Population Numbers By New York City Neighborhood Tabulation Areas The data was collected from Census Bureaus' Decennial data dissemination (SF1). Neighborhood Tabulation Areas (NTAs), are aggregations of census tracts that are subsets of New York City's 55 Public Use Microdata Areas (PUMAs). Primarily due to these constraints, NTA boundaries and their associated names may not definitively represent neighborhoods. This report shows change in population from 2000 to 2010 for each NTA. Compiled by the Population Division – New York City Department of City Planning.

This dataset contains the New York City Population By Community Districts.The community boards of the New York City government are the appointed advisory groups of the community districts of the five boroughs. There are currently 59 community districts, including twelve in Manhattan, twelve in the Bronx, eighteen in Brooklyn, fourteen in Queens, and three in Staten Island.

New York has become one of the worst-affected COVID-19 hotspots and a pandemic epicenter due to the ongoing crisis. This paper identifies the impact of the pandemic and the effectiveness of government policies on human mobility by analyzing multiple datasets available at both macro and micro levels for New York City. Using data sources related to population density, aggregated population mobility, public rail transit use, vehicle use, hotspot and non-hotspot movement patterns, and human activity agglomeration, we analyzed the inter-borough and intra-borough movement for New York City by aggregating the data at the borough level. We also assessed the internodal population movement amongst hotspot and non-hotspot points of interest for the month of March and April 2020. Results indicate a drop of about 80% in people’s mobility in the city, beginning in mid-March. The movement to and from Manhattan showed the most disruption for both public transit and road traffic. The city saw its first case on March 1, 2020, but disruptions in mobility can be seen only after the second week of March when the shelter in place orders was put in effect. Owing to people working from home and adhering to stay-at-home orders, Manhattan saw the largest disruption to both inter- and intra-borough movement. But the risk of spread of infection in Manhattan turned out to be high because of higher hotspot-linked movements. The stay-at-home restrictions also led to an increased population density in Brooklyn and Queens as people were not commuting to Manhattan. Insights obtained from this study would help policymakers better understand human behavior and their response to the news and governmental policies.

Urbanization exposes species to novel environments and selection pressures that may change morphological traits within a population. We investigated how the shape and size of crania and mandibles changed over time within a population of brown rats (Rattus norvegicus) living in Manhattan, New York, USA, a highly urbanized environment. We measured 3D landmarks on the cranium and mandible of 62 adult individuals sampled in the 1890s and 2010s. Static allometry explained approximately 22% of shape variation in crania and mandible datasets, while time accounted for approximately 14% of variation. We did not observe significant changes in skull size through time or between the sexes. Estimating the P-matrix revealed that directional selection explained temporal change of the crania but not the mandible. Specifically, rats from the 2010s had longer noses and shorter upper molar tooth rows, traits identified as adaptive to colder environments and higher quality or softer diets, respectively. Our results highlight the continual evolution to selection pressures. We acknowledge that urban selection pressures impacting cranial shape likely began in Europe prior to the introduction of rats to Manhattan. Yet, our study period spanned changes in intensity of artificial lighting, human population density, and human diet, thereby altering various aspects of rat ecology and hence pressures on the skull.

Methods 3D landmark data was taken with a microscribe on brown rat crania and mandibles. Dorsal and ventral landmarks were merged into a single shape using MorphoJ. Data were analyzed in R with the geomorph package.

SFS of ddRAD-Seq data for 248 rats from NYC included for estimation of Ne.