DOI: 10.5061/dryad.jwstqjqgm
title: Recolonization of secondary forests by a locally extinct Caribbean anole through the lens of range expansion theory

description: Disturbance and recovery dynamics are characteristic features of many
 ecosystems. Disturbance dynamics are widely studied in ecology and
 conservation biology. Still, we know less about the ecological processes
 that drive ecosystem recovery. The ecological processes that mediate
 ecosystem recovery stand at the intersection of many theoretical
 frameworks. Range expansion theory is one of these complementary
 frameworks that can provide unique insights into the population-level
 processes that mediate ecosystem recovery, particularly fauna
 recolonization. Although the biodiversity patterns that follow fauna
 recolonization of recovering forests have been well described in the
 literature, the ecological processes at the population level that drive
 these patterns remain conspicuously unknown. In this study, we tested
 three fundamental predictions of range expansion theory during the
 recolonization of recovering forests in Puerto Rico by a shade specialist
 anole, Anolis gundlachi. Range expansion theory predicts that individuals
 at the early stages of recolonization (i.e., younger forests) would have a
 high prevalence of dispersive traits, experience less density dependence,
 and suffer less parasitism. To test these predictions, we conducted a
 chronosequence study applying space-for-time substitution where we
 compared phenotypic traits (i.e., body size, body condition, and relative
 limb size), population density, population growth rates, and Plasmodium
 parasitism rates among lizard populations living in young (&lt; 30
 years), mid (40–60 years), and old-growth forests (&gt; 75 years).
 Lizard populations in younger forests had lower densities, higher
 population growth rates, and lower rates of Plasmodium parasitism compared
 with old-growth forests. Still, while we found that individuals had larger
 body sizes, and longer forelimbs in young forests in one site, this result
 was not consistent among sites. This suggests a potential trade-off
 between the traits that provide a dispersal advantage during the initial
 stages of recolonization and those that are advantageous to establish in
 novel environmental conditions. Overall, our study emphasizes the
 suitability of range expansion theory to describe fauna recolonization but
 also highlights that the ecological processes that drive recolonization
 are time-dependent, complex, and nuanced.
description: We collected the data in three chronosequences (El Verde,
 Carite1, and Carite2) including forests of different ages (old of &gt;
 75 years; mid of 40–60 years and young of &lt; 30 years) in Puerto
 Rico. We quantified phenotypic traits inside 20 x 20 m plots at each
 forest age (i.e., young, mid, old). To estimate abundance we conducted
 distance sampling with 50 m transects. Infection status was assessed by
 collecting tissue samples and conducting PCR diagnostics. Detailed methods
 are included in the manuscript. 
description: # Recolonization of secondary forests by a locally extinct Caribbean anole
 through the lens of range expansion theory
 Give a brief summary of
 dataset contents, contextualized in experimental procedures and results.
 ## 1. Paper information Citation: Acevedo et al. In press. Recolonization
 of secondary forests by a locally extinct Caribbean anole through the lens
 of range expansion theory. Ecological Applications ## 2. Originators
 Miguel A. Acevedo Carly Fankhauser Luis Gonzalez Marne Quigg Bella
 Gonzalez Riccardo Papa ## 3. Contact Information Miguel Acevedo Department
 of Wildlife Ecology and Conservation University of Florida email:
 ## 4. Date of data collection: December 2018 -
 June 2022 ## 5. Geographic location of data collection Puerto Rico ## 6.
