A spatial simulation model to explore the long-term dynamics of podocarp-tawa forest fragments, northern New Zealand
Authored by George L W Perry, Narkis S Morales
Date Published: 2017
DOI: 10.1016/j.ecolmodel.2017.04.007
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Abstract
Understanding the interactive effects of fragmentation and invasive
species on forest dynamics requires a long-term perspective because they
are difficult to assess in the medium- to long-term using observational
or experimental data alone. In such settings ecological models have an
important role to play. Here we describe the implementation of a
spatially explicit individual-based model (SEIBM) representing the
dynamics of small forest fragments in northern New Zealand based on
empirical data collected in the region. In addition, we performed a
baseline analysis to determine how well the model captured podocarp-tawa
forest dynamics, and compared its performance with stand structure data
obtained from. an unfragmented forest in northern New Zealand. We used
sensitivity analysis to determine how sensitive the model was to changes
in the input parameters. In addition, we simulated different scenarios
under diverse management conditions to explore the model's potential as
a management tool. The model captures the stand structural
characteristics of the fragments reasonably well but under-predicts
stand basal area, suggesting that it does not represent the long-term
suppression of some canopy tree species adequately. Although some
refinement is needed to improve its performance, we believe that the
model presented here is a useful tool for management purposes and for
the assessment of the long term viability of forest fragments. The model
can help inform managers and decision-makers regarding the long-term
persistence of podocarp-tawa forest patches. (C) 2017 Elsevier B.V. All
rights reserved.
Tags
Management
Forest management
Deforestation
Impacts
Sensitivity-analysis
Succession
Vegetation dynamics
Tree growth
Island
Forest fragments
Spatially explicit individual-based model
Long-term
dynamics
Long-term viability
Beilschmiedia-tawa
Landscape
model