Towards decision support-based integrated management planning of papyrus wetlands: a case study from Uganda

Zsuffa, István; Dam, A. A. van; Kaggwa, R.; Namaalwa, S.; Mahieu, Marie; Cools, Jan; Johnston, Robyn

doi:10.1007/s11273-013-9329-z

Cited by 28 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Model-based quantitative evaluations can support wetland management through evaluating alternative management options for communities [52]. We A CGE framework is appropriate to cover economy-wide linkages and to carry out ex-ante simulations [55].…”

Section: Introductionmentioning

confidence: 99%

Papyrus, Forest Resources and Rural Livelihoods: A Village Computable General Equilibrium Analysis from Northern Zambia

Gronau¹,

Winter²,

Grote³

2018

View full text Add to dashboard Cite

Papyrus is increasingly suggested as an alternative bioenergy source to reduce the pressure on forest ecosystems. However, there are few studies on the economic viability of papyrus wetlands and the benefits for local communities. We construct a village Computable General Equilibrium (CGE) model to examine whether papyrus harvesting and processing has the potential to improve local livelihoods and simultaneously counteract pressure on local forest resources. We apply the CGE model to a village in northern Zambia where overexploitation of forest resources to produce energy from firewood and charcoal poses a serious problem. The analysis is based on survey data from 105 households collected in 2015. The model results show that papyrus briquetting would be a possible alternative biofuel and that this technology improves household income and utility through labor reallocations. Higher opportunity costs lead to households switching from firewood extraction and charcoal production activities to papyrus harvesting and processing to produce bioenergy. Replacing energy supplies from firewood and charcoal with papyrus briquettes results in substitution effects between forest land and wetland and thereby reduces the pressure on local forest resources. The CGE approach allows for an economy-wide ex-ante analysis at village level and can support management decisions to ensure the success of papyrus bioenergy interventions.

show abstract

Section: Introductionmentioning

confidence: 99%

Papyrus, Forest Resources and Rural Livelihoods: A Village Computable General Equilibrium Analysis from Northern Zambia

Gronau¹,

Winter²,

Grote³

2018

View full text Add to dashboard Cite

show abstract

“…, Zsuffa et al. ), could be catastrophic for regional population persistence. With no flow of individuals from outside these sites, these patches effectively act as sink populations (Pulliam ), which may fail to exist over the long‐term (Hansen and Rotella ).…”

Section: Discussionmentioning

confidence: 99%

“…, ), seasonal drainage (Zsuffa et al. ), and will likely be subject to altered hydrology as the climate changes (Terer et al. ).…”

Section: Introductionmentioning

confidence: 99%

Quantifying resistance and resilience to local extinction for conservation prioritization

Donaldson

Bennie

Wilson

et al. 2019

Ecological Applications

View full text Add to dashboard Cite

Species‐focused conservation planning is often based on reducing local extinction risk at key sites. However, with increasing levels of habitat fragmentation and pressures from climate change and overexploitation, surrounding landscapes also influence the persistence of species populations, and their effects are increasingly incorporated in conservation planning and management for both species and communities. Here, we present a framework based on metapopulation dynamics in fragmented landscapes, for quantifying the survival (resistance) and reestablishment of species populations following localized extinction events (resilience). We explore the application of this framework to guide the conservation of a group of threatened bird species endemic to papyrus (Cyperus papyrus) swamps in East and Central Africa. Using occupancy data for five species collected over two years from a network of wetlands in Uganda, we determine the local and landscape factors that influence local extinction and colonization, and map expected rates of population turnover across the network to draw inferences about the locations that contribute most to regional resistance and resilience for all species combined. Slight variation in the factors driving extinction and colonization between individual papyrus birds led to species‐specific differences in the spatial patterns of site‐level resistance and resilience. However, despite this, locations with the highest resistance and/or resilience overlapped for most species and reveal where resources could be invested for multispecies persistence. This novel simplified framework can aid decision making associated with conservation planning and prioritization for multiple species residing in overlapping, fragmented habitats; helping to identify key sites that warrant urgent conservation protection, with consideration of the need to adapt and respond to future change.

show abstract

“…Multi-objective optimization assumes a decision maker can quantify the value of a decision with respect to the decision maker's objectives. Examples of objectives that have been explicitly quantified in natural resource management include: minimizing the probability of extinction (Maguire et al 1987, Ewen et al 2015, Larkin et al 2016, maximizing the expected cumulative harvest of a hunted species (Johnson et al 1997), maximizing the probability of successful population establishment of re-introduced species (Converse et al 2013), maximizing biodiversity (Arponen et al 2005, van Teeffelen and Moilanen 2008, Cabeza et al 2010, Tsai et al 2015, maximizing habitat suitability (Williams 1998, Holzkämper et al 2006, Groot et al 2007, Zsuffa et al 2014, and maximizing habitat protection (Kennedy et al 2008). A function that quantifies the value of the potential actions θ from a set of possible choices of actions Θ relative to an objective is termed an objective function (Keeney andRaiffa 1976, Williams et al 2002).…”

Section: The Multi-objective Optimization Problemmentioning

confidence: 99%

“…The weighted-sum method and its variants are the most common methods for solving MOO problems across disciplines (see: Williams 1998, Arponen et al 2005, Holzkämper et al 2006, van Teeffelen and Moilanen 2008, Roura-Pascual et al 2009, Cabeza et al 2010, Converse et al 2013, Zsuffa et al 2014, Ewen et al 2015, Larkin et al 2016, for ecological applications). A weighted sum of multiple functions is described by:…”

Section: Pareto Optimal Solutions and Specification Of Preferencesmentioning

confidence: 99%

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

Williams

Kendall

2017

Ecological Modelling

View full text Add to dashboard Cite

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem. A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (Branta hutchinsii minima) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and 2 Williams and Kendall • Multi-Objective Optimization then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

show abstract

Towards decision support-based integrated management planning of papyrus wetlands: a case study from Uganda

Cited by 28 publications

References 22 publications

Papyrus, Forest Resources and Rural Livelihoods: A Village Computable General Equilibrium Analysis from Northern Zambia

Papyrus, Forest Resources and Rural Livelihoods: A Village Computable General Equilibrium Analysis from Northern Zambia

Quantifying resistance and resilience to local extinction for conservation prioritization

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

Contact Info

Product

Resources

About