Influence of landscape configuration on the sediment retention of Mt. Makiling Forest Reserve, Philippines: An analysis of model-generated land cover

  • Nico R. Almarines Institute of Renewable Natural Resources, University of the Philippines Los Baños, College, Laguna, Philippines
  • Nathaniel C. Bantayan Institute of Renewable Natural Resources, University of the Philippines Los Baños, College, Laguna, Philippines
  • Canesio D. Predo Institute of Renewable Natural Resources, University of the Philippines Los Baños, College, Laguna, Philippines
  • Pastor L. Malabrigo, Jr. Department of Forest Biological Sciences, University of the Philippines Los Baños, College, Laguna, Philippines
Keywords: landscape metrics, landscape pattern, sediment retention, spatial error model

Abstract

Sediment retention is among the most important ecosystem services impacted by anthropogenic drivers of land cover change. However, there have been few efforts to gauge the impacts of land cover configuration on the total ecosystem sediment retention in a landscape. The study aims to do so by computing changes in landscape pattern metrics of catchments draining from the Mt. Makiling Forest Reserve (MMFR) using FRAGSTATS. Then, changes in sediment retention index (SRI) were modeled with the InVEST sediment delivery ratio (SDR) model. Statistical analysis of 64 landscape pattern metrics vis-à-vis SRI using a spatial error model showed eight class-level metrics statistically significant at α = 0.05. These were the edge density (ED) of built-up areas (β = -0.0039), perennial crops (β = 0.0025), and grasslands (β = 0.0102); the disjunct core area density (DCAD) annual crops (β = 0.0243), grasslands (β = -0.0064), perennial crops (β = -0.0068); and the mean radius of gyration (GYRATE) of perennial crops (β = 0.0002) and annual crops (β = 0.0003). However, despite this statistical significance, less than 5% of changes in SRI can be attributed to landscape configuration. This indicates that while landscape configuration influences sediment retention, landscape composition or land cover area remains an important predictor of sediment retention.

Published
2023-04-21