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8-lifehistory.Rmd
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# Life history {#tradeoffs}
WORK IN PROGRESS
See <https://www.oxfordbibliographies.com/display/document/obo-9780199830060/obo-9780199830060-0016.xml> and <https://en.wikipedia.org/wiki/Life_history_theory> for a definition. I think that all case studies below fall in the LH category. I might consider moving the disease ecology case study in the main Sites and states chapter. See however <https://onlinelibrary.wiley.com/doi/epdf/10.1111/ele.13681> for a link between disease ecology and life history theory.
## Access to reproduction
@pradel1997
Transition matrix:
$$\begin{matrix}
& \\
\mathbf{\Gamma} =
\left ( \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \\ 12 \\ 12 \end{matrix} } \right .
\end{matrix}
\hspace{-1.2em}
\begin{matrix}
z_t=J & z_t=1yNB & z_t=2yNB & z_t=B & z_t=D \\ \hdashline
0 & \phi_1 (1-\alpha_1) & 0 & \phi_1 \alpha_1 & 1 - \phi_1\\
0 & 0 & \phi_2 (1-\alpha_2) & \phi_2 \alpha_2 & 1 - \phi_2\\
0 & 0 & 0 & \phi_3 & 1 - \phi_3\\
0 & 0 & 0 & \phi_B & 1 - \phi_B\\
0 & 0 & 0 & 0 & 1
\end{matrix}
\hspace{-0.2em}
\begin{matrix}
& \\
\left . \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \\ 12 \\ 12 \end{matrix} } \right )
\begin{matrix}
z_{t-1} = J \\ z_{t-1} = 1yNB \\ z_{t-1} = 2yNB \\ z_{t-1} = B \\ z_{t-1} = D
\end{matrix}
\end{matrix}$$
First-year and second-year individuals breed with probabilities $\alpha_1$ and $\alpha_2$. Then, everybody breeds from age 3.
Observation matrix:
$$\begin{matrix}
& \\
\mathbf{\Omega} =
\left ( \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \\ 12 \\12 \end{matrix} } \right .
\end{matrix}
\hspace{-1.2em}
\begin{matrix}
y_t = 1 & y_t = 2 & y_t = 3 & y_t = 4\\ \hdashline
1 & 0 & 0 & 0\\
1 - p_1 & p_1 & 0 & 0\\
1 - p_2 & 0 & p_2 & 0\\
1 - p_3 & 0 & 0 & p_3\\
1 & 0 & 0 & 0
\end{matrix}
\hspace{-0.2em}
\begin{matrix}
& \\
\left . \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \\ 12 \\12 \end{matrix} } \right )
\begin{matrix}
z_t = J \\ z_t = 1yNB \\ z_t = 2yNB \\ z_t = B \\ z_t = D
\end{matrix}
\end{matrix}$$
Juveniles are never detected.
## Tradeoffs {#casestudytradeoff}
@morano_life-history_2013, @shefferson_life_2003, and @cruz-flores_sex-specific_nodate
Case study with simulations as in Oikos paper, see Figure 1 and Table 2. Would be a nice example of the use of simulations. Another example could the statistical power analyses.
Also consider paper by Sarah on red-footed boobies.
## Breeding dynamics
@pradel_breeding_2012, @desprez_now_2011, @desprez_known_2013, and @pacoureau_population_2019
## Using data on dead recoveries
### Ring recovery simple model
### Combination of live captures and dead recoveries
Combine live recapture w/ dead recoveries by @lebreton1999.
Transition matrix
$$\begin{matrix}
& \\
\mathbf{\Gamma} =
\left ( \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \end{matrix} } \right .
\end{matrix}
\hspace{-1.2em}
\begin{matrix}
z_t=A & z_t=JD & z_t=D \\ \hdashline
s & 1-s & 0\\
0 & 0 & 1\\
0 & 0 & 1
\end{matrix}
\hspace{-0.2em}
\begin{matrix}
& \\
\left . \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \end{matrix} } \right )
\begin{matrix}
z_{t-1}=\text{alive} \\ z_{t-1}=\text{just dead} \\ z_{t-1}=\text{dead for good}
\end{matrix}
\end{matrix}$$
Observation matrix
$$\begin{matrix}
& \\
\mathbf{\Omega} =
\left ( \vphantom{ \begin{matrix} 12 \\ 12 \\ 12\end{matrix} } \right .
\end{matrix}
\hspace{-1.2em}
\begin{matrix}
y_t=1 & y_t=2 & y_t=3 \\ \hdashline
1 - p & 0 & p\\
1 - r & r & 0\\
1 & 0 & 0
\end{matrix}
\hspace{-0.2em}
\begin{matrix}
& \\
\left . \vphantom{ \begin{matrix} 12 \\ 12 \\ 12 \end{matrix} } \right )
\begin{matrix}
z_{t}=A \\ z_{t}=JD \\ z_{t}=D
\end{matrix}
\end{matrix}$$
### Cause-specific mortalities
@koons2014, @fernandez-chacon_causes_2016 and @ruette_comparative_2015
## Stopover duration
@guerin_advances_2017 for a comparison of method, would be great to reproduce all analyses.
## Actuarial senescence
@choquet_semi-markov_2011, @peron_evidence_2016 and @marzo2011.
## Uncertainty in age
E.g. @Gervasi2017.
## Uncertainty in age and size
E.g. @gowan2021uncertainty.