Food Resource Landscapes

Wed, 03 Dec 2025 00:00:00 +0000

Project Aim

Many aspects of animal behavior and life histories are have been associated to the spatial and temporal distribution of food resources. For example, in primates and other animals, the spatial concentration (clumpedness) of foods impacts competitive regimes and social structure, while seasonality of foods influences reproductive timing. Past research often relied on coarse dietary categories (e.g., leaves vs. fruit). Therefore, our goal is to develop finer-grained maps of food resource distributions to test socioecological and life-history hypotheses.

Analyses of plant phenology and distribution data from Kibale reveal strong interspecific variation in the timing and spatial patterning of leaf and fruit production. To obtain more information about this variability, we are integrating drone imagery and machine-learning classifications with long-term phenological and nutritional datasets to build dynamic, high-resolution food-resource landscapes for Kibale National Park. We will use these landscapes to quantify the spatiotemporal distribution of plant foods (e.g., seasonality, predictability, clumpedness) and to test research hypotheses about the behavior and life-histories of primates and other animal in Kibale.

For additional habitats, we aim to develop scalable, satellite-based methods to estimate canopy structure and validate them against the Kibale resource maps. Where local phenology datasets exist at other sites, we will integrate those datasets. For sites without such datasets, we will estimate fruit and leaf production from satellite time series calibrated with Kibale-based models. The outputs will be site-level estimates of clumpedness, predictability, and seasonality for key food resources.

Contact Information

Urs Kalbitzer

Phenology | Kibale Ecology and Conservation Project

Food Resource Landscapes

Project Aim

Contact Information