Shared and unique approaches of human ecology and resilience thinking

system dynamics, or systems thinking more broadly. The value of systems thinking for developing conceptual frameworks that provide visual representation of the system has been discussed earlier. This shared visual language is not specific to any particular discipline and is useful in facilitating a much-needed constructive dialogue between stakeholders in the system, regardless of their discipline, background or worldviews (Newell and Proust, 2009). Using systems thinking, I am able to not only describe and analyse the rangeland goat system, but also develop propositions that can be used to facilitate dialogue and collaboration between stakeholders in the rangeland goat system. Figure 2.1 highlights the similarity in the way human ecology and resilience thinking use system dynamics to approach the study of SESs, despite the differences in language and concepts.

Figure 2.1: Shared and unique approaches of human ecology and resilience thinking

CAT = cultural adaptation template; RA = resilience assessment

The two distinct analytical tools in this integrated framework are the Goldilocks principle, from human ecology, and the concept of cross-scale interactions from resilience, which are briefly discussed in the Sections 2.2.4.1 and 2.2.4.2.

2.2.4.1The Goldilocks principle

For managers and researchers of SESs, it is important not only to try to identify thresholds of a system, but also to agree on self-imposing limits or goals to ensure these thresholds are not crossed. Both upper and lower limits of what is then a safe operating space, in which communities need to operate to be sustainable, are important for the viability of the system (Raworth, 2012). Dyball and Newell (2015:102) used the term ‘Goldilocks principle’ to express this concept, stating that ‘in order to be sustainable a society must maintain its resource and waste flows at rates that are not too high, not too low, but just right’. The Goldilocks principle (see Figure 2.2) is an extension of the Ehrlich and

CAT RA

DESCRIBE

General description of system and scales

Scales, boundaries, scope, focus scale, and main issues State of cultural paradigms Resilience of what: beliefs,

values, etc…

State of ecosystems General Resilience

Resilience to what (disturbances, disruptions and uncertainty) State of Human Health and

Wellbeing

People: individual resilience

State of Institutions Institutions: resilience and

adaptability Governance

ASSESS

Thresholds Specified resilience (thresholds

and domains)

Scenario matrix Alternative regimes

ACT

Paradigm shift and collaborative management

Cross-Scale Spatial and

Temporal Dynamics

Human

Ecology Resilience Thinking

Goldilocks Principle

Holdren (1971) relation (see Appendix 2), which calculates the negative impact of a society on its environment, based on the population size and the average environmental impact of an individual on the environment (Dyball and Newell, 2015).

Figure 2.2: The Goldilocks principle: Just right (adapted from Dyball and Newell, 2015)

I is a flow that represents the social ecological impact of a resource-consuming or pollution-generating process. P is a stock that represents population. C represents total consumption (affluent consumption) [A] + base consumption [B]; therefore, Iglobal is

represented as PCT for simplification; Imin is PBT as it only includes basic needs, where

A equals 0; K represents the planet’s carrying capacity for humans. It is less than Earth’s overall carrying capacity, because planetary resources and ecosystem services must be shared with all other organisms, the survival of which, in many cases, is essential for human survival;  represents a carrying capacity buffer zone, necessary to avoid the unsustainable situation in which I exceed K. Thus, Imax = K - ; therefore, a safe operating

space is a condition where IminIglobalImax

The Goldilocks principle can be useful when dealing with SESs. For this inquiry, the idea behind employing the Goldilocks principle is to understand the impact of goats as a result of their population drawing on resources in the rangelands on one hand, and the required stocking rates to sustain the rangeland goat industry on the other. Theoretically, what is ‘just right’ would be for goat numbers to remain below the carrying capacity of the land to ensure environmental damage is controlled, but above the minimum numbers needed

Social processes unsustainable 0 Imin= PBT Imax = K -d K Iglobal= PCT d

Social-ecological processes unsustainable

Social-ecological processes sustainable but at risk

A safe and equitable operating zone Social-ecological processes sustainable

to sustain the industry. This would suggest that the number of wild goats is the main limiting factor in any attempt to estimate and manage this impact. However, while these assumptions can be relevant in relatively equilibrial environments, they are extremely difficult to employ in the context of the event-driven Australian rangelands, which are characterised by highly dynamic processes that can change quickly, and are often unpredictable (Ludwig and Freudenberger, 1997). Such uncertainties include, for example, cycling between drought and heavy, often unpredictable rainfall, and the consequent change in the abundance of resources and fluctuation of the carrying capacity of rangelands, as well as flipping of the system from grassland to shrubland. Consequently, stochastic rainfall events, rather than carrying capacity of the land, are ultimately the main factors influencing stocking rates in the rangelands.

