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@Article{Salecker2019,
  author   = {Salecker, Jan and Dislich, Claudia and Wiegand, Kerstin, and Meyer, Katrin M. and Pe´er, Guy},
  title    = {EFForTS-LGraf: A Landscape Generator for Creating Smallholder-Driven Land-Use Mosaics},
  journal  = {EFForTS Discussion Paper Series},
  year     = {2019},
  volume   = {29},
  url_pdf  = {http://webdoc.sub.gwdg.de/pub/mon/sfb990/dp-29.pdf},
  abstract = {Spatially-explicit  simulation  models  are  commonly  used  to  study  complex  ecological and  socio-economic  research  questions.  Often  these  models  depend  on  detailed  input  data,such  as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf  that  provides  artificially-generated  land-use  maps  of  agricultural  landscapes  shaped  by  small-scale  farms.  EFForTS-LGraf  is  a  process-based landscape  generator  that  explicitly  incorporates  the human  dimension  of  land-use  change.  The  model  generates  roads  and  villages  that  consist  of smallholder  farming  households.  These  smallholders  use  different  establishment  strategies  to  create fields  in  their  close  vicinity.  Crop  types  are  distributed  to  these  fields  based  on  crop  fractions  and specialization  levels. EFForTS-LGraf  model  parameters  such  as  household  area  or  field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the  abstract  parameters  of  neutral  landscape  generators.  We  tested  the  model  using  oil  palm  and rubber  farming  in  Indonesia  as  a  case  study  and  validated  the  artificially-generated  maps  against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied  simulation  experiment  on  landscape-level  effects  of  increasing household  area  and  crop specialization  revealed  that  larger  households  with  higher  specialization  levels  led  to  spatially  more homogeneous  and  less  scattered  crop  type  distributions  and  reduced  edge  area  proportion.  Thus, EFForTS-LGraf  can  be  applied  both to  generate  maps  as  inputs  for  simulation  modelling  and  as  a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems.},
  comment  = {public},
  keywords = {landscape generator; agent-based model; ABM; NetLogo; process-based; Indonesia},
  url      = {http://webdoc.sub.gwdg.de/pub/mon/sfb990/dp-29.pdf},
}

Spatially-explicit simulation models are commonly used to study complex ecological and socio-economic research questions. Often these models depend on detailed input data,such as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf that provides artificially-generated land-use maps of agricultural landscapes shaped by small-scale farms. EFForTS-LGraf is a process-based landscape generator that explicitly incorporates the human dimension of land-use change. The model generates roads and villages that consist of smallholder farming households. These smallholders use different establishment strategies to create fields in their close vicinity. Crop types are distributed to these fields based on crop fractions and specialization levels. EFForTS-LGraf model parameters such as household area or field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the abstract parameters of neutral landscape generators. We tested the model using oil palm and rubber farming in Indonesia as a case study and validated the artificially-generated maps against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied simulation experiment on landscape-level effects of increasing household area and crop specialization revealed that larger households with higher specialization levels led to spatially more homogeneous and less scattered crop type distributions and reduced edge area proportion. Thus, EFForTS-LGraf can be applied both to generate maps as inputs for simulation modelling and as a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems.

@Article{Salecker2019a,
  author   = {Salecker, Jan and Sciaini, Marco and Meyer, Katrin M. and Wiegand, Kerstin},
  title    = {The nlrx R package: A next-generation framework for reproducible NetLogo model analyses},
  journal  = {Methods in Ecology and Evolution},
  year     = {2019},
  volume   = {10},
  pages    = {1854--1863},
  abstract = {1.Agent-based models find wide application in all fields of science where large scale patterns emerge from properties of individuals. Due to increasing capacities of computing resources it was possible to improve the level of detail and structural realism of next-generation models in recent years. However, this is at the expense of increased model complexity, which requires more efficient tools for model exploration, analysis and documentation that enable reproducibility, repeatability and parallelisation. NetLogo is a widely used environment for agent-based model development, but it does not provide sufficient built-in tools for extensive model exploration, such as sensitivity analyses. One tool for controlling NetLogo externally is the R-package RNetLogo. However, this package is not suited for efficient, reproducible research as it has stability and resource allocation issues, is not straightforward to be setup and used on high performance computing clusters and does not provide utilities, such as storing and exchanging metadata, in an easy way. 2.We present the R-package nlrx, which overcomes stability and resource allocation issues by running NetLogo simulations via dynamically created XML experiment files. Class objects make setting up experiments more convenient and helper functions provide many parameter exploration approaches, such as Latin Hypercube designs, Sobol sensitivity analyses or optimization approaches. Output is automatically collected in user-friendly formats and can be post-processed with provided utility functions. nlrx enables reproducibility by storing all relevant information and simulation output of experiments in one R object which can conveniently be archived and shared. 3.We provide a detailed description of the nlrx package functions and the overall workflow. We also present a use case scenario using a NetLogo model, for which we performed a sensitivity analysis and a genetic algorithm optimization. 4.The nlrx package is the first framework for documentation and application of reproducible NetLogo simulation model analysis. This article is protected by copyright. All rights reserved.},
  comment  = {public frontpage},
  doi      = {10.1111/2041-210X.13286},
  eprint   = {https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13286},
  keywords = {agent-based modelling, individual-based modelling, reproducible workflow, R package, NetLogo},
  url      = {https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13286},
}

