Insights from life history theory for an explicit treatment of trade-offs in conservation biology

Abstract

As economic and social contexts become more embedded within biodiversity conservation, it becomes obvious that resources are a limiting factor in conservation. This recognition is leading conservation scientists and practitioners to increasingly frame conservation decisions as trade-offs between conflicting societal objectives. However, this framing is all too often done in an intuitive way, rather than by addressing trade-offs explicitly. In contrast, the concept of trade-off is a keystone in evolutionary biology, where it has been investigated extensively. I argue that insights from evolutionary theory can provide methodological and theoretical support to evaluating and quantifying trade-offs in biodiversity conservation. I reviewed the diverse ways in which trade-offs have emerged within the context of conservation and how advances from evolutionary theory can help avoid the main pitfalls of an implicit approach. When studying both evolutionary trade-offs (e.g., reproduction vs. survival) and conservation trade-offs (e.g., biodiversity conservation vs. agriculture), it is crucial to correctly identify the limiting resource, hold constant the amount of this resource when comparing different scenarios, and choose appropriate metrics to quantify the extent to which the objectives have been achieved. Insights from studies in evolutionary theory also reveal how an inadequate selection of conservation solutions may result from considering suboptimal rather than optional solutions when examining whether a trade-off exits between 2 objectives. Furthermore, the shape of a trade-off curve (i.e., whether the relationship between 2 objectives follows a concave, convex, or linear form) is known to affect crucially the definition of optimal solutions in evolutionary biology and very likely affects decisions in biodiversity conservation planning too. This interface between evolutionary biology and biodiversity conservation can therefore provide methodological guidance to support decision makers in the difficult task of choosing among conservation solutions.

How spatial policies can leverage energy transitions − Finding Pareto-optimal solutions for wind turbine locations with evolutionary multi-objective optimization

“…To analyze trade-offs between multiple criteria for only optimal solutions, multi-objective optimization can be used to explore a set of non-dominated or Pareto-optimal solutions (i.e., the Pareto Front) in the n-dimensional target space (Song and Chen, 2018b). A Pareto-optimal solution is impossible to further enhance on one target dimension without reducing the quality of another target (Charpentier, 2015;Drechsler et al, 2017). The set of Pareto solutions facilitates an unbiased trade-off analysis between the targets (Charpentier, 2015;Coello, 2006).…”

“…A Pareto-optimal solution is impossible to further enhance on one target dimension without reducing the quality of another target (Charpentier, 2015;Drechsler et al, 2017). The set of Pareto solutions facilitates an unbiased trade-off analysis between the targets (Charpentier, 2015;Coello, 2006). Consequently, a trade-off analysis of WT planning targets provides insights beyond optimal allocation solutions towards a better understanding of interdependencies between different constraints and targets.…”

What Have We Learned from the Land Sparing-sharing Model?

“…It is a model, and so all assumptions can be varied and tested. Further modifications have been suggested to incorporate species dispersal and source-sink dynamics [71], heterogeneity at multiple scales [15,22], analysis of outcomes for food security and human wellbeing [72], use of optimisation techniques and more complex mixes of land use [73] and replacement of imprecise terms such as "win-wins" with more clearly-defined concepts such as Pareto improvement [74]. An important challenge is to move beyond vote-counting towards developing conservation plans that ensure populations of all species in a region are sustained.…”

Lessons from Ethiopian coffee landscapes for global conservation in a post-wild world

“…When exploring the relationship between biodiversity and provisioning ecosystem services, such as food or fibre, it is common – but far from universal (see below) – to find a trade-off between the two 40 – 42 . Especially in a context of single-crop oriented industrial agriculture, it is difficult to increase the production of goods without harming the biodiversity or ecosystem 43 .…”

“…2b ). Yet, even in agroforestry systems like shade grown coffee or cocoa, it is naïve to believe that it is possible to manage for maximum productivity and revenue at the same time as maintaining the highest biodiversity values 40 , 58 , as also exemplified in the Ethiopian case. However, by exploring the underlying drivers of biodiversity-yield trade-off curves along broad gradients it is easier to develop conservation and management policy and plans both at the landscape scale and site level to reach societal goals of both yields (revenue) and biodiversity 59 .…”