pattern and ecological process are a fundamental union.
- Landscape scale processes previously unexplored because of: scientific culture of reductionsism lack of methodology for gathering/interpreting data a large spatial scales In addition to novelty, landscape/regional scale ecological questions may be poignant because humans causing ubiquitious changes in driving variables at large spatial scales. I.e. global warming. e.g. ecotone shifts e.g. pine beetles e.g. spruce beetles But there’s a difference from just guessing which of previously observed patterns or behaviours an individual or ecosystem might take. The scale and speed of our human-driven ecological experience is such that we may (continue to) be entirely unprecedented. Prediction is not necessarily explanation. Overfitting is a deal-breaker under those conditions. Thus models must not only be predictive under existing ranges of conditions, they must be mechanistically robust so as to be predictive under wider ranges of conditions than can currently be observed. Investment in mechanistically faithful models based on our current observations is an investment in scenarioing the future. Positivists be damned.
- Landscape scale processes previously unexplored because of: scientific culture of reductionsism lack of methodology for gathering/interpreting data a large spatial scales In addition to novelty, landscape/regional scale ecological questions may be poignant because humans causing ubiquitious changes in driving variables at large spatial scales. I.e. global warming. e.g. ecotone shifts e.g. pine beetles e.g. spruce beetles But there’s a difference from just guessing which of previously observed patterns or behaviours an individual or ecosystem might take. The scale and speed of our human-driven ecological experience is such that we may (continue to) be entirely unprecedented. Prediction is not necessarily explanation. Overfitting is a deal-breaker under those conditions. Thus models must not only be predictive under existing ranges of conditions, they must be mechanistically robust so as to be predictive under wider ranges of conditions than can currently be observed. Investment in mechanistically faithful models based on our current observations is an investment in scenarioing the future. Positivists be damned.
- Explicit focus on the unit of individual allows the deployment of the BFG-9000 of biology: the theory of evolution through natural selection. Doesn’t get much more mechanistically robust than that this side of physics. Focus of IBE is on scaling up and down through IBMs. So you potentially have access to all scales with mechanistic robustness and a full flavoured aftertaste.
- My claim.
- My further claim.
- But is this going too far?
- if you’re measuring more than just the presence/absence of an obvious organism, but actually want to monitor it’s state change, how do you do that?
- Let’s say you find an individual that can be measured with a sensor. Let’s say you have the money and/or the access to get the data. What do you do with the it?
- Let’s say you find an individual that can be measured with a sensor. Let’s say you have the money and/or the access to get the data. What do you do with the it?
- Although this graphic is misleading in ways I won’t describe, this actually is from one of the few studies I’ve seen that appear to be using this approach. Because the output of many IBMs is explicity spatial, it is open to spatial comparison (see below) with spatially explicit remotely sensed data.
- Let’s say you find an individual that can be measured with a sensor. Let’s say you have the money and/or the access to get the data. What do you do with the it?
- Use of pattern (not point) statistics to test if outcome of model fits with observed data. Growing discipline of application of geo-stats to raster-based data for this sort of operation. Needs to grow more, and I need to learn it.
- Use of pattern (not point) statistics to test if outcome of model fits with observed data. Growing discipline of application of geo-stats to raster-based data for this sort of operation. Needs to grow more, and I need to learn it.
- Use of pattern (not point) statistics to test if outcome of model fits with observed data. Growing discipline of application of geo-stats to raster-based data for this sort of operation. Needs to grow more, and I need to learn it.
- Ta da! It’s the scientific method!
- Ta da! It’s the scientific method!