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Many pressing conservation issues are complex problems caused by multiple social and environmental drivers; their resolution is aided by interdisciplinary teams of scientists, decision makers, and stakeholders working together. In these situations, how do we generate science to effectively guide conservation (resource management and policy) decisions? This paper describes elements of successful big-team science in conservation, as well as shortcomings and lessons learned, based on our work with the monarch butterfly (Danaus plexippus) in North America. We summarize literature on effective science teams, extracting information about elements of success, effective implementation approaches, and barriers or pitfalls. We then describe recent and ongoing conservation science for the monarch butterfly in North America. We focus primarily on the activities of the Monarch Conservation Science Partnership–an international collaboration of interdisciplinary scientists, policy experts and natural resource managers spanning government, non-governmental and academic institutions—which developed science to inform imperilment status, recovery options, and monitoring strategies. We couch these science efforts in the adaptative management framework of Strategic Habitat Conservation, the business model for conservation employed by the US Fish and Wildlife Service to inform decision-making needs identified by stakeholders from Canada, the United States, and Mexico. We conclude with elements critical to effective big-team conservation science, discuss why science teams focused on applied conservation problems are unique relative to science teams focusing on traditional or theoretical research, and list benefits of big team science in conservation.

Context: Grasslands of the North American Great Plains are among the world's most imperiled ecosystems. Determining landscapes at risk of grassland loss will benefit grassland conservation programs by enabling prioritization of parcels for acquisition. Objectives: We hypothesized that gradients in the amount of grass in local landscapes resulting from past conversion would be a useful predictor of future conversion. We developed simple, intuitive models predicting grassland conversion across the United States northern Great Plains. Methods: We used the grassland/herbaceous, pasture/hay, and emergent herbaceous wetland classes from the National Land Cover Database to evaluate grassland loss from 2001 to 2016. We classified the amount of grass in 13.2-km2 landscapes in 2001 into percentage bins and used generalized additive models to relate these values to the total and proportion of grassland lost, by percentage bin. We applied models to landcover data to create spatial surfaces predicting conversion. Results: Area of grass lost was highest in 40–60% grass bins, except for heavily cropped states, where highest losses occurred in 10–20% grass bins. Percentage of grass in local landscapes was generally a strong predictor of state-level total grassland loss and proportion of grassland lost. Predicted conversion for remaining grasslands varied within and among states. Conclusion: The amount of grass in local landscapes can be a useful indicator of grassland conversion. Our simple models complement species distribution models used to guide conservation in the region. Mechanistic models of conversion can be improved by including amount of grass in local landscapes. [ABSTRACT FROM AUTHOR]

The Perdido Key beach mouse (Peromyscus polionotus trissyllepsis), Choctawhatchee beach mouse (P. p. allophrys), and St. Andrew beach mouse (P. p. peninsularis) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well‐targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30‐m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post‐storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km2 of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives. © 2020 The Wildlife Society. This study aids coastal habitat managers by providing quantitative, spatially explicit decision support tools that estimate how much beach mouse habitat is available and how much more is needed to achieve established downlisting criteria related to habitat. These results could also guide selection of specific management actions, where those actions might be taken, and over how much critical habitat they must be applied. [ABSTRACT FROM AUTHOR]

Large-scale planning for the conservation of species is often hindered by a poor understanding of factors limiting populations. In regions with declining wildlife populations, it is critical that objective metrics of conservation success are developed to ensure that conservation actions achieve desired results. Using spatially explicit estimates of bird abundance, we evaluated several management alternatives for conserving bird populations in the Prairie Hardwood Transition of the United States. We designed landscapes conserving species at 50% of their current predicted abundance as well as landscapes attempting to achieve species population targets (which often required the doubling of current abundance). Conserving species at reduced (half of current) abundance led to few conservation conflicts. However, because of extensive modification of the landscape to suit human use, strategies for achieving regional population targets for forest bird species would be difficult under even ideal circumstances, and even more so if maintenance of grassland bird populations is also desired. Our results indicated that large-scale restoration of agricultural lands to native grassland and forest habitats may be the most productive conservation action for increasing bird population sizes but the level of landscape transition required to approach target bird population sizes may be societally unacceptable. [ABSTRACT FROM AUTHOR]