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The monthly Young Complexity Research Lunch (YCRL) is organised by the open group for Young Complexity Researchers Utrecht (YCRU), consisting of PhD candidates and postdocs at UU. This community building lunch event is designed specifically for young complexity researchers to share their complex systems science related work in a relaxing and informal settings, and to provide the opportunity to discuss challenges in Complex Systems Studies.

Hereby, we cordially invite you to the Young Complexity Researchers’ Lunch (YCRL) #26 on Wednesday 1 October (12:30-13:00) by Fleur Slegers at the Centre for Complex Systems Studies (CCSS) where you can:

• Get a free gourmet lunch with the best sandwiches you can get in the Utrecht Science Park;

• Know one young complexity researchers' work over just 30 mins;

• Contribute your professional knowledge and experiences in a relaxing and informal setting;

• Develop potential collaboration.

YCRL #26: From theory to data: a data-driven dynamical MaxEnt approach for macroecology
Leading young complexity researcher: Fleur Slegers, Quantitative Biodiversity Dynamics (QBD) research group, Department of Biology, Utrecht ľ¹Ï¸£ÀûÓ°ÊÓ

Abstract:
Ecological systems typically maintain long-term equilibrium, meaning they are constant when viewed on a large scale, despite fluctuations on a small scale (for instance, in species’ abundances and trees' metabolic rates). The Maximum Entropy Theory of Ecology (METE) has successfully predicted small-scale distributions in relatively stable ecosystems using only large-scale observables, without requiring detailed small-scale information. However, disturbances such as wildfires and droughts can upset the system's balance, and applying METE to destabilized ecosystems proves more challenging. 

A recent dynamical extension of METE connects small-scale variations in species abundances and metabolic rates to large-scale shifts; however, it has only been tested via simulations and relies on strong assumptions about small-scale mechanisms and processes. 

We introduce METimE, a new approach that builds on this dynamical extension of METE by replacing rigid assumptions with flexible, data-driven transition functions learned directly from time-series observations of ecosystems. We evaluate whether this method can precisely capture small-scale changes in population sizes and metabolic rates, and whether incorporating these transition functions into the Maximum Entropy inference leads to more accurate predictions of ecological distributions, specifically the rank-abundance distribution, which describes the distribution of individuals among species within a community.

Everyone is welcome, and please feel free to invite your colleagues/friends/classmates/students to join us.

If you would like to have the lunch arrangement, please sign up before 15:00 Tuesday 30 September.