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., Brimacombe et al. (2023) 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