Precipitation gradients drive high tree species turnover in the woodlands of eastern and southern Africa

Savannas cover one-fifth of the Earth's surface, harbour substantial biodiversity, and provide a broad range of ecosystem services to hundreds of millions of people. The community composition of trees in tropical moist forests varies with climate, but whether the same processes structure communities in disturbance-driven savannas remains relatively unknown. We investigate how biodiversity is structured over large environmental and disturbance gradients in woodlands of eastern and southern Africa. We use tree inventory data from the Socio-Ecological Observatory for Studying African Woodlands (SEOSAW) network, covering 755 ha in a total of 6780 plots across nine countries of eastern and southern Africa, to investigate how alpha, beta, and phylogenetic diversity varies across environmental and disturbance gradients. We find strong climate-richness patterns, with precipitation playing a primary role in determining patterns of tree richness and high turnover across these savannas. Savannas with greater rainfall contain more tree species, suggesting that low water availability places distributional limits on species, creating the observed climate-richness patterns. Both fire and herbivory have minimal effects on tree diversity, despite their role in determining savanna distribution and structure. High turnover of tree species, genera, and families is similar to turnover in seasonally dry tropical forests of the Americas, suggesting this is a feature of semiarid tree floras. The greater richness and phylogenetic diversity of wetter plots shows that broad-scale ecological patterns apply to disturbance-driven savanna systems. High taxonomic turnover suggests that savannas from across the regional rainfall gradient should be protected if we are to maximise the conservation of unique tree communities

Improving peer review with ACORN: ACO algorithm for Reviewer’s Network

Peer review, our current system used by journals and conferences to determine which papers to accept and which to reject, has limitations that impair the quality of scientific communication. Under the current system, reviewers have only a limited amount of time to devote to evaluating papers and each paper receives an equal amount of attention regardless of how good the paper is. We propose to implement a new system for computer science peer review based on ant colony optimization (ACO) algorithms. In our model, each reviewer has a set of ants that goes out and finds articles. The reviewer reviews the articles the ants bring and the ant deposits pheromone that is proportional to the quality of the review. The reviewer assesses the paper according to the criteria specified by the conference organizers. Each subsequent ant then samples the pheromones and probabilistically selects the next article based on the strength of the pheromones. We used an agent-based model to determine if an ACO-based paper selection system will direct reviewers ’ attention to the best articles and if the average quality of papers increases with each round of reviews. We will also conduct an experiment in conjunction with the Computer Science Graduate Student Association conference and compare the results of our simulation