Recovery Action Plan for Grey Box community


Monitoring Success of Management Interventions at a Site



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1.10.Monitoring Success of Management Interventions at a Site

Monitoring and evaluation provides information that will help to improve management of Grey Box woodlands, through the process of adaptive management. Adaptive management involves a process where land managers predict the possible outcomes of management options and implement the most logical management option. The implementation works are undertaken and monitored in a way that will verify whether the management actions result in the expected outcomes. Management is adjusted according to whether or not the early results obtained are likely to reach project goals (Clarke et al 2010). The principles of adaptive management are shown in Figure 1.10.


Figure 1.10: Key components of effective monitoring


Monitoring of changes in areas being worked can thus inform managers if current management actions are being effective, and can enable them to adapt their management accordingly. Monitoring can also provide valuable motivation to people involved in natural resource management, as they receive feedback on the progress of their efforts.

Output monitoring measures the tangible, immediate and intended results from a management action, such as the area for which weed control has been undertaken, or the kilometres of fencing established. Outcome monitoring measures whether anything has actually been achieved by undertaking the work, and usually relates to the objective of doing the work. Table 1.10 shows a series of desired primary outcomes for management actions for Grey Box Woodlands. Obviously there are other overarching outcomes that would be achieved through these management interventions, such as improved regeneration, increased habitat values, improved structure and diversity of native vegetation. Measuring these broader outcomes can be complex and may require a specific experimental approach.

The measurement of the primary outcomes requires a different suite of skills which is dependent on the management intervention itself – so for example measuring a reduction in woody weed density could be undertaken by less skilled individuals, whereas measuring the improved structure and diversity of the understorey requires a comprehensive suite of skills.

Table 1.10 Monitoring Outputs and Outcomes from Management Interventions



Management Intervention

Output

Primary Outcome

Woody weed control

Area of woody weed control undertaken

Reduction in density of woody weeds

Herbaceous weed control

Area of herbaceous weed control undertaken

Reduction in density of herbaceous weeds

Grassy weed control

Area of grassy weed control undertaken

Reduction in density of grassy weeds

Broad Acre weed control

Area of broad acre weed control undertaken

Reduction in density of weeds

Baling to remove nutrients

Area of baling undertaken

Reduction in density of nutrient reliant flora

Grazing management

Area and intensity of grazing undertaken

Increase in cover and diversity of native understorey, decrease in cover of introduced understorey

Slashing

Area, height and timing of slashing

Increase in cover and diversity of native understorey, decrease in cover of introduced understorey

Fire management

Area of fire management undertaken

Improved structure and diversity of understorey

Reduced fuel load



Supplementary planting

Total number of individuals and number of different species and lifeforms planted

Improved structure and diversity across lifeforms1

Reconstruction

Total number of individuals and number of different species and lifeforms planted

Improved structure and diversity across lifeforms1

1Note that this would need to be assessed against the optimal structure of Grey Box woodland as per the description of the woodland in section 1.2.

There is an array of monitoring methods that could be used to measure the success of these management interventions. It is recommended that the monitoring method chosen specifically addresses the desired outputs and outcomes of the particular management intervention.


1.11.Identifying Regional Priorities

Based on the number and type of management interventions required, and the expected biodiversity outcomes from this investment, a coarse indicator of return per investment can be generated. Table 1.11 shows that the lowest cost alternatives are maintenance of existing good quality sites (ie States 1 and 1b), but that these do not generally lead to a change in biodiversity value of a site. State 5a shows the best return (in terms of biodiversity value increase) for only moderate cost. Restoration of grazed sites without nutrient addition (State 3a) also shows good return for investment.


The most costly States to move to their optimal State are where full reconstruction is required (States 5c, 5d, 7, 8, 9), and the resultant biodiversity value of the reconstructed vegetation is only moderate.
However, it is important to consider the landscape context of the site. These landscape considerations help to determine if the patch has additional conservation values, and include:


  • Connectivity to other native vegetation remnants or restoration works (e.g. native plantings). In particular, if a patch has an important position between (or linking) other patches (or other native vegetation remnants) in the landscape.

  • Patches that occur in those areas in which the ecological community has been most heavily cleared and degraded or are at the natural edge of its range.

  • Large patch size and/or large area to boundary ratio. Such patches are less exposed and more resilient to edge effects disturbances such as weed invasion.

  • Evidence that native species are recruiting or that a range of age cohorts are present. For instance, tree canopy species are present as saplings through to large old hollow-bearing trees.

  • Areas of minimal weeds and feral animals, or where they can be easily managed.

  • Presence of mosses, lichens, liverworts, soil crust and leaf litter on the soil surface, indicating low disturbance and potential for good functional attributes such as nutrient cycling.

Section 3 discusses the development of a regional map of the State of all Grey Box remnants. If this map were developed, all of the above prioritisation considerations could be incorporated into a prioritisation process that ensured recovery of these Grey Box remnants was planned and implemented as efficiently and effectively as possible.



Table 1.11: Costs, benefits and values for applying management interventions1 to Grey Box Woodland States. States highlighted are those which show the best biodiversity gain for cost.

Current State

S0

S1

S1b

S2

S3a

S3b

S4

S5a

S5b

S5c

S5d

S6

S7

S8

S9

S10

S11

Maximum State achievable

NA

S1

S1b

S1

S1b

S9

S9

S1

S1b/S94

S9

S9

S11

S9

S9

S9

NA

NA

Current biodiversity value

Very high

High

Moderate

Moderate - High

Moderate

Low

Low

Moderate

Low-Moderate

Low

Low

NA

Very low

Very low

Moderate







Relative biodiversity value of maximum state achievable

Very high

Very High

Moderate-High

Very High

Moderate-High

Moderate

Moderate

Very High

Moderate-high

Moderate

Moderate

NA

Moderate

Moderate

Moderate

NA

NA

Cost to achieve or maintain that state1:

NA

$

$

$$

$$

$$$

SS$$

$$

$$$

$$$$

$$$$

NA

$$$$$

$$$$$

$2

NA

NA

1Based on applying management interventions flagged in Table 1.8 2maintenance costs of reconstructed woodland

State 0 – Pre-European intact Grey Box woodland

State 5c – Woodland impacted by neglect / tree death

State 1 – Remnant intact woodland

State 5d – Woodland impacted by neglect / tree death after disturbance with nutrients

State 1b – Remnant depauperate woodland

State 6 – Woodland impacted by Phytophthora root fungus

State 2 – Woodland impacted by inappropriate fire events

State 7 – Woodland replaced by pasture, without trees

State 3a – Woodland with grazing impacts, but no / little added fertiliser

State 8 – Woodland lost through alienation

State 3b – Woodland with grazing impacts and with nutrients

State 9 – Woodland reconstructed

State 4 – Woodland impacted by pasture species understorey

State 10 – Woodland impacted by climate change

State 5a – Woodland impacted by neglect – recoverable

State 11 – Woodland best-option conservation surrogate

State 5b – Woodland impacted by neglect after disturbance




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