Based on these facts, it would be difficult to argue for defined limits in an event-driven ecological system like the rangelands. While they can be concordant, boundaries for the true safe operating space of a system from a resilience perspective can vary across temporal and spatial scales from suggested limits of biophysical carrying capacity of the landscape. This will be discussed in greater detail in Chapter 9. However, to help visualise this concept of disparity between perceived and actual, continuously changing boundaries, I have adapted the Goldilocks diagram (see Figure 2.3) by adding dotted wavy lines to acknowledge the uncertainties and indicate that the thresholds, as represented in the original Goldilocks principle, cannot be set in stone in the rangelands.

Figure 2.3: Thresholds and safe operating space of the goat SES within the limits of resource consumption

Note: I = goat impact in relation to their population; Pmin = minimum number of goats to support industry; Pmax = maximum number of goats that the rangelands can support before collapse; C = resource consumption; K = rangeland carrying capacity for goats;  = rangeland carrying capacity buffer zone.

This adapted Goldilocks principle will be used as part of the analysis in Chapter 8 and in the discussion in Chapter 10.

2.2.4.2Cross-scale interactions

Resilience thinking proposes that scales are interconnected, and that a change at one scale might trigger a change at a different scale (Gunderson and Holling, 2002; Walker and Meyers, 2004; Walker et al., 2004; Walker and Salt, 2012; O’Connell et al., 2015). The structure and dynamics at each scale are driven by a small set of key processes and, in turn, this linked hierarchy governs the behaviour of the whole system (Walker and Salt, 2012). Therefore, cross-scale interactions are vital for systems at a particular focal scale, as the behaviour of these systems ‘depends on both bottom-up and top-down cross-scale interactions’ (Walker et al., 2006:17). Chapter 9 uses these concepts to analyse cross- scale interactions within the rangeland goat SES.

Social processes unsustainable Goat industry collapses

0 Imin= PminC Imax = K -d K Iglobal= P C d

Social-ecological processes unsustainable Goats grazing pressure deplete resources Social-ecological processes sustainable but at risk Goat numbers high as harvesting is opportunistic and some

releases intentional

A safe and equitable operating zone Social-ecological processes sustainable

Goat harvesting as the environmental management tool of choice

Both the Goldilocks principle and the concept of cross-scale interactions are valuable tools to use in this inquiry. The former contributes with the CAT to the study of the behaviour of the system in response to endogenous feedbacks and analyses its position within or outside defined limits for proposed operating spaces; the latter allows the analysis to progress further to account for cross-scale spatial and temporal dynamics. I use them both to support my analysis using the CAT as the main conceptual framework.

2.2.4.3A note on other herbivores in the western division

It is important to acknowledge that goats share resources with other native and domestic herbivores in the western division, particularly sheep and kangaroos. The impacts of goats and the capacity of the rangeland to support them is at least in part a function of the populations of these other herbivores, each of which constitute a social ecological system at same or different scale. Given that SESs do not exist in a void and that in reality all systems are related (Folke et al., 2010; Meadows, 2008), cross-scale and cross-sector feedbacks between the goat SES and other SESs of various herbivores can influence its behaviour, as discussed in section 2.2.4.2. For example, similarly to goats, kangaroos can cross fences and exert pressure on resource within pastoral paddocks. Dorper sheep, which are now becoming increasingly farmed in the division, have similar browsing behaviour as goats, and therefore can compete with them on the same resources, as I will discuss in subsequent chapters. In reality, it’s hard to separate the impacts of goats from these herbivores, and consequently the dotted wavy line representing the rangeland carrying capacity (K) in the goldilocks diagram should take into consideration all species (see Figure 2.3). For the scope of this thesis however, and to facilitate my analysis of the goat SES, I will confine the discussion to the relative impact and resource needs of goats, which are the focus of this study.