Conservation has many facets, ranging from biodiversity protection to management of invasive species to restoration of degraded lands. In many cases, protection alone may not be sufficient and restoration is urgently needed to reverse human damage and prevent ongoing attrition of species from isolated forest fragments and reinstate ecosystem services. Increasing ambitious initiatives have been proposed to respond to these challenges e.g., Bonn Challenge Ministerial Roundtable target to restore 150 million hectares of lost forests and degraded land worldwide by 2020 (IUCN). Nevertheless, ecological restoration is a complex endeavor and prioritization of where, when and how habitat is restored is likely to be critical in managing risks and ensuring that desired outcomes are delivered in a way that represents good value for money and supported by key stakeholders.

Better decision making in ecological restoration

Why do we undertake restoration?

Ecological restoration assists the recovery of degraded ecosystems but the underlying motivations stem from diverse environmental and social reasons which influence the desired outcomes.  We surveyed 307 people involved in the restoration of native vegetation across Australia to identify their underlying motivations.  We found that biodiversity enhancement is the main motivation for undertaking restoration, with biodiversity offsetting, water quality improvements, and social reasons as important secondary motivations. Better alignment of different restoration motivations, with the planning and monitoring of restoration projects, should deliver greater benefits. These improvements will increase the capacity of the restoration practice to meet international commitments (Hagger et al. 2017). Read more

Accounting for values and preferences

The task of setting clear restoration objectives is hindered by the motivations and values of different stakeholders, which is not often accounted for. Restoration projects can benefit from the formal objective setting, in particular when there are multiple stakeholder groups with varying values. We applied a structured decision making (SDM) approach to restoration decision making in a local government in South East Queensland, Australia aiming to maximise outcomes of public expenditure in a region with multiple stakeholders. Our modified SDM process allowed us to ascertain more broadly held underlying values and time frame considerations, alerted us to process issues and time frames that mattered to stakeholders, and helped facilitating transparent and inclusive establishment of restoration objectives. Read more

Smart allocation of funds

Ecosystem restoration requires choosing between potential interventions that differ in cost and the time required to achieve outcomes of varying quality. Managers have different preferences for timeframes, certainty, and quality of outcomes, which can influence the choice of investment strategy. We have developed an approach to quantify expected restoration outcomes from alternative investment strategies, given operational constraints or alternative preferences. We applied this approach to a tropical forest restoration case study in which managers seek to allocate future resources between active planting and self-organized regrowth. A useful outcome of this analytical approach is that it prompts decision-makers to define and reappraise their preferences for important attributes of the outcomes, to explore management options and their consequences, and to examine trade-offs.

Projects

Marine restoration

Restoration of marine coastal environments will be important for climate change adaptation and mitigation. We ask, what is the role of marine restoration in a changing climate? Seagrasses, saltmarshes, macroalgae and mangroves sequester carbon in a process called blue carbon. We aimed to identify marine restoration actions that will maximise return-on-investment under climate change. Possible outcomes of this work include increasing coastal resilience to climate change and increasing blue carbon/opening up new markets around blue carbon.

While initiatives for restoring coastal environments are plentiful, these programs rarely focus on ecosystem services provision at broader scales. Scaling-up marine restoration will have important ecological and socio-economical outcomes. We aimed to evaluate whether cost-efficiencies are possible if marine restoration moves from small to large-scale. We reviewed the costs and benefits of marine restoration actions via meta-analysis of literature. To effectively judge benefits of marine restoration, we aimed to quantify ecosystem services generated by successful restoration activities. These include ‘downstream’ economic benefits to marine industries – including fisheries and coastal tourism. Possible outcomes include development of a novel marine spatial planning tool to analyse priority locations for global marine restoration activities.

Borneo

Using East Kalimantan as a case study, we prioritised degraded forest for restoration and determined which restoration actions should be implemented across multiple ecosystem types. We identified 400,000 hectares of highly degraded lowland forest in East Kalimantan, for which restoration was cost-effective (Budiharta et al., 2014). This research revealed degraded areas that should not be converted to other land uses, such as palm oil. Instead these areas could be the focus of privately funded ecosystem restoration concessions (ERCs) and contribute to the government target of creating 2.5 million hectares of ERC (currently only 397,000 hectares of ERC licenses have been granted). Read more

