Mixed policies give more options in multifunctional tropical forest landscapes

Law, Elizabeth (2016): Mixed policies give more options in multifunctional tropical forest landscapes. The University of Queensland. Dataset. doi:10.14264/uql.2016.113

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Project name Mixed policies give more options in multifunctional tropical forest landscapes
Project description
1. Tropical forest landscapes face competing demands for conserving biodiversity, sustaining ecosystem services and accommodating production systems such as forestry and agriculture. Land-sparing and land-sharing have emerged as contrasting strategies to manage trade-offs between production and biodiversity conservation. Both strategies are evident in land management policies at local to international scales. However, studies rarely report the impacts of these strategies, assessed for multiple stakeholders and multiple ecosystem services, particularly in real landscapes.
2. Using a case study from a high-priority region for forest protection, restoration, and rural development in Central Kalimantan, Indonesia, we analysed the potential outcomes under ten alternative policy scenarios, including land-sharing, land-sparing, and mixed strategies. We used a novel optimization process integrating integer programming with conservation planning software (Marxan with Zones) to identify production possibility frontiers (PPFs), highlighting the trade-off between smallholder agriculture and oil palm, subject to achievement of a set of carbon, timber, and biodiversity conservation targets.
3. All policy scenarios modelled proved to be capable of achieving all targets simultaneously. Most strategies resulted in an expansion of the PPF from the baseline, increasing the flexibility of land allocation to achieve all targets. Mixed strategies gave the greatest flexibility to achieve targets, followed closely by land-sparing. Land-sharing only performed better than the baseline when no yield penalties were incurred, and resulted in PPF contraction otherwise. Strategies assessed required a minimum of 29–37% to be placed in conservation zones, notably protecting the majority of remaining forest, but requiring little reforestation.
4. Policy implications. Production possibility frontiers (PPFs) can evaluate a broad spectrum of land-use policy options. When using targets sought by multiple stakeholders within an ecosystem services framework, PPFs can characterize biophysical, socio-economic, and institutional dimensions of policy trade-offs in heterogeneous landscapes. All ten policy strategies assessed in our case study are biophysically capable of achieving all stakeholder objectives, provided at least 29–37% of the landscape is conserved for biodiversity. This novel methodological approach provides practical options for systematic analysis in complex, multifunctional landscapes, and could, when integrated within a larger planning and implementation process, inform the design of land-use policies that maximize stakeholder satisfaction and minimize conflict.
Contact name Law, Elizabeth
Contact email e.law@uq.edu.au
Creator name Law, Elizabeth
Creator(s) role Chief investigator
Dataset name Mixed policies give more options in multifunctional tropical forest landscapes
Dataset description
This archive stores data utilised in:

Mixed policies give more options in multifunctional tropical forest landscapes
Law E.A., Bryan B.A., Meijaard E., Mallawaarachchi T., Struebig M.J., Watts M., Wilson K.A.
Journal of Applied Ecology 2016

Corresponding author:
Elizabeth A. Law*
The University of Queensland, School of Biological Sciences

Date: Jan 18, 2016

Along with this txt file, this archive contains five csv files included, and one folder containing a shape file. These are in the typical format required for input into Marxan with Zones, available from http://www.uq.edu.au/marxan/ (also see new cloud development on Marxan.net). The data time frames relate to a start year of 2008 (see associated publication for further details.

Readme.txt - this document
Zones.csv - contains zone identification numbers (zoneid) and names (zonenames)
FeatureTargets.csv - contains feature id (id), the targets (target; units are specified in supplementary material), species penalty factor (spf; weighting number to determine if the feature is considered as an optimisation threshold constraint, 1, or not, 0), and feature names (name; features 1-9 and 19-20 represent primate species, 10-14 forest types, and 15-17 production values smallholder agriculture, timber, and oil palm, and 18 carbon emissions reduction.
Extant.csv - contains planning unit id (pu), the extant class (class; using descriptive codes), and the area (area.ha, in hectares).
PuVsFeatures.csv - for every planning unit and feature combination, the 'amount' gives the maximum possible achievement for that feature in that planning unit. Units of measurement are indicated in the main text/supplementary methods and associated papers detailing data development.
BaselineZoneContributions.csv - for every zone, planning unit, and feature combination (identified using zoneid, puid, featid codes found in their respective files), this gives the fraction of the full amount possible to achieve within that pu for that feature.
Pulayer folder - contains a shape file created in arcgis for the planning units. Coordinate reference system is WGS 84 / UTM zone 49S. One column in the attribute table, indicating the planning unit number (pu).
Access conditions Open Access
Licencing and terms of access Creative Commons Attribution noncommercial no derivatives

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ANZSRC Field of Research (FoR) Code 1402 Applied Economics
0502 Environmental Science and Management
DOI 10.14264/uql.2016.113
Type of data Data
CSV files
Language eng
Collection start date 2010-01-01
Collection end date 2014-01-01
Time coverage start date 2008-01-01
Time coverage end date 2008-01-01
Keyword Borneo
Ex-Mega Rice Project
Ecosystem services
Land use
Geographic co-ordinates

113.584900,-3.436658 113.887024,-3.436658 114.062805,-3.354405 114.337463,-3.480523 114.853821,-2.454693 114.875793,-2.037534 113.996887,-1.955187 114.007874,-2.339438 114.172668,-2.487621 113.919983,-3.008870 113.573914,-3.140516 113.584900,-3.436658

Collection type Dataset
Publisher The University of Queensland
Publication Year 2016
Copyright notice 2016, The University of Queensland

Document type: Data Collection
Collections: Research Data Collections
School of Biological Sciences Publications
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Created: Fri, 18 Mar 2016, 22:41:28 EST by Elizabeth Law