Biome-BGC MuSo model outputs of net ecosystem production, dry matter and water use efficiency for New Zealand under land-use scenarios

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Authors: Elizabeth Keller
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Abstract

New Zealand national annual mean net ecosystem production (gC m-2 yr-1), dry matter (kg ha-1 yr-1) and water use efficiency (gross primary production divided by evapotranspriation; gC mm-1) modelled with the Biome-BGC MuSo model v6.1 (Hidy et al., 2016, 2022), for six types of landcovers: dairy pasture, sheep/beef pasture, ungrazed grasslands, exotic needleleaf forest, evergreen broadleaf forest, and shrub, over ten years 2006-2015. The "dairy" and "sheep/beef" model ecophysical parameters were calibrated against eddy covariance data from five sites in New Zealand (Bukosa et al., 2025). For all other landcovers, default parameters were used. The baseline landcover is based on the New Zealand land cover database v5.0 (LCDBv5). The four land use scenarios consist of different afforestation strategies and involve replacing grasslands with exotic needleleaf forest (pine) in different locations: 1) “blanket extended” afforestation to maximize carbon sequestration (sc1), 2) “optimized” afforestation to limit downslope transport of soil and forestry debris (sc2), 3) “optimized” afforestation to reserve high-producing grasslands for pastoral agriculture (sc3), and 4) “optimized” afforestation to preserve water quantity (sc4). Scenarios are described in detail in Mourot et al., submitted. The Biome-BGC MuSo model was run on a daily time step at a 0.01o (~1 km) grid resolution for all of NZ from 2006 to 2015. Climate inputs include daily minimum and maximum air temperature, precipitation, vapor pressure deficit, and solar radiation. These variables were obtained from the New Zealand Virtual Climate Station Network. Soil information (texture, pH, and rooting depth) comes from the Fundamental Soil Layers database, re-gridded to match the VCSN data.

Fields of Study & Subjects

Plant Water Relations and Carbon Dynamics Land Use and Ecosystem Services Soil Carbon and Nitrogen Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
17 February 2026
Language
EN
Document type
Dataset