City of Gold Coast

Over a quarter of Australia’s native forest and woodlands have been cleared since European settlement, and vegetation restoration is urgently needed to avoid further loss of species and ecosystem services (such as clean air and water). Through a collaborative project with City of Gold Coast we developed new theory and methods to help environmental managers allocate restoration funds for vegetation recovery in a way that addresses the tensions between risk aversion and aspirations to maximise return on investment. We applied technical optimisation approaches that find solutions to resource allocation problems through mathematical formulation of restoration prioritisation problems. Read more

Irvine Ranch Natural Landmark

Priority areas for restoration after 20 years. Irvine Range Project

The Irvine Ranch Natural Landmark is a collection of permanently protected wildlands and parks located near the Santa Ana Mountains in Southern California. It represents approximately 44,000 acres of land, much of which has been degraded by anthropological disturbances and fire. Managers of the Irvine Ranch sought to prioritise funding over the next 20 years to achieve the best possible results for restoration. We worked with Dr Jutta Burger, Dr Megan Lulow and Yi-Chin Fang at the Irvine Ranch Conservancy to formulate the restoration prioritisation problem and developed a return on investment based approach for determining robust restoration priorities for a 20 year planning horizon. Problem complexities included a need to account for multiple objectives, time lags, logistical constraints, stochastic occurrences of fire and drought, connectivity and uncertain outcomes.

Outcomes from the project included:

• A problem definition paper for prioritizing restoration activities (McBride et al, 2010)
• An application paper, detailing how we specifically applied our methodology to the Irvine Ranch Landmark case study (Wilson et al, 2011)
• Development of a restoration prioritization decision support tool for use by Ranch managers to implement and update restoration priorities over the next 20 years.

Read these stories in Decision Point magazine…

Allocating funds among restoration actions

A major emerging task for biodiversity conservation is to ‘scale-up’ the restoration of degraded land from the local patch to the scale of the landscape (regional). This poses significant challenges for prioritising investments, most notably because: (a) restoring native vegetation involves considerable uncertainty and time lags over at least several decades; and (b) restoration typically involves a range of different potential actions, each with its own costs, time frame and likelihood of success.

In this workshop we aimed to directly address the tension between minimizing shortfall risk (not achieving desired targets) and maximizing return on investment… read more

Prioritising restoration in Kalimantan

Mention Indonesia and images of soaring rainforests and orangutans come to mind. But the reality is quite different. Over 63% of Indonesia’s forest estate is currently deforested or degraded (that’s around 83 million hectares), and many of its iconic species such as the orangutan and proboscis monkeys are endangered. And the deforestation marches on. In 2012 Indonesia broke the record for clearing tropical forest. The choking haze from burning forest and peatland has blanketed South East Asia many times in recent years, and awareness of the economic and health hazards associated with this is growing… read more

Key references

Wilson, K.A., Davis, K.J., Matzek, V. and Kragt, M. 2019. Concern about threatened species and ecosystem disservices underpin public willingness to pay for ecological restoration. Restoration Ecology. 27(3):513-519. https://doi.org/10.1111/rec.12895

Hagger V., Wilson K., England J.R., Dwyer, J. M. 2019. Water availability drives aboveground biomass and bird richness in forest restoration plantings to achieve carbon and biodiversity cobenefits. Ecology and Evolution. https://doi.org/10.1002/ece3.5874

Bayraktarov, E., Stewart‐Sinclair, P.J., Brisbane, S., Boström‐Einarsson, L., Saunders, M.I., Lovelock, C.E., Possingham, H.P., Mumby, P.J. and Wilson, K.A. 2019. Motivations, success and cost of coral reef restoration. Restoration Ecology, 27(5): 981-991. https://doi.org/10.1111/rec.12977

Beyer, H.L., Kennedy, E.V., Beger, M., Chen, C.A., Cinner, J.E., Darling, E.S., Eakin, C.M., Gates, R.D., Heron, S.F., Knowlton, N., Obura, D.O., Palumbi, S.R., Possingham, H.P., Poutinen, M., Runting, R.K., Skirving, W.J., Spalding, M., Wilson, K.A., Wood, S., Veron, J.E. and Hoegh-Guldberg, O. 2018. Risk‐sensitive planning for conserving coral reefs under rapid climate change. Conservation Letters. p.e12587. https://doi.org/10.1111/conl.12587. A top 20 most read paper in Conservation Letters in 2017-2018

Hagger, V., Dwyer, J., Shoo, L. and Wilson, K. 2018. Use of seasonal forecasting to manage weather risk in ecological restoration. 28(7):1797-1807. Ecological Applications. https://doi.org/10.1002/eap.1769