1.Agent-based models find wide application in all fields of science where large scale patterns emerge from properties of individuals. Due to increasing capacities of computing resources it was possible to improve the level of detail and structural realism of next-generation models in recent years. However, this is at the expense of increased model complexity, which requires more efficient tools for model exploration, analysis and documentation that enable reproducibility, repeatability and parallelisation. NetLogo is a widely used environment for agent-based model development, but it does not provide sufficient built-in tools for extensive model exploration, such as sensitivity analyses. One tool for controlling NetLogo externally is the R-package RNetLogo. However, this package is not suited for efficient, reproducible research as it has stability and resource allocation issues, is not straightforward to be setup and used on high performance computing clusters and does not provide utilities, such as storing and exchanging metadata, in an easy way. 2.We present the R-package nlrx, which overcomes stability and resource allocation issues by running NetLogo simulations via dynamically created XML experiment files. Class objects make setting up experiments more convenient and helper functions provide many parameter exploration approaches, such as Latin Hypercube designs, Sobol sensitivity analyses or optimization approaches. Output is automatically collected in user-friendly formats and can be post-processed with provided utility functions. nlrx enables reproducibility by storing all relevant information and simulation output of experiments in one R object which can conveniently be archived and shared. 3.We provide a detailed description of the nlrx package functions and the overall workflow. We also present a use case scenario using a NetLogo model, for which we performed a sensitivity analysis and a genetic algorithm optimization. 4.The nlrx package is the first framework for documentation and application of reproducible NetLogo simulation model analysis. This article is protected by copyright. All rights reserved.

@Article{Salecker2019b,
  author    = {Salecker, Jan and Dislich, Claudia and Wiegand, Kerstin and Meyer, Katrin M. and Pe´er, Guy},
  title     = {EFForTS-LGraf: A landscape generator for creating smallholder-driven land-use mosaics},
  journal   = {PLOS ONE},
  year      = {2019},
  volume    = {14},
  number    = {9},
  pages     = {1-24},
  month     = {09},
  abstract  = {Spatially-explicit simulation models are commonly used to study complex ecological and socio-economic research questions. Often these models depend on detailed input data, such as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf that provides artificially-generated land-use maps of agricultural landscapes shaped by small-scale farms. EFForTS-LGraf is a process-based landscape generator that explicitly incorporates the human dimension of land-use change. The model generates roads and villages that consist of smallholder farming households. These smallholders use different establishment strategies to create fields in their close vicinity. Crop types are distributed to these fields based on crop fractions and specialization levels. EFForTS-LGraf model parameters such as household area or field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the abstract parameters of neutral landscape generators. We tested the model using oil palm and rubber farming in Indonesia as a case study and validated the artificially-generated maps against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied simulation experiment on landscape-level effects of increasing household area and crop specialization revealed that larger households with higher specialization levels led to spatially more homogeneous and less scattered crop type distributions and reduced edge area proportion. Thus, EFForTS-LGraf can be applied both to generate maps as inputs for simulation modelling and as a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems.},
  comment   = {public frontpage},
  doi       = {10.1371/journal.pone.0222949},
  publisher = {Public Library of Science},
  url       = {https://doi.org/10.1371/journal.pone.0222949},
}

Spatially-explicit simulation models are commonly used to study complex ecological and socio-economic research questions. Often these models depend on detailed input data, such as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf that provides artificially-generated land-use maps of agricultural landscapes shaped by small-scale farms. EFForTS-LGraf is a process-based landscape generator that explicitly incorporates the human dimension of land-use change. The model generates roads and villages that consist of smallholder farming households. These smallholders use different establishment strategies to create fields in their close vicinity. Crop types are distributed to these fields based on crop fractions and specialization levels. EFForTS-LGraf model parameters such as household area or field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the abstract parameters of neutral landscape generators. We tested the model using oil palm and rubber farming in Indonesia as a case study and validated the artificially-generated maps against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied simulation experiment on landscape-level effects of increasing household area and crop specialization revealed that larger households with higher specialization levels led to spatially more homogeneous and less scattered crop type distributions and reduced edge area proportion. Thus, EFForTS-LGraf can be applied both to generate maps as inputs for simulation modelling and as a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems.

