Land and biodiversity policies/Data uncertainties limitations: Difference between revisions

From IMAGE
Jump to navigation Jump to search
m (RinekeOostenrijk moved page Land and biodiversity policies3/Data uncertainties limitations to Land and biodiversity policies/Data uncertainties limitations without leaving a redirect: Text replace - "Land and biodiversity policies3" to "Land an...)
No edit summary
Line 1: Line 1:
{{PolicyResponsePartTemplate
{{PolicyResponsePartTemplate
|PageLabel=Data uncertainties and limitations
|PageLabel=Data, uncertainties and limitations
|Sequence=6
|Sequence=6
|Reference=Godfray et al., 2010; Leverington et al., 2010; Lambin et al., 2001;
|Reference=Godfray et al., 2010; Leverington et al., 2010; Lambin et al., 2001; Hertel, 2011;  
|Description=<h2>Uncertainties</h2>
|Description=<h2>Data, uncertainties and limitations</h2>
This section is a compilation of policies on land use and biodiversity, from a systems point of view, and with a focus on the interactions between policy areas. It should be noted that the kind of analysis described in this section contains some important uncertainties, which increase even further when the analysis covers longer scenario periods. All processes involved have been described in the respective model-specific section, together with the related uncertainties in the introduction page of this component ([[Land and biodiversity policies#Links to other parts of the model|Links to other parts of the model]]). Therefore, those uncertainties are not addressed again in this section. Instead, the most crucial uncertainties from a systems perspective are discussed  
==Uncertainties===
The type of analysis described in this section contains major uncertainties that increase with longer scenario periods. All processes involved are described in the respective model-specific component, together with the related uncertainties (see Policy intervention Tables in the parts above). The key uncertainties from a systems perspective are discussed here.


===Uncertainties in consumption===
An uncertainty with regard to agricultural demand is the shift in consumption and consumption patterns due to higher incomes, cultural preferences and urbanisation. Although consumption per person is not likely not to exceed 4,000 kcal per person per day, the proportion of animal products in the diet and the types of products will largely determine the land area needed per person. Thus, a key uncertainty is the current transition to more animal products in the diet of a increasing proportion of the world population. In addition, the possible increase in biomass use for energy plays a key role in total demand.  
For agricultural demand, the shift in consumption and consumption patterns due to higher incomes is uncertain and probably also influenced by cultural preferences and urbanisation. Although consumption per person is likely not to exceed 4,000 kcal per person per day, the share of animal products and the types of products will largely determine the size of the land area needed per person. Therefore, the result of the current transition by large parts of the world population towards more affluent diets is a crucial uncertainty. In addition, the possible breakthrough of biomass use for energy plays an important role in total demand.  


===Uncertainties in technology===
In modelling production systems, the main uncertainties are developments in productivity and yield increases. Historically, yields have increased approximately 1% annually. However, increased production and yields result from development of new technologies and breeds, and from increased adoption of existing improved management practices, both partly driven by commodity prices. Empirical data and quantitative modelling of these intensification processes are still rather poor ([[Hertel, 2011]]). In addition, the agro-economy model does not cover farmer objectives and constraints. And research and plant breeding focus on decreasing susceptibility to water scarcity, diseases and pests, but it is uncertain whether more efficient varieties can be developed. New technologies to unravel crop DNA could significantly accelerate plant breeding process (Godfray et al., 2010).  
In the modelling of production systems, the largest uncertainties concern the developments in productivity or yield increase. Historically, annual yields have been increasing by approximately 1%. Technological developments relate to research and plant breeding and yield developments also result from improved management practices. Both are driven, at least partly, by commodity prices, but empirical data and the quantitative modelling of these effects is still rather poor ([[Hertel et al., ...]]). A further complication is the fact that farmers may have objectives and constraints that are not covered in the economic model. Research and plant breeding is targeted, for example, to a decreased susceptibility to water scarcity, diseases and pests. Although it is uncertain whether varieties could be bred that are more efficient than current varieties, new technologies to unravel the DNA of crops could significantly accelerate the breeding process ([[Godfray et al., 2010]]).  


===Uncertainties in forestry===
The key uncertainty in forestry is the use of fuelwood and sources of traditional biomass, mostly due to limited data availability (Component [[Forest management]]). A substantial quantity of fuelwood is still used in developing countries, and how rapidly the shift to modern energy carriers will occur is highly uncertain (see also Component [[Air pollution and energy policies]]).
For forestry the most important uncertainty concerns the use of fuel wood and the sources of traditional biomass. Only limited data is available on these subjects ([[Forest management]]). In developed countries, a substantial amount of fuel wood is still being used, and it is highly uncertain, how fast  a full shift to modern energy carriers will occur.  
 
In land-use regulation, the effectiveness of protected areas is not always sufficient to maintain original biodiversity values ([[Leverington et al., 2010]]). IMAGE only takes account of economic processes in the agricultural sector but the complex socio-economic interactions that drive deforestation ([[Lambin et al., 2001]]) are not included. In addition, the role of national institutions in land use and land-use change is not included, although it is well known that these institutions largely define landscape and land use developments.
 
The uncertainty range changes with the time horizon of the scenario, and is greater for indicators further down the modelling chain. For example, biodiversity results are largely driven by land-use change, which is sensitive to uncertainties about land allocation and production systems, and to agricultural demand.
 