Jellinek, S., Wilson, K., Hagger, V., Mumaw, L., Cooke, B., Guerrero, A., Zamin, T., Waryszak, P., Erickson, T., Standish, R. 2018. Integrating diverse social and ecological motivations to achieve landscape restoration. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.13248

Guerrero A.M., Shoo L., Iacona G., Standish R.J., Catterall C.P., Rumpff L., de Bie K., White Z., Matzek V., Wilson K.A. 2017. Using structured decision making to set restoration objectives when multiple values and preferences exist. Restoration Ecology. 25(6): 853-865. http://doi.org/10.1111/rec.12591

Hagger, V., Dwyer, J. and Wilson, K. 2017. What motivates ecological restoration? Restoration Ecology. 25(5): 832-843. http://doi.org/10.1111/rec.12503

Shoo, L.P., Catterall, C.P., Nicol, S., Christian, R., Rhodes, J., Atkinson, P., Butler, D., Zhu, R., Wilson, K.A. 2017. Navigating complex decisions in restoration investment. Conservation Letters. Conservation Letters. 10(6):748-756. http://doi.org/10.1111/1365-2664.12920

Uebel, K., Wilson, K. A. and Shoo, L. P. 2017. Assisted natural regeneration accelerates recovery of highly disturbed rainforest. Ecological Management and Restoration. 18: 231–238. http://doi.org/10.1111/emr.12277

Budiharta, S, Meijaard E, Wells J.A, Abram N.K, and Wilson, K.A. 2016. Enhancing feasibility: incorporating a socio-ecological systems framework into restoration planning. Environmental Science & Policy. 64: 83-92. http://dx.doi.org/10.1016/j.envsci.2016.06.014

McAlpine, C.A., Catterall, C.P., Mac Nally, R., Lindenmayer, D., Leighton Reid, J., Holl, K.D., Bennett, A.F., Runting, R.K., Wilson, K.A., Hobbs, R.J., Seabrook, L., Cunningham, S., Moilanen, A., Maron, M., Shoo, L., Lunt, I., Vesk, P., Rumpff, L., Martin, T.G., Thomson, J. and Possingham, H. 2016. Integrating plant- and animal-based perspectives for more effective restoration of biodiversity. Frontiers in Ecology and the Environment. 14(1): 37–45. http://dx.doi.org/10.1002/16-0108.1

Evans, M. C., Carwardine, J., Fensham, R.J., Butler, D., Wilson, K.A., Possingham, H.P., and Martin, T.G. 2015. Carbon farming via assisted natural regeneration as a cost-effective mechanism for restoring biodiversity in agricultural landscapes. Environmental Science & Policy. 50: 114-129. http://dx.doi.org/10.1016/j.envsci.2015.02.003

Budiharta S., Meijaard E., Erskine P.D., Rondinini C., Pacifici M. & Wilson K.A. 2014. Restoring degraded tropical forests for carbon and biodiversity. Environmental Research Letters. 9, 114020. http://dx.doi.org/10.1088/1748-9326/9/11/114020

Shoo, L. P., Scarth, P., Schmidt, S. and Wilson, K. A. 2013. Reclaiming Degraded Rainforest: A Spatial Evaluation of Gains and Losses in Subtropical Eastern Australia to Inform Future Investment in Restoration. Restoration Ecology. 21: 481–489. doi: 10.1111/j.1526-100X.2012.00916.x

Wilson, K. A., Lulow, M., Burger, J. and McBride, M. F. 2012. The economics of restoration. In L. David, M. Palle and S. John (eds.), Forest landscape restoration: integrating natural and social sciences pp. 215-231). New York, NY, United States: Springer. doi: 10.1007/978-94-007-5326-6_11

Wilson, K.A., Lulow, M., Burger, J., Fang Y-C, Andersen, C., Olson D., O’Connell, M., and McBride M.F. 2011. Optimal restoration: accounting for space, time, and uncertainty. Journal of Applied Ecology. 48:715-725. doi: 10.1111/j.1365-2664.2011.01975.x

McBride, M.F., Wilson, K.A., Burger, J., Fang, Y.-C., Lulow, M., Olson, D., O’Connell, M. and Possingham, H.P. 2010. Mathematical problem definition for ecological restoration planning. Ecological Modelling. 221 (19): 2243-2250 doi:10.1016/j.ecolmodel.2010.04.012