@Article{Paul2019,
  author   = {Paul, Carola and Reith, Esther and Salecker, Jan and Knoke, Thomas},
  journal  = {Current Landscape Ecology Reports},
  title    = {How Integrated Ecological-Economic Modelling Can Inform Landscape Pattern in Forest Agroecosystems},
  year     = {2019},
  issn     = {2364-494X},
  month    = {Nov},
  number   = {4},
  pages    = {125--138},
  volume   = {4},
  abstract = {The purpose of this review is to analyse recent advances in ecological-economic modelling designed to inform desirable landscape composition and configuration. We explore how models capture the economic and ecological consequences of landscape pattern, and potential feedbacks to the responses by policy or landholders.
Modelling approaches are becoming increasingly interlinked, coupling components of empirical-statistical modelling, spatial and bioeconomic simulation, land-use optimization and agent-based models. We analyse recent methodological advances and find that only few examples capture feedbacks between landscape pattern and decision-making.
We outline how future hybrid models could build on these recent advances by inter alia an improved representation of landscape patterns, refining the theory behind decision-making, incorporating uncertainty and reducing model complexity. We conclude that coupling recent developments in land-use optimization and agent-based models may help bridge gaps between modelling philosophies as well as parsimony vs. complexity. This fruitful field of research could help to improve understanding on the role of landscape pattern in social-ecological systems.},
  comment  = {public frontpage},
  day      = {08},
  doi      = {10.1007/s40823-019-00046-4},
  keywords = {Bioeconomic modelling Social-economic models Portfolio analysis Landscape metrics Ecosystem services Trade-offs},
  url      = {https://doi.org/10.1007/s40823-019-00046-4},
}

The purpose of this review is to analyse recent advances in ecological-economic modelling designed to inform desirable landscape composition and configuration. We explore how models capture the economic and ecological consequences of landscape pattern, and potential feedbacks to the responses by policy or landholders. Modelling approaches are becoming increasingly interlinked, coupling components of empirical-statistical modelling, spatial and bioeconomic simulation, land-use optimization and agent-based models. We analyse recent methodological advances and find that only few examples capture feedbacks between landscape pattern and decision-making. We outline how future hybrid models could build on these recent advances by inter alia an improved representation of landscape patterns, refining the theory behind decision-making, incorporating uncertainty and reducing model complexity. We conclude that coupling recent developments in land-use optimization and agent-based models may help bridge gaps between modelling philosophies as well as parsimony vs. complexity. This fruitful field of research could help to improve understanding on the role of landscape pattern in social-ecological systems.

@Article{Dislich2018,
  author    = {Dislich, Claudia and Hettig, Elisabeth and Salecker, Jan and Heinonen, Johannes and Lay, Jann and Meyer, Katrin M. and Wiegand, Kerstin and Tarigan, Suria},
  title     = {{Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs}},
  journal   = {PLOS ONE},
  year      = {2018},
  volume    = {13},
  number    = {1},
  pages     = {e0190506},
  month     = {jan},
  issn      = {1932-6203},
  url_pdf   = {http://uni-goettingen.de/docs/396ae7967961248a393e20be62750a4d.pdf},
  abstract  = {Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes.},
  comment   = {public frontpage},
  doi       = {10.1371/journal.pone.0190506},
  editor    = {Webb, Edward},
  publisher = {Public Library of Science},
  url       = {http://dx.plos.org/10.1371/journal.pone.0190506},
}

Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes.