 Information about funding sources that supported the collection of the
 data: National Science Foundation (No. 1754401) ## 7. Access Information
 Creative Commons Zero v1.0 Universal ## 8. Data files and variables ####
 data\_phenotypic\_traits.csv - describes phenotypic traits of Anolis
 gundlachi lizards captured in chronosquences in Puerto Rico * uid:
 describes a unique identification number for each individual * date: date
 that the data was collected in the field (month/day/year) * f1: measure of
 the radius/ulna of the lizard in mm measured with an analog caliper * f2:
 measure of the humerus of the lizard in mm measured with an analog caliper
 * b1: measure of the tibia/fibula of the lizard in mm measured with an
 analog caliper * b2: measure of the femur of the lizard in mm measured
 with an analog caliper * svl: snout-to-vent length of the lizard measured
 in mm with a clear ruler * weight: weight of the lizard in g measured with
 a pesola * sex: male, female, juvenile or NA * dbh: diameter at breast
 height of the substrate where the lizard was captured (cm) * temp:
 temperature in F of the substrate where the lizard was captured * site:
 chronosequence in Puerto Rico where the lizard was captured (El Verde,
 Carite1, Carite2) * season: field season where the lizard was captured *
 forest_age: Categorical variable of forest age, young (&lt; 30 yrs), mid
 (50-70 yrs) and old (&gt; 70 yrs). #### data\_parasitism.csv - describes
 malaria infection status of Anolis gundlachi lizards captured in
 chronosequences in Puerto Rico * uid: describes a unique identification
 number for each individual * infection: Plasmodium spp. infection status
 (0 not infected, 1 infected) * svl: snout-to-vent length of the lizard
 measured in mm with a clear ruler * weight: weight of the lizard in g
 measured with a pesola * sex: male, female * forest_age: Categorical
 variable of forest age, young (&lt; 30 yrs), mid (50-70 yrs) and old (&gt;
 70 yrs). * site: chronosequence in Puerto Rico where the lizard was
 captured (El Verde, Carite1, Carite2) * season: field season where the
 lizard was captured #### anolissitedata\_ev\_21.csv - site data for
 distance sampling in El Verde in 2021 * siteID: transect name. These names
 were given by our field team. * length: transect length in m * observer:
 who in the team was the observer. In this case Isla Hession * age: forest
 age: mid, old, young #### anolissitedata\_ev\_19 - site data for distance
 sampling in El Verde in 2019 * siteID: transect name. These names were
 given by our field team. * length: transect length in m * observer: who in
 the team was the observer. In this case Luis Gonzalez * age: forest age:
 mid, old, young #### anolissitedata\_carite\_21 - site data for distance
 sampling in Carite in 2021 * siteID: transect name. These names were given
 by our field team. * length: transect length in m * observer: who in the
 team was the observer. In this case Isla Hession * age: forest age: mid,
 old, young #### anolis\_transect\_data\_ev\_21 - detection data for
 distance sampling in El Verde in 2021 * ID: identification number for
 observation * species: lizard species. "gund" is *Anolis
 gundlachi* * distance_observer: distance to observer in meters * angle:
 heading of lizard in degrees * date: date of observation (month/date/year)
 * site: transect name. This name was given by our field team. *
 main_heading: heading of the transect * forest_age: Categorical variable
 of forest age, young (&lt; 30 yrs), mid (50-70 yrs) and old (&gt; 70 yrs).
 #### anolis\_transect\_data\_ev\_19 - detection data for distance sampling
 in El Verde in 2019 * ID: identification number for observation * species:
 lizard species. "gund" is *Anolis gundlachi* *
 distance_observer: distance to observer in meters * angle: heading of
 lizard in degrees * date: date of observation (month/date/year) * site:
 transect name. This name was given by our field team. * main_heading:
 heading of the transect * forest_age: Categorical variable of forest age,
 young (&lt; 30 yrs), mid (50-70 yrs) and old (&gt; 70 yrs). ####
 anolis\_transect\_data\_carite\_21 detection data for distance sampling in
 Carite in 2021 * ID: identification number for observation * species:
 lizard species. "gund" is *Anolis gundlachi* *
 distance_observer: distance to observer in meters * angle: heading of
 lizard in degrees * date: date of observation (month/date/year) * site:
 transect name. This name was given by our field team. * main_heading:
 heading of the transect * forest_age: Categorical variable of forest age,
 young (&lt; 30 yrs), mid (50-70 yrs) and old (&gt; 70 yrs). ####
 data\_tails.csv - data on tail status (complete, broken, or regenerated)
 of A. gundlachi in chronosequences in Puerto Rico * uid: describes a
 unique identification number for each individual * sex: male, female,
 juvenile or NA * site: chronosequence in Puerto Rico where the lizard was
 captured (El Verde, Carite1, Carite2) * season: field season where the
 lizard was captured * forest_age: Categorical variable of forest age,
 young (&lt; 30 yrs), mid (50-70 yrs) and old (&gt; 70 yrs). * tail: tc is
 tail complete, tr is tail regenerated, and tb is tail broken *
 tail_broken: tc is 0 and 1 otherwise. Note that for all NA means that the
 data point is not available. We use 'NA' consistently among
 tables. ## Code/Software R code for statistical analyses is available in
 [Zenodo](https://zenodo.org/records/10498639?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImIwYmE4MzFmLTVlMDMtNGMwOS1iZWNjLWNhZDg0ODEyYjhhNiIsImRhdGEiOnt9LCJyYW5kb20iOiI0N2I5YmI0MWUxNmVlZmM2ZmNiYmFkMDE0MjFkOGQ5YiJ9.Iurg8TJVWM8hRxnmzUa5adYI9tFf8akU54ZCoMWTxtn_v9VOjx8o22WDUtrgIj6IJak_rofdOPYenXx3phQOqQ).