Results 161 to 170 of about 6,314 (245)

Predictions From Evolutionary Theory for Urban Environments

open access: yesEvolutionary Applications, Volume 19, Issue 6, June 2026.
ABSTRACT Urbanization drives rapid and extreme environmental change, profoundly shaping the ecology and evolution of populations. In this Perspective, we call for the integration and development of evolutionary theory and empirical research through collaboration between theoretical and experimental biologists to provide new insights into urban ...
Ailene MacPherson   +13 more
wiley   +1 more source

Foliar Contributions to Methane and Nitrous Oxide Exchange in Urban Green Roof Systems

open access: yesGCB Bioenergy, Volume 18, Issue 6, June 2026.
Biochar amendment of extensive green roof substrates enhanced foliar methane (CH4) uptake (~3×) and reduced nitrous oxide (N2O) emissions across native and stonecrop vegetation. City‐scale extrapolation to Toronto's permitted green roof area indicates measurable, management‐sensitive non‐CO2 mitigation within urban green infrastructure systems ...
Md Rezaul Karim, Sean C. Thomas
wiley   +1 more source

The Social Equity of Spatial Compactness Varies by Context: Evidence From Belfast, Glasgow and Liverpool

open access: yesThe Geographical Journal, Volume 192, Issue 2, June 2026.
Short Abstract This paper examines the relationship between urban compactness and social equity across three UK cities. Using a multidimensional compactness framework and multiscale geographically weighted regression (MGWR), it analyses how demographic characteristics relate to spatial compactness at a fine scale.
Tianrui Sun, Cristian Silva
wiley   +1 more source

Optimizing LID Practices in the Genoa Urban Drainage System Based on the Community's Call for Action Through Participatory Mapping

open access: yesJournal of Flood Risk Management, Volume 19, Issue 2, June 2026.
ABSTRACT This paper presents a novel methodology for optimizing installation of low impact development practices (LIDs) in an urban hydrological catchment. This methodology helps stakeholders in deciding on what kind and area of LID must be installed in each sub‐catchment to attenuate pluvial flooding as a result of intense rain events.
Enrico Creaco   +5 more
wiley   +1 more source

Application of Deep Learning and Rain‐On‐Grid Hydrodynamic Modeling for Catchment‐Scale Flood Forecasting in Guwahati, India

open access: yesJournal of Flood Risk Management, Volume 19, Issue 2, June 2026.
ABSTRACT This study integrates deep learning‐based real‐time rainfall forecasting with hydrodynamic flood modeling to provide near real‐time predictions of urban flood inundation. The research focuses on urban Guwahati, a rapidly urbanizing city in Northeast India prone to recurrent pluvial flooding. A novel hybrid model, Multivariate Singular Spectrum
Shejule Priya Ashok, Sreeja Pekkat
wiley   +1 more source

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