@Article{Dislich2017,
  author   = {Dislich, Claudia and Keyel, Alexander C. and Salecker, Jan and Kisel, Yael and Meyer, Katrin M. and Auliya, Mark and Barnes, Andrew D. and Corre, Marife D. and Darras, Kevin and Faust, Heiko and Hess, Bastian and Klasen, Stephan and Knohl, Alexander and Kreft, Holger and Meijide, Ana and Nurdiansyah, Fuad and Otten, Fenna and Pe'er, Guy and Steinebach, Stefanie and Tarigan, Suria and T{\"{o}}lle, Merja H. and Tscharntke, Teja and Wiegand, Kerstin},
  title    = {{A review of the ecosystem functions in oil palm plantations, using forests as a reference system}},
  journal  = {Biological Reviews},
  year     = {2017},
  volume   = {92},
  number   = {3},
  pages    = {1539--1569},
  issn     = {1469185X},
  url_pdf  = {http://uni-goettingen.de/de/document/download/53135cfc82a2d81cf8b97e4cf12018cb.pdf/Dislich_et_al_2017_BIOLOGICAL_REVIEWS_ecosystem_functions_oil_palm_plantations.pdf},
  abstract = {ABSTRACT Oil palm plantations have expanded rapidly in recent decades. This large-scale land-use change has had great ecological, economic, and social impacts on both the areas converted to oil palm and their surroundings. However, research on the impacts of oil palm cultivation is scattered and patchy, and no clear overview exists. We address this gap through a systematic and comprehensive literature review of all ecosystem functions in oil palm plantations, including several (genetic, medicinal and ornamental resources, information functions) not included in previous systematic reviews. We compare ecosystem functions in oil palm plantations to those in forests, as the conversion of forest to oil palm is prevalent in the tropics. We find that oil palm plantations generally have reduced ecosystem functioning compared to forests: 11 out of 14 ecosystem functions show a net decrease in level of function. Some functions show decreases with potentially irreversible global impacts (e.g. reductions in gas and climate regulation, habitat and nursery functions, genetic resources, medicinal resources, and information functions). The most serious impacts occur when forest is cleared to establish new plantations, and immediately afterwards, especially on peat soils. To variable degrees, specific plantation management measures can prevent or reduce losses of some ecosystem functions (e.g. avoid illegal land clearing via fire, avoid draining of peat, use of integrated pestmanagement, use of cover crops, mulch, and compost) and we highlight synergistic mitigation measures that can improve multiple ecosystem functions simultaneously. The},
  comment  = {public},
  doi      = {10.1111/brv.12295},
  isbn     = {2015111646},
  keywords = {Elaeis guineensis,biodiversity,ecosystem functions,ecosystem services,land-use change,oil palm},
  pmid     = {27511961},
}

ABSTRACT Oil palm plantations have expanded rapidly in recent decades. This large-scale land-use change has had great ecological, economic, and social impacts on both the areas converted to oil palm and their surroundings. However, research on the impacts of oil palm cultivation is scattered and patchy, and no clear overview exists. We address this gap through a systematic and comprehensive literature review of all ecosystem functions in oil palm plantations, including several (genetic, medicinal and ornamental resources, information functions) not included in previous systematic reviews. We compare ecosystem functions in oil palm plantations to those in forests, as the conversion of forest to oil palm is prevalent in the tropics. We find that oil palm plantations generally have reduced ecosystem functioning compared to forests: 11 out of 14 ecosystem functions show a net decrease in level of function. Some functions show decreases with potentially irreversible global impacts (e.g. reductions in gas and climate regulation, habitat and nursery functions, genetic resources, medicinal resources, and information functions). The most serious impacts occur when forest is cleared to establish new plantations, and immediately afterwards, especially on peat soils. To variable degrees, specific plantation management measures can prevent or reduce losses of some ecosystem functions (e.g. avoid illegal land clearing via fire, avoid draining of peat, use of integrated pestmanagement, use of cover crops, mulch, and compost) and we highlight synergistic mitigation measures that can improve multiple ecosystem functions simultaneously. The

@Conference{Salecker2017,
  author    = {Salecker, Jan and Dislich, Claudia and Hettig, Elisabeth and Heinonen, Johannes and Lay, Jann and Meyer, Katrin M. and Wiegand, Kerstin and Tarigan, Suria},
  booktitle = {Conference Talk, esa annual meeting 2017, Portland, USA},
  title     = {{Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs}},
  year      = {2017},
  groups    = {Jana:1},
  owner     = {Jan},
  timestamp = {2018.01.25},
}

@Conference{Salecker2014,
  author    = {Salecker, Jan and Meyer, Katrin M and Wiegand, Kerstin},
  booktitle = {Poster at GfÖ annual meeting 2014, Hildesheim, Germany},
  title     = {{Black Poplar Population Persistence}},
  year      = {2014},
  groups    = {Jana:1},
  owner     = {Jan},
  timestamp = {2018.01.25},
}