Context <p>Waterbird diversity, critical for wetland ecosystem health, is increasingly threatened by multi-scale habitat degradation, including hydrological disconnection, wetland fragmentation, and landscape homogenization. Research has traditionally addressed these factors in isolation, which limits our understanding of their coupled-system effects on waterbird diversity.</p> Objectives <p>This study addresses this gap by analyzing how waterbird diversity is collectively driven by the coupled synergies and trade-offs among three landscape components: water network connectivity, wetland morphological patterns, and the landscape context.</p> Methods <p>We employed Generalized Additive Models on 11-year (2010–2020) multi-source waterbird richness data, sampled across 801 50&#xa0;km-side hexagonal grids, to quantify responses to water network connectivity (via Graph Theory), wetland morphological patterns (via MSPA), and landscape context metrics (including landscape diversity and non-habitat disturbance landscapes).</p> Results <p>Water connectivity shows non-linear effects, where moderate connectivity optimizes richness while excessive levels limit growth through diminishing marginal utility. Richness peaks in landscapes with intermediate wetland core areas, suggesting that increasing area alone is insufficient. Conversely, higher landscape diversity (particularly wetland diversity) linearly increases richness, but the negative impacts of disturbance landscapes require vigilance.</p> Conclusions <p>We conclude that these operate as a multi-level, coupled system of synergies and trade-offs on waterbird diversity: water connectivity supports resource accessibility, wetland morphology shapes habitat quality, and landscape diversity enhances supplementary resources. This research provides a scientific reference for waterbird diversity conservation strategies to shift from maximizing single metrics to optimizing this complex systemic balance.</p>

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How water connectivity, wetland morphology, and landscape context collectively shape waterbird diversity?

  • Xueman Xing,
  • Qingyan Sun,
  • Ruilin Wang,
  • Keming Ma

摘要

Context

Waterbird diversity, critical for wetland ecosystem health, is increasingly threatened by multi-scale habitat degradation, including hydrological disconnection, wetland fragmentation, and landscape homogenization. Research has traditionally addressed these factors in isolation, which limits our understanding of their coupled-system effects on waterbird diversity.

Objectives

This study addresses this gap by analyzing how waterbird diversity is collectively driven by the coupled synergies and trade-offs among three landscape components: water network connectivity, wetland morphological patterns, and the landscape context.

Methods

We employed Generalized Additive Models on 11-year (2010–2020) multi-source waterbird richness data, sampled across 801 50 km-side hexagonal grids, to quantify responses to water network connectivity (via Graph Theory), wetland morphological patterns (via MSPA), and landscape context metrics (including landscape diversity and non-habitat disturbance landscapes).

Results

Water connectivity shows non-linear effects, where moderate connectivity optimizes richness while excessive levels limit growth through diminishing marginal utility. Richness peaks in landscapes with intermediate wetland core areas, suggesting that increasing area alone is insufficient. Conversely, higher landscape diversity (particularly wetland diversity) linearly increases richness, but the negative impacts of disturbance landscapes require vigilance.

Conclusions

We conclude that these operate as a multi-level, coupled system of synergies and trade-offs on waterbird diversity: water connectivity supports resource accessibility, wetland morphology shapes habitat quality, and landscape diversity enhances supplementary resources. This research provides a scientific reference for waterbird diversity conservation strategies to shift from maximizing single metrics to optimizing this complex systemic balance.