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01_reconstruction_methods.qmd
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01_reconstruction_methods.qmd
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---
title: "How we reconstruct paleo food webs"
date: last-modified
format:
html:
embed-resources: true
title-block-banner: true
bibliography: references.bib
---
## Why build paleo food webs?
- Because its interesting?
- Value in using hindcasting to aid in forecasting. *e.g.,* the Toarcian ms shows how we can use these paleo communities to understand trophic-level responses to extinctions.
## How do we do it?
- There is an evolving body of work that focuses on developing tools specifically for the task of predicting food webs.
- There are a handful that have been developed specifically in the context of paleo settings *e.g.,* TODO but we can also talk about those that might have been developed/tested in contemporary settings but still have applicability in paleo ones.
- Different underlying theory though
- Focus here on the idea of different 'currencies' but also aggregations - energy vs compatibility.
- Insert brief overview of the different methods as they pertain to approach (so the T4T triangle)
- Challenges we face (even in contemporary settings)?
- keep high level - I think the argument here should fall more in the data trade offs...
## The cost of prediction
- different models need different data and/or are making some very opinionated assumptions
- this is going to link back to the goal of prediction as well (desire to discover or describe)
- which means need to make a cost-benefit analysis
- especially if we want to think about how this intersects with model performance/benchmarking
## Understanding how networks are different
- Not always representing the same things (*i.e.,* different underlying philosophies). So, although they may all be representing food webs (and feeding links between species) they are 'telling different stories' - T4T work...
- feasibility (*e.g.* PFIM) vs energy (*e.g.* ADBM)
- fundamental vs realised niche analogy??
- understanding what links are representing
- Need to be careful when we are 'presenting'/analysing these different food webs and we can't really compare on contrast
- *e.g.,* @brimacombe2023 shows that the research group influences the 'criteria' that defines interactions/networks and so we can't actually meaningfully integrate these networks into the same database and assume that they 'fit' together.
- Petchy dilemma?
## Challenges specific to paleo communities/networks
- I think the goal here should be more a way of acknowledging some of the limitations we face and not a 'this is a complete waste of time' narrative
- It's a case of being aware of your blind spots and working with the acknowledgement that they are there.
- Don't actually have both the complete community (preservation bias) or location specific occurrence (to account for preservation bias often need to aggregate from different locations???)
- We can't truly validate any predictions (maybe some)
## Dataset Overview
- Species
- Time/space
- And probably some other paleo things that will be relevant...
## Methods to use
- PFIM (mechanistic compatibility)
- ADBM (energy explicit)
- Body size ratio (energy implicit)
- Niche (topographical/generative)
## Section Overview
- introduce/discuss some of the food web reconstruction methods
- construct networks for (ideally) a datasets across distinct time units using these (or some of) approaches
- compare and contrast if they tell us a different story