In this course you will become familiar with the ideas of the water-energy-food nexus and transdisciplinary thinking. You will learn to see your community or country as a complex social-ecological system and to describe its water, energy and food metabolism in the form of a pattern, as well as to map the categories of social actors. We will provide you with the tools to measure the nexus elements and to analyze them in a coherent way across scales and dimensions of analysis. In this way, your quantitative analysis will become useful for informed decision-making. You will be able to detect and quantify dependence on non-renewable resources and externalization of environmental problems to other societies and ecosystems (a popular ‘solution’ in the western world). Practical case studies, from both developed and developing countries, will help you evaluate the state-of-play of a given community or country and to evaluate possible solutions. Last but not least, you will learn to see pressing social-ecological issues, such as energy poverty, water scarcity and inequity, from a radically different perspective, and to question everything you’ve been told so far. ACKNOWLEDGEMENT Part of the results and case studies presented have been developed within two projects: MAGIC and PARTICIPIA. However, the course does not reflect the views of the funding institutions or of the project partners as a whole, and the case studies were presented purely with an educational and illustrative purpose.
Procedure for accounting
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來自 Universitat Autònoma de Barcelona 的課程
Sustainability of Social-Ecological Systems: the Nexus between Water, Energy and Food
11 個評分
Universitat Autònoma de Barcelona
11 個評分
從本節課中
Module 7. Applications of MuSIASEM 2.0
How can the theoretical concepts explained so far be applied to practical examples? After introducing the basic building blocks of relational analysis needed for our applications, we will look at two real case examples: a nexus analysis of vegetable production in Almeria, and of a wind-powered desalination plant in the Canary Islands. By the end of this week you should be able to build processors and set up nexus analyses.
與講師見面
Mario GiampietroICREA Research Professor
Institute of Environmental Science and Technology (ICTA)
Andrea SaltelliGuest researcher
Institute of Environmental Science and Technology (ICTA)
Tarik SerranoPost-Doc Researcher
Institute of Environmental Science and Technology (ICTA)
Hello again. We are now moving to the second session
in which we are talking about how can we analyze the Nexus of our farming system.
And we are looking at the cases that are in southern Spain that is that Almeria region.
In the previous session, we just framed a little bit the problem and
then the problem of study in the area.
And we also introduced what
was the difficulty of analyzing the Nexus at this regional level.
In this second session,
we are going to explain how can we build
a multi-level accounting of the Nexus values in a tool of processor.
So if you recall, we ended up the previous session with
this question about how can we integrate the different dimensions,
analytical levels and boundaries in a Nexus analysis.
And the answer to this question that I propose is that we can use
processes as tools when doing
analysis and we can connect the different analytical levels by patterns.
And I'll explain later what this means.
We are going to keep in this lesson
the question of the different boundaries
because in 10 minutes I cannot explain you everything,
although we will tackle it a little bit in the next session.
Okay.
So we look at the food production system of the farming system.
In order to analyze it with processor,
we can follow four steps.
The first step is that we need to define
what are the analytical levels that we want to consider.
The second step is that we need to define typologies
of what are we looking at in each of the different levels.
The third step is to define the processor for the lowest level,
because I am proposing in this session a bottom-up accounting.
We could also go for a top-down accounting and then build
a processor for the upper level and move down to the lower level,
but we are going to do the other way around.
Finally, we will upscale the processors from
the lowest level to the upper levels by different patterns.
So let's go step-by-step.
First, I wanted to say that the two first steps are pre-analytical steps,
are pre-analytical steps that we say
and require a set of choices of how to frame your analysis.
And that will shape whatever happens in the rest of it.
So the third and fourth step vary according to
how you decide to design step one and step two.
Yes. So first step, define analytical levels.
I have shown you already this graph.
This one was my decision when approaching this case study of Almeria,
to go - to define the lowest level at
the processes of production of different crops at the local level.
The second step would be the farms,
the third level will be
the different Agrarian regions that are within Almeria and my upper level is Almeria.
I am going to build that content from the lower lever to the upper level;
this is bottom-up accounting.
And I would like to emphasize the fact that you can decide any other type of a structure,
of multi-level structure, that you want to approach.
And precisely, it is this decision that will shape what you're going to look at and
the results of the accounting will be totally different, okay?
The second step in the analysis was to define typologies at the different level.
So if we go from the lower level, n minus three,
there was processes, production of the different crops.
