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Land use change-for example, the conversion of natural habitats to agricultural or urban ecosystems-is widely recognized to influence the risk and emergence of zoonotic disease in humans1,2. However, whether such changes in risk are underpinned by predictable ecological changes remains unclear. It has been suggested that habitat disturbance might cause predictable changes in the local diversity and taxonomic composition of potential reservoir hosts, owing to systematic, trait-mediated differences in species resilience to human pressures3,4. Here we analyse 6,801 ecological assemblages and 376 host species worldwide, controlling for research effort, and show that land use has global and systematic effects on local zoonotic host communities. Known wildlife hosts of human-shared pathogens and parasites overall comprise a greater proportion of local species richness (18-72% higher) and total abundance (21-144% higher) in sites under substantial human use (secondary, agricultural and urban ecosystems) compared with nearby undisturbed habitats. The magnitude of this effect varies taxonomically and is strongest for rodent, bat and passerine bird zoonotic host species, which may be one factor that underpins the global importance of these taxa as zoonotic reservoirs. We further show that mammal species that harbour more pathogens overall (either human-shared or non-human-shared) are more likely to occur in human-managed ecosystems, suggesting that these trends may be mediated by ecological or life-history traits that influence both host status and tolerance to human disturbance5,6. Our results suggest that global changes in the mode and the intensity of land use are creating expanding hazardous interfaces between people, livestock and wildlife reservoirs of zoonotic disease.

The complexity of an ecological community can be distilled into a network, where diverse interactions connect species in a web of dependencies. Species interact directly with each other and indirectly through environmental effects, however to our knowledge the role of these ecosystem engineers has not been considered in ecological network models. Here we explore the dynamics of ecosystem assembly, where species colonization and extinction depends on the constraints imposed by trophic, service, and engineering dependencies. We show that our assembly model reproduces many key features of ecological systems, such as the role of generalists during assembly, realistic maximum trophic levels, and increased nestedness with mutualistic interactions. We find that ecosystem engineering has large and nonlinear effects on extinction rates. While small numbers of engineers reduce stability by increasing primary extinctions, larger numbers of engineers increase stability by reducing primary extinctions and extinction cascade magnitude. Our results suggest that ecological engineers may enhance community diversity while increasing persistence by facilitating colonization and limiting competitive exclusion.

we've started abstracting and developing a new approach to organizational design and development called the Entrepreneurial Ecosystem Enabling Organization.

Trophic rewilding seeks to rehabilitate degraded ecosystems by repopulating them with large animals, thereby re-establishing strong top-down interactions. Yet there are very few tests of whether such initiatives can restore ecosystem structure and functions, and on what timescales. Here we show that war-induced collapse of large-mammal populations in Mozambique's Gorongosa National Park exacerbated woody encroachment by the invasive shrub Mimosa pigra-considered one of the world's 100 worst invasive species-and that one decade of concerted trophic rewilding restored this invasion to pre-war baseline levels.

A microbial community is a complex, dynamic system composed of hundreds of species and their interactions, they are found in oceans, soil, animal guts and plant roots. Each system feeds the Earth's ecosystem and their own growth, as they each have their own metabolism that underpin biogeochemical cycles. The same community-level metabolic rates are exploited in biotechnology for water treatment and bioenergy production from organic waste, thus the ability to capture microbial growth rates and metabolic activities within the communities is key for modeling of planetary ecosystem dynamics, animal and plant health and biotechnological waste valorzation.

If you want to understand an ecosystem, look at what the species within it eat. In studying food webs-how animals and plants in a community are connected through their dietary preferences-ecologists can piece together how energy flows through an ecosystem and how stable it is to climate change and other disturbances. Studying ancient food webs can help scientists reconstruct communities of species, many long extinct, and even use those insights to figure out how modern-day communities might change in the future. There's just one problem: only some species left enough of a trace for scientists to find eons later, leaving large gaps in the fossil record-and researchers' ability to piece together the food webs from the past.

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.