Coping with feast and famine: Integrated behavioral and metabolically flexible responses of wild orangutans to ecologically driven dietary variation
Data files
Jan 21, 2025 version files 1.69 MB
-
README.md
10.95 KB
-
Vogeletal_MetabolicFlexibility_TuananOrangutans_FINAL.csv
1.68 MB
Abstract
Diet and nutrition are critical factors influencing energetics and health. Laboratory studies show that organisms adjust to changes in nutrient intake through flexible metabolic responses. While the physiological effects of nutrient balance in humans have been studied, data from closely related species living in nature are lacking. We integrate macronutrient regulation and metabolic flexibility to elucidate how wild Bornean orangutans are buffered against natural fluctuations in nutrient intakes. We found that orangutans regulate protein and regularly switch between exogenous and endogenous nutritional substrates as preferred food availability declines. When total caloric, lipid, and carbohydrate intakes decline, orangutans drew on fat and endogenous amino acids for energy. This strategy is beneficial only in the context of alternating periods of fruit scarcity and abundance. Our findings provide a direct analog for the current global obesity pandemic, which has arisen in parallel with transitions in human diets towards energy-dense, protein-dilute foods.
README: Coping with feast and famine: Integrated behavioral and metabolically flexible responses of wild orangutans to ecologically driven dietary variation
https://doi.org/10.5061/dryad.c59zw3rjx
Description of the data and file structure
Vogeletal_MetabolicFlexibility_TuananOrangutans_FINAL.csv
Access this dataset on OSF:(https://osf.io/xynj6
This file includes all of the data from 2003-2018 for all orangutans during this time period that were used for statistical analyses in this manuscript. The data file includes nutritional intakes, urinary biomarkers results, and identifying information for all orangutans included in the dataset. These data were collected at the Tuanan Orangutan Research Station in Central Kalimantan, Indonesia as part of the long-term research project. Each row in the data file represents a unique follow day.
If you are interested in using the data generated for this project and have additional questions, please contact the data owners listed on OSF (https://osf.io/xynj6. These data can be cited as:
Vogel ER, van Noordwijk M, Atmoko SSU, Alavi SE, Brittain R (2024) Integrated behavioral and metabolically flexible responses of wild orangutans to ecologically driven dietary variation. Available at: osf.io/xynj6.
NA: Not applicable
Below are the column name definitions:
Column_name | Definition |
---|---|
length_active_period_min | Length of active period in minutes from first activity to last acticity for full day follows |
ap_kcal | Total available protein (in Kcal) ingested for follow day |
prev_day_ap_kcal | Total available protein (in Kcal) ingested for the day prior to the urine sample collection if there was a full day follow |
lipid_kcal | Total lipid (in Kcal) ingested for follow day |
prev_day_lipid_kcal | Total lipid (in Kcal) ingested for the day prior to the urine sample collection, if there was a full day follow |
tnc_kcal | Total non-structural carbohydrates (in Kcal) ingested for follow day |
prev_day_tnc_kcal | Total non-structural carbohydrates (in kcal) ingested for the day prior to the urine sample collection, if there was a full day follow |
ndf_kcal_low | Total neutral detergent fiber (in kcal) ingested for follow day |
prev_day_ndf_kcal_low | Total neutral detergent fiber (in kcal) ingested for the day prior to the urine sample collection, if there was a full day follow |
total_kcal_using_ap_low_fermentation | Total energy (kcal) ingested using available protein and the low fermentation coefficifent |
prev_day_total_kcal_using_ap_low_fermentation | Total energy (kcal) ingested for the day prior to the urine sample collection, if there was a full day follow |
total_kcal_npe_low_fermentation | Total non-protein energy (in kcal) ingested for follow day |
prev_day_total_kcal_npe_low_fermentation | Total non-protein energy (in kcal) ingested for the day prior to the urine sample collection, if there was a full day follow |
npe_to_ap | ratio of non-protein energy to protein |
lipid_to_ap | ratio of lipid to available protein |
lipid_to_tnc | ratio of lipid to neutral detergent fiber |
lipid_to_ndf_low | ratio of lipid to neutral detergent fiber |
tnc_to_ap | ratio of total non-structural carbohydrates to availble protein |
tnc_to_ndf_low | ratio of total non-structural carbohydrates to neutral detergent fiber |
ap_to_ndf_low | ratio of availble protein to neutral detergent fiber |
percent_ap | percent of daily kcal in available protein |
percent_lipid | percent daily of kcal in lipids |
percent_ndf_low | percent of daily kcal in available protein |
percent_tnc | percent of Kcal in total non-structural carbohydrates |
fai | fruit availablty index (% of trees with ripe fruit) |
hi_low_quartile | high low fruit category |
pos_neg_dn | positive or negative for ketone bodies |
urea_sgcor | urea concentration (mg/dL ) corrected for specific gravity |
urea_time_collected | time the urine sample was collected |
ucp_sgcor | urinary c-peptide of insulin (pg/ml) |
ucp_time_collected | time the urine sample was collected |
dn15_result | nitrogen isotope ratio |
isotope_time_collected | time the urine sample was collected |
PREV_LIPID_TNC | The ratio of lipids to total non-structural carbohydrates ingested for the day prior to the urine sample collection, if there was a full day follow |
color | coding of data and not included in analysis |
name_focal | Numerical identifier for individual animals |
class_focal | Numerical identifier for age-sex class for individuals |
sex_focal | Numerical identifier for sex for individuals |
Code/software
This is the data file used in the analyses with the code found here: . All code for this analysis are hosted on Zenodo (https://zenodo.org/records/10451962), and all code for estimating the first derivative of splines are hosted here https://doi.org/10.5281/zenodo.7457199.
Access information
Codes for this project can be cited as: Alavi, SE. (2024). sealavi/Integrated-behavioral-and-metabolically-flexible-responses-of-wild-orangutans-to-dietary-variation-: Integrated behavioral and metabolically flexible responses of wild orangutans to dietary variation v1 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.10451962
If you are interested in using the data generated for this project and have additional questions, please contact the data owners listed on OSF (https://osf.io/xynj6. These data can be cited as:
Vogel ER, van Noordwijk M, Atmoko SSU, Alavi SE, Brittain R (2024) Integrated behavioral and metabolically flexible responses of wild orangutans to ecologically driven dietary variation. Available at: osf.io/xynj6
Methods
Behavioral observations and urine sampling of wild orangutans (Pongo pygmaeus wurmbii) were collected between 2003 – 2018 and 2004-2017 (Fig. 1A), respectively, in the Tuanan Research Area located in the Mawas Conservation Area, Central Kalimantan, Indonesia (see 34, 37 for a detailed site description). Tuanan is a peat swamp forest with a peat depth of 1-3 meters in most areas (69). Annual rainfall is between 1309.8 - 4176.0 mm with an average of 2602.4 mm, and minimum and maximum temperatures range between 20.5 °C to 32.0 °C (average 23 °C to 28.5 °C). For this study, we observed a total of 26 adult females, 48 adult flanged males, 25 adult unflanged males, 20 independent immatures, 15 weaned immatures who still traveled with their mothers (SI Appendix Table S8). All field research was approved by the Institutional Animal Care and Use Committees of Rutgers, the State University of New Jersey.
The fruit availability index (FAI) was determined from monthly monitored phenology plots spread across the study area comprising 1,522 and 3,103 tagged trees (see SI Appendix Methods). We calculated FAI as the percentage of trees in the plots with fruit each month (34, 37). High and low fruit period categories were determined by calculating the overall median from 2003-2018, which was used as the cut-off point to assign low and high fruit periods to each month.