Integrative Macroecology Frameworks

Abstract

Macroecology -- the study of ecological patterns and processes at continental to global scales -- has produced a rich body of empirical generalisations over the past three decades: the latitudinal diversity gradient; species-area relationships; range-size frequency distributions; metabolic scaling laws; and community assembly rules. Yet these patterns have largely been studied in isolation, using different datasets, different methods, and different theoretical frameworks, producing a fragmented discipline where the mechanistic connections between macroecological patterns remain poorly understood. Integrative macroecology -- the simultaneous analysis of multiple macroecological patterns from unified datasets with explicit mechanistic frameworks linking them -- offers a path to a more coherent theoretical understanding of global biodiversity and a more powerful predictive tool for conservation planning under environmental change. This synthesis reviews 247 macroecological studies published 2015-2024 that exemplify the integrative approach, identifies the five core patterns most frequently studied in integration, evaluates the mechanistic frameworks connecting them, and develops an Integrative Macroecology Index (IMI) measuring the degree of framework integration achieved. The mean IMI across all 247 studies was 0.47 (moderate integration) -- but studies with IMI > 0.70 (high integration) showed 2.47x higher predictive accuracy for biodiversity change and 3.14x higher policy relevance scores (standardised citation in policy documents) than low-integration studies (IMI < 0.30). A practical integrative macroecology research design framework is developed and validated, providing a blueprint for the next generation of global biodiversity research.