Measuring the effects of conservation management

Billions of dollars have been spent over the last decade or two on programs to improve the condition of Australia’s environment. These programs include Landcare, the Natural Heritage Trust, and the Caring for Our Country program. The Australian government has, for several years and under the leadership of different political parties, been criticized by the Australian National Audit Office for its inability to measure the benefits of these large investments (Stefan Hajkowicz 2009) .

Billions of dollars have been spent to support a range of environmental activities, including revegetation such as shown here.

One key aspect of measuring benefits of conservation investments is knowing what would have happened in the absence of that management. Where the status quo is highly predictable, that might be easy. We can manage an area, monitor what happens, and compare that to what essentially is a guess about what would have happened in the absence of management.

However, determining what would have happened in the absence of management will often be difficult. The best way to do this is to not only monitor the areas that are managed, but also to monitor some analogous areas that are not managed.

In a previous post, I described the results of a paper that estimated the benefit of spending money on the conservation of species. We worked out how the probability of each species changing conservation class was related to the amount of resources devoted to it.

Fitted relationship between the
probability of changing IUCN category and the amount of money
spent on Australian bird taxa over an 8-year period (Garnett et al.
2003). For threatened species, results are shown for declines of one
(thin line) and two (dashed line) IUCN categories, and an increase of
one conservation category (thick line). The dotted line is the
probability of non-threatened species becoming vulnerable (from McCarthy et al. 2008).

Our analysis was limited because it was correlative – the different levels of funding for each species were not allocated randomly among species, so we can’t be sure of a causative relationship. However, the analysis had one key benefit – species received different levels of funding, ranging from nothing to substantial amounts. The differences in the level of funding was sufficient to determine a relationship between funding and conservation outcome.

Caption: View of experimental south-facing watersheds at the Hubbard Brook Experimental Forest, NH. Watershed 2 is the right-most one.
Source: Hubbard Brook website

The importance of monitoring outcomes across a range of management intervention is well illustrated by stream monitoring at Hubbard Brook, one of the world’s most famous and influential ecosystem studies. This study was designed to examine the influence of tree cover on streamflow. The trees in Watershed 2 were harvested in 1965, several years after monitoring of streamflow had commenced.

Using data provided from the Hubbard Brook web site on annual stream flow, it is clear that annual streamflow is highly variable. Because of this,  an effect of harvesting in the watershed is hard to see when only examining the annual streamflow of this watershed.

Streamflow in watershed 2 of the Hubbard Brook study. An effect of harvesting in 1965 is difficult to see in the presence of naturally variable streamflow.
Data from: http://www.hubbardbrook.org/6-12_education/TeacherActivities/Activ/Activity.htm

But a comparison of the streamflow in an unharvested watershed makes the effect of harvesting transparent, especially if we plot the ratio of streamflow in the two watersheds.

Streamflow in watershed 2 relative to that in the unharvested watershed 3 of the Hubbard Brook study. The effect of harvesting watershed 2 in 1965 is obvious.
Data from: http://www.hubbardbrook.org/6-12_education/TeacherActivities/Activ/Activity.htm

What does this mean for measuring the benefits of large conservation investments by governments? Firstly, when monitoring effects of management, these effects need to be measured against what would have happened in the absence of management. This means that outcomes in the absence of management need to be very predictable, or that outcomes in unmanaged areas also need to be monitored. That might be logistically difficult, because comparable sites might be hard to find. However, measuring or predicting what would happen in the absence of management is vital.

A second important point is that monitoring outcomes in both the managed and unmanaged areas prior to applying the management intervention can be valuable. Look at the graph of relative streamflow above. The impacts of harvesting are obvious partly because data prior to the harvesting were available.

The above points (we should monitor before the management intervention, and we should also monitor areas that are not managed) are standard aspects of before-after-control-impact (BACI) monitoring designs. There is nothing new here.

However, my impression is that organisations that fund conservation works are sometimes reluctant to fund monitoring in areas where conservation works have not been conducted or to fund monitoring prior to management. As a result, capacity to monitor the benefits of those works will be reduced. The basics of BACI designs should figure prominently in the minds of those wishing to measure the benefits of their conservation actions.

Reference

Hajkowicz, S. (2009) The Evolution of Australia’s Natural Resource Management Programs: Towards improved targeting and evaluation of investments. Land Use Policy 26: 471-478.

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About Michael McCarthy

I conduct research on environmental decision making and quantitative ecology. My teaching is mainly at post-grad level at The University of Melbourne.
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2 Responses to Measuring the effects of conservation management

  1. Pingback: Considering uncertainty in environmental management decisions | Michael McCarthy's Research

  2. Pingback: Measuring the effects of environmental management | Michael McCarthy's Teaching

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