I'm going to consider two different production systems, okay?
Greenhouses and open fields,
because I know that these are the two production systems
of vegetables in an area and I know which are the crops that each of them is producing.
Going to the next level, the farms,
I'm going to consider three types of
farming systems according to a criteria of the number of seasons of production.
So in the case of the greenhouses,
I know there are greenhouses producing only for one long season,
whereas there are others that have crop rotation.
In the case of open fields,
they only do one season of production.
And these results are in three typologies of farming systems,
each of which produces different types of crops at the lower level.
If we go one level above to the Agrarian regions,
we'll define six typologies of regions in this case by a geographic criterion,
because I know that that needs to take a structure of every culture in Almeria,
response to the geographical criterion.
This - again, this level and the typologies considered as Agragrian region,
can be defined with any other type of criterion.
Criterion for the finish of the typologies are semantics,
are political decision of the analysis
depending on the case you study and depending on what objective is.
For instance, you could do a statistical analysis of the different type of
farming systems of the lower level and cluster them in order to obtain - to
see which of the clusters defining
Agrarian regions that might or not respond to geographic evaluation.
Third step is to define the processor for the lowest levels because,
as I said, we are going to build them from bottom-up.
Okay. So if you recall, the processor is an array of
different variables that are categorized with three different categories.
We differentiate between inputs to the system and
outputs and we differentiate between internal inputs and outputs - that
mean those that belong inside the socioeconomic system and external inputs
and outputs - that are those representing
the relations between the production system and the ecosystems.
And finally, the third category is between flows and funds.
So this is how I define the processor for the lowest level.
There was processors of production of different crops.
This is an example of a processor in the form of our table.
I didn't use that representation, just the table,
of the production of tomatoes in open fields.
In here, I've filled a set of
variables such as the requirements of the different nutrients,
the pesticides, the water requirements,
the labor, et cetera.
Okay. So the variables have different values,
whether this tomato is produced in an open field or in a greenhouse.
Okay. So I repeat - and I had to collect and generate
this data for each crop in each production system - there
was 18 greenhouses and eight in open fields.
As a result, I have 16 different processors with the same variables and different values.
So how to decide which variables should be included in the processor?
This really depends.
This is another pre-analytical choice that depends on the objective of your case study.
As you have seen,
I didn't include any variables related to energy because in my case,
I was not so much focused on it;
but if you are interested in which is
the energy consumption of different production systems,
you definitely need to include energy variables.
Finally, in this step,
another important point is how to quantify the variables in
the processor and this is done by using different processes,
depending on the variable.
There are some variables that you might find in statistical data sources,
such as, for instance,
the labor that is required for different systems of production.
Some others you might sample the region and survey to
collect primary data and some others are
difficult to even collect and measure from levels,
such as nitrogen pollution.
You probably need to use different models,
hydrological models, effusive pollution models, to quantify it.
Moreover, some of them will come from other processors if
you are analyzing an entailment of other work as has been shown in the previous session.
Let's move to the final step.
The final step is to do the scaling up.
This means to go from the level n minus three to
the level n minus two of farming system and to the level n minus three.
To do so, we need to establish a competitive relation between
each typology of farming system and the typology of the production process.
This is what I mean by a pattern.
So in this slide,
I show you an example of what a pattern and an upscaling is;
in this case from moving from the crop production process to the farming system.
So the farm I had to find the farm type two,
as farm that only grows vegetables in their greenhouses and
that produces three different type of
crops in a portion of their land use as the one that I am showing, okay?
So 50 percent of the land in this farm type is devoted to aubergine production,
42 to pepper production and 43 to tomato production.
So the pattern means,
what is the pattern of land use to - devoted to each type of crop within my farm.
And the upscaling is a simple weighted average
of each of the processors for the three crops containing this pattern,
to the processor of the farm.
I can repeat this for farm type one,
farm type two and farm type three by analyzing which are the land use patterns,
defined by the different production of
crops production systems at the level n minus three into the level n minus two.
Once again, if I want to go from n minus two to n minus one,
I would have to analyze what is the pattern of
different farming systems contained within each of the Agrarian regions.
These patterns will obviously depend on how you have defined your typologies.
So if you define a different type of farming types with a criterion, for instance,
differentiated which are high-water intensive versus which are low-water intensive,
the upscaling and the results of the upscaling would be different.
