Multi-Parametric Assessment of Avian Biodiversity and Anthropogenic Disturbance for Conservation Prioritization in Belize

Scotty Clark

Background: Anthropogenic climate change and rising
levels have accelerated global warming, causing severe disruptions to Belizean ecosystems through
sea-level rise and habitat fragmentation. To mitigate these impacts, identifying high-value land for
protected status is a critical conservation priority for maintaining medicinal biodiversity and preventing
zoonotic disease spillover.
Objective: This study evaluated four candidate land parcels—Belmopan, Cockscomb Basin, Gallon
Jug, and Punta Gorda—to determine the optimal site for acquisition based on ecological health and
long-term sustainability.
Methods: Avian populations served as primary biological indicators. Biodiversity was quantified using
taxonomic richness (s), the Shannon-Wiener index (H), dominance (D), and equitability (J). These
metrics were integrated with geospatial land-use data to assess anthropogenic pressure, including
agricultural encroachment and soil stability risks.
Results: Preliminary analysis excluded Belmopan and Gallon Jug due to insufficient taxonomic
richness (S<100). While Punta Gorda exhibited the highest immediate biodiversity (S = 240; H =
5.446; J = 0.9936), it faced extreme anthropogenic pressure with 50% land conversion for
agriculture. Conversely, Cockscomb Basin demonstrated robust biodiversity ( S = 240, H =4.411);
with significantly lower agricultural impact (30%) and superior habitat complexity, including lowland
lake and pine forest ecosystems. Statistical differentiation in dominance (D) values—0.00443 for Punta
Gorda versus 0.05034 for Cockscomb Basin—suggested more resilient population clusters in the latter
despite lower evenness.
Conclusion: Cockscomb Basin was identified as the superior conservation candidate due to its higher
ecological integrity and lower risk of future degradation. This study underscores the necessity of
combining point-in-time biodiversity indices with longitudinal land-use data and chemical monitoring,
such as soil pH and contamination tracking, to ensure sustainable environmental preservation.