Marco Tulio Angulo

The paper quantifies ecosystem degradation by calculating energetic and monetary deficits needed for regeneration, showing nonlinear relationships and significant economic costs in African savannas.

This paper develops a geometric framework to show how energetic constraints shape ecological network diversity, revealing a unimodal relationship between energy supply and biodiversity.

The paper develops a method to estimate biodiversity risk metrics from species-area relationships using empirical data from forest censuses.

The paper develops a thermodynamic framework to determine the energetic boundaries of trophic systems and shows how these boundaries limit food-chain length.

The paper links power, efficiency, and bifurcations in consumer-resource systems using mathematical models and shows how ecological principles can be formalized and tested.

The paper derives a general sustainability rule using allometric scaling laws and tests it against ethnographic data from hunter-gatherer societies, finding consistent alignment with predicted sustainability corridors.

The paper introduces a deep learning framework to predict microbial community compositions from species assemblages using synthetic and experimental data.

The paper develops a method to identify sensor species in ecosystems to predict critical transitions using network structure, validated on experimental lake data.

This paper develops a network-based framework to control microbial communities by identifying driver species, validated on gut and sponge microbiota.