The question of what controls animal abundance has always been fundamental to ecology, but given rapid environmental change, understanding the drivers and mechanisms governing abundance is more important than ever. Here, we determine how multidimensional environments and niches interact to determine population abundance along a tropical habitat gradient. Focusing on the endemic lizard Anolis bicaorum on the island of Utila (Honduras), we evaluate direct and indirect effects of three interacting niche axes on abundance: thermal habitat quality, structural habitat quality, and prey availability. We measured A. bicaorum abundance across a series of thirteen plots and used N-mixture models and path analysis to disentangle direct and indirect effects of these factors. Results showed that thermal habitat quality and prey biomass both had positive direct effects on anole abundance. However, thermal habitat quality also influenced prey biomass, leading to a strong indirect effect on abundance. Thermal habitat quality was primarily a function of canopy density, measured as leaf area index (LAI). Despite having little direct effect on abundance, LAI  had a strong overall effect mediated by thermal quality and prey biomass. Our results demonstrate the role of multidimensional environments and niche interactions in determining animal abundance and highlight the need to consider interactions between thermal niches and trophic interactions to understand variation in abundance, rather than focusing solely on changes in the physical environment.

Combination of Data sources collected on the island of Utila, Honduras - Datasets outlined below. 

1. Anole Count Data - collected using mark recapture methods over 4 survey visits (9am, 1pm, 5pm and 9am the following day)- (Count_Abicaorum.xlsx). 

2. bicaCovs.csv - dataset used as covariates within the unmarked package (Unmarked_Code_Abicaorum.R) All columns described below. 

• Time and date columns - used for estimates as a basic unmarked matrix. 
• LAI Transects - mean leaf area index of two cross sectional transects captured using an Accupar Lp-80 ceptometer. 
• Shannon.Div.Sweep - Shannons diversity for plot invertebrate sweep net samples. 
• Simpson.div.sweep - simpsons diversity for plot invertebrate sweep net samples
• sweep.net.biomass - biomass (g) of sweep net invertebrate samples 
• combined prey shannon - combined sweep net and leaf litter invertebrate samples - shannon diversity 
• combined prey simpson -  combined sweep net and leaf litter invertebrate samples - simpson diversity 
• Combined biomass -  biomass (g) - combined sweep net and leaf litter invertebrate samples
• Tpref.Dev - Total deviation (total oC) of all 3d models within plot away from Tpref range during thermal survey period - collected with ibutton and 3d anolis models. 
• Tpref.3 - percent of time (out of 39 survey hours) that the 3d models were within the tpref range in each plot. 
• Air.Temp - mean air temperature during anole surveys - collected using consistent hour logging of air temp by shaded ibutton within plot over 10 weeks. 
• No.perches - number of perches within each plot - measured manually in plot. 
• Basal.area - basal area (m2) of each plot c\alculated suing standard basal area calculation of diameter at breast height for each tree/perch in plot. 
• Sagrei.abundance - abundance calculated from unmarked models of - Anolis sagrei abundance within plots - note this not used in paper. 
• Dev.Above - Total deviation (total oC) of all 3d models within plot being above the Tpref range during thermal survey period - collected with ibutton and 3d anolis models.
• Dev.Below - Total deviation (total oC) of all 3d models within plot below the Tpref range during thermal survey period - collected with ibutton and 3d anolis models.

 3. AirTemp_6amto6pm_wholeseason.xls – hourly air temperature measures from 06:00 to 18:00 for the whole of the survey season – approx. 10 weeks – for each plot. , measured using ibutton.

4. AirTemp_duringsurveys – air temperature recorded with same ibutton as dataset above – for the time/day that surveys were conducted at each plot (abundance surveys).

5. bicao.csv – Matrix of anole individual encounters – gathered from mark recapture methods – (dataset 1) – to be inputted into unmarked model code  - (Unmarked_Code_Abicaorum.R).

6. A.bicaorum abundance.csv – abundance estimates for each plot calculated using Unmarked_Code_Abicaorum.R allowing abundance only to vary by plot.

7. Invertebrate Samples – Analysis and Dataset – All invertebrate #(prey availability) data collected for each plot,. Including genus and weight – used to calculate metrics within bicaCovs.csv.

8. Path_variables – input for ‘path anlysis .R’ – including all data for plots used in the path analysis -  outlined in ‘bicaCovs.csv’ above.

9. Tpref_bica_allind_filter15. Csv – Measurements of body temperature of lizards (Abicaorum)  on the Tpref gradient –(oC – measured with thermocouple inserted into cloaca and measured every 10 seconds) – with a 15 minute adjustment period removed.

10. Tpref_diffinds.R – R code to calculated the Tpref of individuals from daset above.

11. Uncal bicao.csv and Uncal_bicaCovs.csv – same covariates as outlined above – but using uncalibrated 3d anolis model data.

12. Variables.csv and Variablesuncal.csv – variables – same as outlined above – for use to plot graphics.

No additional notes - data and code as used.