===Limitations===
The IMAGE framework may be used to analyse policy issues in different ways. Most frequently, technical interventions or assumed behavioural changes are implemented, and the results from alternative scenarios are used to answer 'what if' questions. However, the costs and policy measures to bring about such changes often cannot be modelled internally, and the feasibility of such options cannot be taken into account. Some economic instruments in the agro-economy model (e.g., a meat tax) can be modelled explicitly, and also specific policies, such as those on [[abbrTemplate|REDD+}}, biofuels, or additional protected areas, can be modelled explicitly for their economic and system-wide effects. Other important transitions, such as behavioural change cannot be modelled.  


===Uncertainties in land use regulation and  land use change===
For land-use regulation, the effectiveness of protected areas is not always sufficient to maintain original biodiversity values ([[Leverington et al., 2010]]). For land-use change, only the economic processes of the agricultural sector are taken into account. Complex socioeconomic interactions that drive deforestation ([[Lambin et al., 2001]]) are not part of the model. Likewise, the national institutional part of land use and land-use change is hardly included, although it is well-known that the institutional part largely defines the development of landscapes and land uses. 


The uncertainty range changes with the time horizon of the scenario, and is larger for indicators further down the modelling chain. For example, biodiversity results are largely driven by land-use change, which in turn is sensitive to uncertainties about land allocation and production systems, and finally to agricultural demand.


The IMAGE framework may be used to answer policy questions in different ways. Most frequently, technical interventions or assumed behavioural changes are implemented. The results from such alternative scenarios are then used to answer the respective 'what if' questions. The costs or policy measures needed to bring about such changes often cannot be modelled internally, nor can the feasibility of such options be taken into account. Only some economic instruments in the agro-economic model (e.g. a meat tax) can be modelled explicitly, and also some specific policies, such as those on [[HasAcronym::REDD+]], biofuels, or additional protected areas, can be modelled explicitly for their economic and system-wide effects. Other important transitions, such as behavioural change, can not be modelled.
}}
}}
{{ContentPartsTemplate}}

Revision as of 12:03, 16 May 2014

{{PolicyResponsePartTemplate |PageLabel=Data, uncertainties and limitations |Sequence=6 |Reference=Godfray et al., 2010; Leverington et al., 2010; Lambin et al., 2001; Hertel, 2011;

|Description=

Data, uncertainties and limitations

Uncertainties=

The type of analysis described in this section contains major uncertainties that increase with longer scenario periods. All processes involved are described in the respective model-specific component, together with the related uncertainties (see Policy intervention Tables in the parts above). The key uncertainties from a systems perspective are discussed here.

An uncertainty with regard to agricultural demand is the shift in consumption and consumption patterns due to higher incomes, cultural preferences and urbanisation. Although consumption per person is not likely not to exceed 4,000 kcal per person per day, the proportion of animal products in the diet and the types of products will largely determine the land area needed per person. Thus, a key uncertainty is the current transition to more animal products in the diet of a increasing proportion of the world population. In addition, the possible increase in biomass use for energy plays a key role in total demand.

In modelling production systems, the main uncertainties are developments in productivity and yield increases. Historically, yields have increased approximately 1% annually. However, increased production and yields result from development of new technologies and breeds, and from increased adoption of existing improved management practices, both partly driven by commodity prices. Empirical data and quantitative modelling of these intensification processes are still rather poor (Hertel, 2011). In addition, the agro-economy model does not cover farmer objectives and constraints. And research and plant breeding focus on decreasing susceptibility to water scarcity, diseases and pests, but it is uncertain whether more efficient varieties can be developed. New technologies to unravel crop DNA could significantly accelerate plant breeding process (Godfray et al., 2010).

The key uncertainty in forestry is the use of fuelwood and sources of traditional biomass, mostly due to limited data availability (Component Forest management). A substantial quantity of fuelwood is still used in developing countries, and how rapidly the shift to modern energy carriers will occur is highly uncertain (see also Component Air pollution and energy policies).

In land-use regulation, the effectiveness of protected areas is not always sufficient to maintain original biodiversity values (Leverington et al., 2010). IMAGE only takes account of economic processes in the agricultural sector but the complex socio-economic interactions that drive deforestation (Lambin et al., 2001) are not included. In addition, the role of national institutions in land use and land-use change is not included, although it is well known that these institutions largely define landscape and land use developments.

The uncertainty range changes with the time horizon of the scenario, and is greater for indicators further down the modelling chain. For example, biodiversity results are largely driven by land-use change, which is sensitive to uncertainties about land allocation and production systems, and to agricultural demand.

Limitations

The IMAGE framework may be used to analyse policy issues in different ways. Most frequently, technical interventions or assumed behavioural changes are implemented, and the results from alternative scenarios are used to answer 'what if' questions. However, the costs and policy measures to bring about such changes often cannot be modelled internally, and the feasibility of such options cannot be taken into account. Some economic instruments in the agro-economy model (e.g., a meat tax) can be modelled explicitly, and also specific policies, such as those on [[abbrTemplate|REDD+}}, biofuels, or additional protected areas, can be modelled explicitly for their economic and system-wide effects. Other important transitions, such as behavioural change cannot be modelled.


}}

    SMW::off
  1. Introduction page
  2. Agricultural demand
  3. Agricultural production system
  4. Forestry sector
  5. Land-use regulation
  6. Policy issues
  7. Data, uncertainties and limitations
  8. Overview of references
Retrieved from "https://models.pbl.nl/index.php?title=Land_and_biodiversity_policies/Data_uncertainties_limitations&oldid=22217"