General System Theory

Let’s travel back to the 1920s, but not in geography—in biology.

👉 The contribution of Ludwig von Bertalanffy:

He asked a very fundamental question:

Can we really understand a living organism if we study its parts in isolation?

And his answer was clear: No.

According to him:

“To truly understand the life of an organism, we must study it as a system—a network of diverse (or multifarious) parts working together.”

This thought gave birth to what we now call the General System Theory.

🔁 Expansion Beyond Biology

Initially, this theory applied only to living organisms. But soon, Bertalanffy and other thinkers realized something powerful:

Non-biological systems (like ecosystems, economies, even human societies) also behave like organisms.
They have parts, they have relationships, and they function as a whole.

So, a common pattern exists across different disciplines.
This realization led to a revolutionary idea:

Can we create a single, unified framework to study all kinds of systems—whether biological, physical, or social?

The answer was yes—and that’s what General System Theory offered.

🔬 A Unifying Framework Across Sciences

Let’s simplify.

• Each science (biology, physics, economics, geography) studies its own systems.
• But General System Theory gives us a higher-order model—an umbrella approach to analyze all these systems using common rules and methods.

This sparked an interdisciplinary approach in research—something modern science thrives on.

So, in a way:

General System Theory = Theory of General Models

It doesn’t replace individual sciences.
It gives them a shared toolkit to study complexity.

🧠 Cybernetics: The Mind of Systems

Now let’s introduce another fascinating concept—Cybernetics.

This comes from mathematics and physics, and it adds depth to system theory.

📌 What is Cybernetics?

Cybernetics is the study of regulating and self-regulating mechanisms—both in nature and technology.

Let’s take examples:

• Your body regulates its temperature—you don’t tell it what to do.
• A thermostat maintains the temperature of a room.
• Ecosystems recover balance after disturbance (to some extent).

Such systems follow programs—they act in predefined ways.
This is what we call regulation.

In nature, regulation is very precise.
In human societies, it is often imperfect—due to emotions, politics, ideologies, etc.

🔄 Feedback Loops and Interactions

Cybernetics also changes how we think about cause and effect.

Usually, we ask : What caused this outcome?

But in cybernetics, the focus shifts to interaction.

• A cause in one part of a system might loop through other parts and come back as a changed effect.
• Think of it like a ripple moving through water, hitting edges, and returning.

This is called a feedback loop.
It’s crucial in understanding complex systems like cities, climates, or economies.

🧩 Open vs Closed Systems

Now comes a very important analytical distinction:
Open Systems vs Closed Systems

Let’s define:

Type of System	Description
Open System	Interacts with its environment (real-world systems, like a landscape)
Closed System	Analyzed in isolation by assuming fixed boundaries (a simplified model)

In reality, all systems are open—they exchange energy, matter, and information with their surroundings.
But for the purpose of analysis, we often need to treat them as closed systems.

Why?
Because: To analyze something properly, we need clarity and boundaries.

So, we draw boundaries around a system to make it manageable.

🧠 The Problem of Boundaries in Geography

But here’s the twist:
In geography, drawing boundaries is not always easy.

Let’s take the example by David Harvey:

• Suppose you are analyzing a firm functioning in an economy.
• Inside the firm: production, labor, decisions—your focus.
• Outside: political changes, market dynamics, public sentiment.

If you consider only internal factors, the firm seems like a closed system.
But if you include external influences, the entire analysis changes.

So, even in simple studies, defining boundaries becomes a subjective and sensitive task.

This is why we say:
“A system is not the same as the model we make of it.”

🧱 What Does a System Consist Of?

Let’s conclude this part with the core elements of a system:

✅ A System Consists Of:

1. A set of elements – which are variable attributes of objects
   (e.g., rainfall, population, vegetation cover)
2. A set of relationships – between those attributes and their environment
   (e.g., how rainfall affects vegetation, which in turn affects human settlements)

🧠 What is ‘Abstract Construal’ of a System?

❓ What does “abstract construal” mean?

• “Abstract” = not tied to a specific object or example; generalized or theoretical.
• “Construal” = interpretation or understanding.

So, abstract construal of a system means:

Understanding a system not as a physical thing, but as a theoretical model—with parts, relationships, and structures—regardless of the real-world example it might represent.

🌟 Now, why is This Abstract Understanding Useful?

Let’s break down the five key merits, one by one, in simple language.

✅ Simplifies the Complexity of Geography

Geographical regions are full of diverse phenomena—climate, population, rivers, cities, vegetation, land use, and so on.

In reality, everything is connected, which makes understanding such regions extremely complex.

System analysis helps by:

• Reducing this complexity to its essential elements.
• Presenting a simplified structure.
• Helping geographers construct models that are easier to analyze and apply.

✅ Builds a Universal Theory

Abstract system theory is not limited to any one region, discipline, or topic.

It gives rise to:

A general framework that can be applied to any system—natural, human, social, or economic.

For example:

• The same system model can be used for analysing a river basin, a transport network, or even a city’s housing market.

🧩 This universality makes it powerful and flexible.

✅ Predicts Possibilities

System theory doesn’t just describe existing structures—it also helps us imagine what is possible.

It gives us insights into:

• The possible structures a system can take,
• The behaviours it might show under certain conditions,
• The states it might shift between.

So, system theory becomes a tool not just for analysis, but also for prediction and planning.

📈 For example:
We can simulate what might happen to an ecosystem if rainfall patterns change.

✅ Handles Complex Interactions Technically

In geography, variables are interdependent.

• Example: Rainfall affects soil → Soil affects vegetation → Vegetation affects human settlement patterns.

System theory equips us with:

A technical apparatus—mathematical tools and logical structures—to handle this web of interactions in a systematic way.

It brings rigour to geographical analysis, helping us avoid vague generalizations.

✅ Uses Abstract Mathematical Language

Just as we use:

• Geometry to understand shapes,
• Probability theory to understand chance,

System theory offers:

An abstract mathematical language to discuss real-world empirical problems in geography.

This helps in:

• Formulating precise models,
• Performing quantitative analysis,
• Comparing systems across space and time.

🧠 Even though we’re studying something practical (like a city or a forest), we’re able to use mathematics to understand its underlying logic.

🎯 In Essence:

The abstract understanding of systems gives us a way to see through complexity,
construct models, make predictions, and apply theory—all while staying grounded in real-world geography.