Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems.

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

Equity trade-offs in conservation decision making.

Conservation decisions increasingly involve multiple environmental and social objectives, which result in complex decision contexts with high potential for trade-offs. Improving social equity is one such objective that is often considered an enabler of successful outcomes and a virtuous ideal in itself. Despite its idealized importance in conservation policy, social equity is often highly simplified or ill-defined and is applied uncritically. What constitutes equitable outcomes and processes is highly normative and subject to ethical deliberation. Different ethical frameworks may lead to different conceptions of equity through alternative perspectives of what is good or right. This can lead to different and potentially conflicting equity objectives in practice. We promote a more transparent, nuanced, and pluralistic conceptualization of equity in conservation decision making that particularly recognizes where multidimensional equity objectives may conflict. To help identify and mitigate ethical conflicts and avoid cases of good intentions producing bad outcomes, we encourage a more analytical incorporation of equity into conservation decision making particularly during mechanistic integration of equity objectives. We recommend that in conservation planning motivations and objectives for equity be made explicit within the problem context, methods used to incorporate equity objectives be applied with respect to stated objectives, and, should objectives dictate, evaluation of equity outcomes and adaptation of strategies be employed during policy implementation.

Global climatic drivers of leaf size.

Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves, the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot, sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich "next-generation" vegetation models in which leaf temperature and water use during photosynthesis play key roles.

Ecosystem services from a degraded peatland of Central Kalimantan: implications for policy, planning, and management.

Increasingly, landscapes are managed for multiple objectives to balance social, economic, and environmental goals. The Ex-Mega Rice Project (EMRP) peatland in Central Kalimantan, Indonesia provides a timely example with globally significant development, carbon, and biodiversity concerns. To inform future policy, planning, and management in the EMRP, we quantified and mapped ecosystem service values, assessed their spatial interactions, and evaluated the potential provision of ecosystem services under future land-use scenarios. We focus on key policy-relevant regulating (carbon stocks and the potential for emissions reduction), provisioning (timber, crops from smallholder agriculture, palm oil), and supporting (biodiversity) services. We found that implementation of existing land-use plans has the potential to improve total ecosystem service provision. We identify a number of significant inefficiencies, trade-offs, and unintended outcomes that may arise. For example, the potential development of existing palm oil concessions over one-third of the region may shift smallholder agriculture into low-productivity regions and substantially impact carbon and biodiversity outcomes. While improved management of conservation zones may enhance the protection of carbon stocks, not all biodiversity features will be represented, and there will be a reduction in timber harvesting and agricultural production. This study highlights how ecosystem service analyses can be structured to better inform policy, planning, and management in globally significant but data-poor regions.