The term “metacity” was introduced by the United Nations as a way to capture the increasing size of the largest urban aggregations on the planet.Previously, the term “megacity” had been the largest category of city, referring to any urban area comprising more than 10 million people.With a number of cities, such as Mexico City, Tokyo, Lagos, breaking the ceiling of 20 million inhabitants, UN Habitat chose to introduce a new term.The sequence of city size classes now includes city at the lower end, grading through increasing sizes of metropolis, megacity or hypercity, with metacity representing the largest agglomeration.
BES Co-PI Brian McGrath suggested that the emphasis on size of the city by this classification left much to be desired.For example, the metacity category included such different cities as metropolitan New York and Lagos, Nigeria.The first is a city with sanitary infrastructure, and long established control over the form and location of growth.Lagos, on the other hand, like many huge cities in the Global south, is plagued by sprawling in-migration and lack of well developed sanitary infrastructure, among other constraints.Lumping these cities together in terms of mere size fails to take account of the vast social and environmental differences that they exhibit.
A Dynamic Concept for Urban Design
Shenzhen. Copyright Brian McGrath.
McGrath pointed out that a better use of the metacity concept was to highlight the dynamic and patchy changes that cities were experiencing.If cities are considered to be complex spatial mosaics, reflecting spatially distinct changes in the buildings, infrastructure, human demography, and economic investment and activity, the idea of metacity could help focus on those things, not just mere size.A dynamic, spatially patchy metacity could just as well be shrinking as a result of declining residential density or industrial activity, as it could be growing explosively in an unplanned manner.
Metacity as a Parallel between Ecology and Urban Design
HERCULES patch mosaic, Glyndon, Baltimore.
When McGrath introduced me to the metacity concept, and its dynamic refinements, I was immediately struck by the parallels with some “meta” terms in ecology.Metapopulations and metacommunities are characterized not by size, but by being “systems of systems.”A metapopulation is a collection of spatially discrete populations of a species that may periodically be linked by migration, exchange of genes, or sharing information.Different populations in the collection can grow, shrink, or even go extinct relatively independently.Similarly, a metacommunity is a collection of different species that is represented by spatially distinct patches.Large, physically powerful disturbances are a cause of loss of different members of a collection of a particular kind of community.Likewise, metacities can comprise patches that are changing as well as patches that are relatively stable.The changing patches can be shifting in social or architectural composition, population density, access to transportation and other resources, and in many other ways.Baltimore as a city-suburban-exurban system is surely a metacity, with growth, shrinkage, economic and demographic shifts occurring in different patches across the five county metropolitan area.In other words, a metacity and various kinds of meta-ecology share important dynamic features.
So the metacity concept is an excellent way to link the concerns, theories, and activities of socio-ecological research with urban design and regional land use decisions.This concept and its power as an integrative tool is explored in a new paper by McGrath and myself.If you want to have a look at the original publication, follow this link:
https://baltimoreecosystemstudy.org/wp-content/uploads/2019/04/BES-Circle-Text.jpg00John Lagrosahttps://baltimoreecosystemstudy.org/wp-content/uploads/2019/04/BES-Circle-Text.jpgJohn Lagrosa2011-10-25 14:56:002019-04-11 12:32:14What is a Metacity?
This research was supported by funding from the NSF Long-term Ecological Research (LTER) Program. This material is based upon work supported by the National Science Foundation under Grant Nos. DEB-1637661 and DEB-1855277. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.