Factoring economic costs into conservation planning may not improve agreement over priorities for protection

Costs in conservation: Common costly mistakes and how to avoid them

There has been an increasingly prevalent message that data regarding costs must be included in conservation planning activities to make cost-efficient decisions. Despite the growing acceptance that socioeconomic context is critical to conservation success, the approaches to embedded economic and financial considerations into planning have not significantly evolved. Inappropriate cost data is frequently included in decisions, with the potential of compromising biodiversity and social outcomes. For each conservation planning step, this essay details common mistakes made when considering costs, proposing solutions to enable conservation managers to know when and how to include costs. Appropriate use of high-quality cost data obtained at the right scale will improve decision-making and ultimately avoid costly mistakes.

Costs and benefits of protecting linear landscape elements: Applying systematic conservation planning on a case study in the Netherlands

Protecting and increasing linear landscape elements (LLEs) in agricultural lands is regarded as a possible solution for a transition to a more biodiverse agricultural system. However, optimizing the spatial configuration of LLEs protected areas is challenging, especially given the demand for land for food production. Systematic Conservation Planning (SCP) can address this challenge, by prioritizing cost-efficient protection areas. We used a SCP approach to look at the LLEs network in the Province of Noord-Brabant in the Netherlands, identifying the possible trade-off between optimizing species conservation, costs and the monetary values of ecosystem services (ES). For this we defined two scenarios. One scenario focuses on achieving species conservation targets at the minimum cost, and the other focuses on achieving targets while maximizing the benefits provided by ES. For each scenario, we further developed two land-management options, namely land-sharing and land-sparing. For each solution, we tested their cost-effectiveness by calculating implementation costs, economic benefits provided by ES, and cost/benefit ratios. First, our scenario analysis indicates that the economic benefits provided by ES always outweigh the implementation costs. Second, it shows that including ES as co-benefits in SCP (Maximize ES Scenario) yields more cost-efficient conservation solutions. Third, both land-sharing and land-sparing are possible cost-efficient approaches to achieve conservation targets. Our results are spatially explicit and identify crucial habitat areas for the conservation of the selected species, which represent 12-20% of the current unprotected network of LLEs. Our findings showcase net economic benefit of conserving species and LLEs, thus representing an additional reason for biodiversity conservation.

Accounting for spatial heterogeneity in the added conservation value of land protection when prioritizing protected areas

To combat biodiversity loss, there is increasing interest in safeguarding habitat by expanding protected areas. Given limited resources in conservation, organizations must invest in places that will add the greatest amount of value in species protection. To determine the added conservation value of protection, one needs to consider the level of human disturbance in areas that would result if they were left unprotected. In recent years, data resources have become available that reveal the spatial heterogeneity in human disturbance over large spatial extents worldwide. We investigated how accounting for heterogeneity in future disturbance in unprotected areas affects prioritization of protected areas by determining the added value offered by protection of different areas. We applied a complementarity-based framework for protected area prioritization to select protected areas in the coterminous United States under different assumptions about the heterogeneity of future disturbance in unprotected areas. Prioritizing protected areas while incorrectly assuming spatially homogeneous disturbance in unprotected areas, a common assumption, led to a loss of 76% of possible conservation gain for a given budget. The conservation return on investment from protecting candidate areas was positively correlated (0.44) to future human disturbance in that area if it was left unprotected. Our results show that the ability to identify cost-effective protected area networks depends on how one accounts for the ecological contribution of private lands that remain unprotected.

"Targets-Plans-Decision": A framework to identify the size of protected areas based on the balance of ecological protection and economic development

A framework called "Targets-Plans-Decision" (TPD) was established for identifying the size of adequate protected areas (PAs) based on the combination of species distribution probability prediction method, systematic conservation planning (SCP) theory, and protection efficiency analysis, to achieve a balance between ecological protection and economic development. The first step of the framework is to determine the protection targets. In this study, the protection targets were defined as important habitats and important ecosystems. The second step is to identify the PAs plans of different sizes. We adopted a SCP method, which takes into account cost-effectiveness while delineating the PAs. The third step is to determine the optimal size of the PAs through ecological protection efficiency analysis. We constructed the protection efficiency index (PEI), which is the protection cost per unit area. Then we used Kaya identity (a structural decomposition method) to decompose PEI. The decomposed PEI included value density (ecological value per unit area) and value cost (cost to realize unit ecological value). By analyzing the changes of the two, the optimal size of the PAs can be determined. We took Nanchang as an example to conduct an empirical study to verify the usability of the TPD framework. The result shows the TPD framework proposed in this study can effectively identify the optimal size of PAs and contribute to forming a cost-effective ecological protection plan. When the size of PAs was set to 70% of the important habitats and important ecosystems, it was most beneficial for ecological protection. Furthermore, the optimal protection efficiency plan recommended by the TPD framework improved the efficiency of ecological protection. The TPD framework can serve as a basis for the size identification of PAs and also support the delineation of PAs worldwide.

