Urban form and scale shaped the agroecology of early 'cities' in northern Mesopotamia, the Aegean and Central Europe.

Agricultural extensification refers to an expansive, low-input production strategy that is land rather than labour limited. Here, we present a robust method, using the archaeological proxies of cereal grain nitrogen isotope values and settlement size, to investigate the relationship between agricultural intensity and population size at Neolithic to Bronze/Iron Age settlement sites in northern Mesopotamia, the Aegean and south-west Germany. We conclude that urban form-in particular, density of occupation-as well as scale shaped the agroecological trajectories of early cities. Whereas high-density urbanism in northern Mesopotamia and the Aegean entailed radical agricultural extensification, lower density urbanism in south-west Germany afforded more intensive management of arable land. We relate these differing agricultural trajectories to long-term urban growth/collapse cycles in northern Mesopotamia and the Aegean, on the one hand, and to the volatility of early Iron Age elite power structures and urban centralization in south-west Germany, on the other.

Isotope evidence for agricultural extensification reveals how the world's first cities were fed.

This study sheds light on the agricultural economy that underpinned the emergence of the first urban centres in northern Mesopotamia. Using δ13C and δ15N values of crop remains from the sites of Tell Sabi Abyad, Tell Zeidan, Hamoukar, Tell Brak and Tell Leilan (6500-2000 cal bc), we reveal that labour-intensive practices such as manuring/middening and water management formed an integral part of the agricultural strategy from the seventh millennium bc. Increased agricultural production to support growing urban populations was achieved by cultivation of larger areas of land, entailing lower manure/midden inputs per unit area-extensification. Our findings paint a nuanced picture of the role of agricultural production in new forms of political centralization. The shift towards lower-input farming most plausibly developed gradually at a household level, but the increased importance of land-based wealth constituted a key potential source of political power, providing the possibility for greater bureaucratic control and contributing to the wider societal changes that accompanied urbanization.

Integrating genealogy and epidemiology: the ancestral infection and selection graph as a model for reconstructing host virus histories.

We model the genealogies of coupled haploid host-virus populations. Hosts reproduce and replace other hosts as in the Moran model. The virus can be transmitted between individuals of the same and succeeding generations. The epidemic model allows a selective advantage for susceptible over infected hosts. The coupled host-virus ancestry of a sample of hosts is embedded in a branching and coalescing structure that we call the Ancestral Infection and Selection Graph, a direct analogue to the Ancestral Selection Graph of Krone and Neuhauser [1997. Theoret. Population Biol. 51, 210-237]. We prove this and discuss various special cases. We show that the inter-host viral genealogy is a scaled coalescent. Using simulations, we compare the viral genealogy under this model to earlier published models and investigate the estimatability of the selection and infectious contact rates. We use simulations to compare the persistence of the disease with the time to the ultimate ancestor.

Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.