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Primary Health Care Manual Health Care In Pohnpei Micronesia Traditional Uses Of Plants For Health And

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Primary Health Care Manual Health Care In Pohnpei Micronesia Traditional Uses Of Plants For Health And
          

Sacre, Edmond (2019) Developing spatial prioritisation strategies to maximise conservation impact. PhD thesis, James Cook University.

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Despite exponential increases in the size, number, and coverage of protected areas (PAs), biodiversity continues to decline worldwide. Additionally, emerging evidence shows that PAs are often located in 'residual' areas, locations with minimal value for extractive activities, such as agriculture, development, mining and fishing. Over recent decades, systematic conservation planning (SCP) has developed new and sophisticated methods for ensuring that protected areas are complementary and representative, so that PA networks avoid redundancy and maximise biodiversity within their bounds. However, the SCP literature has few analyses that aim to maximise conservation impact. Impact is measured as the difference in biodiversity outcomes that occur when a given conservation intervention is applied, compared to when it is not (referred to as a 'counterfactual' scenario). As a result, many modern approaches to SCP have questionable impact, and might do little to counteract residual biases and ongoing biodiversity declines. The goal of my thesis is develop methods for estimating impact in SCP, and to use these methods to compare alternative spatial prioritisation strategies. To achieve this goal I set three objectives: 1. Establish a framework for using counterfactual-based impact estimation in conservation planning 2. Estimate and compare the impact of currently widespread conservation prioritisation strategies 3. Develop evidence-based spatial prioritisation strategies (i.e. 'rules of thumb') for cost effectively maximising impact in conservation planning In the first chapter, I introduce the concept of systematic conservation planning, and discuss modern approaches to conservation impact evaluation. I then identify four key knowledge gaps with respect to incorporating impact evaluation into conservation planning using counterfactual methods: (1) What methods can be used to implement counterfactual scenarios and estimate impact in spatial conservation prioritisation? (2) How effective are modern approaches to spatial conservation prioritisation at achieving impact? (3) What is the spatial relationship between threats and costs, and how does this affect conservation prioritisation to maximise impact? (4) How should we prioritise areas for conservation based on spatial patterns of costs, biodiversity, and threats? In the second chapter, I first address Objective 1 by developing a theoretical model to explore how the impact of alternative prioritisation strategies, compared to a counterfactual, can vary according to various factors. I compare two alternative prioritisation strategies: protecting high-threat frontier areas, or low-threat wilderness areas. I explore how the relative efficacy of either strategy compared to the counterfactual scenario varies depending on spatial patterns of threats, biodiversity values, conservation costs, timeframes within which impacts are measured, rates of biodiversity recovery, and temporal changes in threats. In doing so, this chapter also contributes to Objective 3, by identifying circumstances under which either frontier prioritisation, wilderness prioritisation, or a combination of both are likely to be most effective. In the third chapter, I further contribute to Objective 3 by aiming to quantify the spatial relationship between acquisition costs and threats to biodiversity using empirical data in a conservation landscape. As I show in the prior chapter, this spatial distribution has a large influence on the cost-efficiency of any given prioritisation strategy. In this chapter, I use high-resolution datasets of rates of vegetation clearance in Queensland, Australia. I then combine this data with land sales transactions, land valuations, and agricultural profitability to examine the spatial relationship. I then use a classic economic model to explore the potential drivers behind this relationship. I found that counter to what is widely assumed in conservation science, there is no clear spatial relationship between rates of land clearing and acquisition costs, and the relationship displays enormous variability. As a result, the landscape appears to contain a large number of sites with relatively low cost and potential for high impact. In the fourth chapter, I address all three objectives by implementing an ex post method to measure counterfactual outcomes and estimate impacts for several alternative prioritisation strategies. This chapter also uses the case study of Queensland, Australia. With the ex post method, the counterfactual scenario is measured using historical changes in vegetation in a landscape with no protected areas. I then retrospectively implement alternative prioritisation strategies and predict how outcomes might have differed compared to the counterfactual. Specifically, I compare four alternative prioritisation strategies: cost minimisation; threat prioritisation and cost minimisation; representation and cost minimisation; and representation, threat prioritisation and cost minimisation. These alternative strategies represent the extremes of how much importance should be placed on costs, threats and biodiversity when aiming to maximise impact. I find that the most effective strategy to maximise impact is to prioritise highthreat locations, and that aiming to achieve representation targets, a widely adopted practice in conservation planning, can be counter-productive to achieving impact. In the fifth chapter, I provide an alternative method to estimating impacts, which is to use ex ante predictions of expected outcomes in counterfactual scenarios and when alternative strategies are implemented. In this chapter, I estimate the impact of several strategies on the coral reefs of Micronesia: frontier prioritisation; wilderness prioritisation; representation; and representation with connectivity. This chapter complements the previous chapter by providing a method for estimating impacts when historical data on changes in biodiversity are unavailable, and when aiming to estimate impacts over long timeframes. Importantly, this chapter incorporates an additional component to measuring impact, which is to compare all strategies to a 'best-case' scenario, where biodiversity outcomes are known and impact can be optimised. Comparing strategies to a counterfactual and best-case allow absolute impacts to be measured. In this chapter I also find that the most effective strategy is generally to prioritise high-threat frontier areas, and that representation targets can be counterproductive to maximising impact. In achieving the above objectives and addressing the respective knowledge gaps, my thesis provides an important contribution towards incorporating counterfactual-based impact estimation in conservation planning. The global protected area network is expanding at an exponential rate, yet little is known about how well the strategies to spatially allocate these protected areas achieve positive conservation impacts. Given the severity and imminence of global biodiversity declines, it is essential that we develop an evidence base from which conservation policy and practice can draw upon to ensure that future conservation efforts can efficiently maximise impact and prevent further declines.


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