Mitochondrial remodelling-a vicious cycle in diabetic complications

Diabetes mellitus (DM) is a chronic, metabolic condition characterized by excessive blood glucose that causes perturbations in physiological functioning of almost all the organs of human body. This devastating metabolic disease has its implications in cognitive decline, heart damage, renal, retinal and neuronal complications that severely affects quality of life and associated with decreased life expectancy. Mitochondria possess adaptive mechanisms to meet the cellular energy demand and combat cellular stress. In recent years mitochondrial homeostasis has been point of focus where several mechanisms regulating mitochondrial health and function are evaluated. Mitochondrial dynamics plays crucial role in maintaining healthy mitochondria in cell under physiological as well as stress condition. Mitochondrial dynamics and corresponding regulating mechanisms have been implicated in progression of metabolic disorders including diabetes and its complications. In current review we have discussed about role of mitochondrial dynamics under physiological and pathological conditions. Also, modulation of mitochondrial fission and fusion in diabetic complications are described. The available literature supports mitochondrial remodelling as reliable target for diabetic complications.

Allocating resources for land protection using continuous optimization: biodiversity conservation in the United States

Spatial optimization approaches that were originally developed to help conservation organizations determine protection decisions over small spatial scales are now used to inform global or continental scale priority setting. However, the different decision contexts involved in large-scale resource allocation need to be considered. We present a continuous optimization approach in which a decision-maker allocates funding to regional offices. Local decision-makers then use these funds to implement habitat protection efforts with varying effectiveness when evaluated in terms of the funder's goals. We illustrate this continuous formulation by examining the relative priority that should be given to different counties in the coterminous United States when acquiring land to establish new protected areas. If weighting all species equally, counties in the southwest United States, where large areas can be bought cheaply, are priorities for protection. If focusing only on species of conservation concern, priorities shift to locations rich in such species, particularly near expanding exurban areas facing high rates of future habitat conversion (e.g., south-central Texas). Priorities for protection are sensitive to what is assumed about local ecological and decision-making processes. For example, decision-makers who doubt the efficacy of local land protection efforts should focus on a few key areas, while optimistic decision-makers should disperse funding more widely. Efforts to inform large-scale conservation priorities should reflect better the types of choice that decision-makers actually face when working over these scales. They also need to report the sensitivity of recommended priorities to what are often unstated assumptions about local processes affecting conservation outcomes.

Tradeoffs in the value of biodiversity feature and cost data in conservation prioritization

Decision-support tools are commonly used to maximize return on investments (ROI) in conservation. We evaluated how the relative value of information on biodiversity features and land cost varied with data structure and variability, attributes of focal species and conservation targets, and habitat suitability thresholds for contrasting bird communities in the Pacific Northwest of North America. Specifically, we used spatial distribution maps for 20 bird species, land values, and an integer linear programming model to prioritize land units (1 km²) that met conservation targets at the lowest estimated cost (hereafter ‘efficiency’). Across scenarios, the relative value of biodiversity data increased with conservation targets, as higher thresholds for suitable habitat were applied, and when focal species occurred disproportionately on land of high assessed value. Incorporating land cost generally improved planning efficiency, but at diminishing rates as spatial variance in biodiversity features relative to land cost increased. Our results offer a precise, empirical demonstration of how spatially-optimized planning solutions are influenced by spatial variation in underlying feature layers. We also provide guidance to planners seeking to maximize efficiency in data acquisition and resolve potential trade-offs when setting targets and thresholds in financially-constrained, spatial planning efforts aimed at maximizing ROI in biodiversity conservation.

Effects of Protected Area Size on Conservation Return on Investment

The objective of this research is to examine how protected area size influences the conservation benefit and acquisition cost of creating a protected area, how the resulting effects influence the predicted rate of return on investment (ROI), and how those relationships change prioritization decision-making for selecting protected areas compared with decisions based only on conservation benefit and decisions based only on acquisition cost. The objective is accomplished in an econometric framework by analyzing the parcel-level acquisition cost and conservation benefit measured by the change in potential fragmentation patterns on the landscape resulting from protection. We focus on areas acquired by The Nature Conservancy in central and southern Appalachia, United States. As an indicator of the change in landscape fragmentation, we use a fragmentation statistic known as effective mesh size. Although the effect of protected parcel size on predicted ROI is inelastic, greater conservation effectiveness is obtained with larger protected parcels than with smaller ones on average. Protected parcel size influences parcels' rankings for protection more (less) when only the predicted change in effective mesh size of protected area (only the predicted acquisition cost per area) is used for prioritizing parcels than when the ranking of parcels is determined by the predicted ROI. These findings imply that, although protected parcel size is important, failure to prioritize using ROI could result in an inappropriate level of emphasis being given to protected parcel size than is warranted.