Socioeconomic status–biodiversity associations are widely reported in cities. However, most studies remain correlational and cannot distinguish whether socioeconomic status drives biodiversity change, biodiversity shapes socioeco-nomic outcomes, or whether observed patterns reflect biodiversity gains versus losses. We propose a unifying framework organizing established mechanisms from diverse urban research into four hypothesized causal pathways: (A) investment-driven biodiversity enhancement, (B) disinvestment-driven biodi-versity degradation, (C) biodiversity-driven socioeconomic improvement, and (D) biodiversity loss reinforcing socioeconomic decline. This framework supports pathway-specific study designs and helps practitioners anticipate whether biodiversity interventions will reduce or exacerbate inequality. Shifting from pattern description to mechanism identification is essential for credible inference and for informing urban planning and governance interventions aimed at reducing environmental inequality.
Socioeconomics and biodiversity in cities: moving beyond patterns to mechanisms
Chamberlain, Dan
In corso di stampa
Abstract
Socioeconomic status–biodiversity associations are widely reported in cities. However, most studies remain correlational and cannot distinguish whether socioeconomic status drives biodiversity change, biodiversity shapes socioeco-nomic outcomes, or whether observed patterns reflect biodiversity gains versus losses. We propose a unifying framework organizing established mechanisms from diverse urban research into four hypothesized causal pathways: (A) investment-driven biodiversity enhancement, (B) disinvestment-driven biodi-versity degradation, (C) biodiversity-driven socioeconomic improvement, and (D) biodiversity loss reinforcing socioeconomic decline. This framework supports pathway-specific study designs and helps practitioners anticipate whether biodiversity interventions will reduce or exacerbate inequality. Shifting from pattern description to mechanism identification is essential for credible inference and for informing urban planning and governance interventions aimed at reducing environmental inequality.| File | Dimensione | Formato | |
|---|---|---|---|
|
Reynolds et al. 2026 TREE.pdf
Accesso aperto
Tipo di file:
PDF EDITORIALE
Dimensione
778.85 kB
Formato
Adobe PDF
|
778.85 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



