Experiences with wildfire are associated with private landowners’ management decisions, relationships, and perceptions of risk - Clare Aslan; Ryan Tarver; Mark Brunson; Sam Veloz; Ben Sikes; Rebecca Epanchin-Niell (Landscape and Urban Planning, 2024)

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate - Kristin B. Byrd; Elliott Matchett; Claudia Mengelt; Tamara S. Wilson; Deanne DiPietro; Monica Moritsch; Erin Conlisk; Sam Veloz; Michael L. Casazza; Matthew E. Reiter (Conservation Biology, 2023)
Scientists, resource managers, and decision makers increasingly use knowledge coproduction to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley (USA) to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We coproduced scenario narratives, spatially explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We documented our coproduction process, and using the coproduced models, we determined when and where management actions make a difference and when climate overrides these actions. The outcomes of this process provide lessons learned on how to cocreate usable information and how to increase climate adaptive capacity in a highly managed landscape. Actions to restore wetlands and prioritize their water supply created habitat outcomes resilient to climate change impacts particularly in March, when habitat was most limited; land protection combined with management can increase the ecosystem's resilience to climate change; and uptake and use of this information was influenced by the roles of different stakeholders, rapidly changing water policies, discrepancies in decision‐making time frames, and immediate crises of extreme drought. Although a broad stakeholder group contributed knowledge to scenario narratives and model development, to coproduce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped build legitimacy. Yet, broadscale use of climate adaptation knowledge depends on state and local policies, engagement with decision makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.

The ice age ecologist: testing methods for reserve prioritization during the last global warming - John W. Williams; Heather M. Kharouba; Sam Veloz; Mark Vellend; Jason McLachlan; Zhengyu Liu; Bette Otto‐Bliesner; Feng He (Global Ecology and Biogeography, 2013)
Aim We play the role of an ice age ecologist (IAE) charged with conserving biodiversity during the climate changes accompanying the last deglaciation. We develop reserve‐selection strategies for the IAE and check them against rankings based on modern data. Location Northern and eastern North America. Methods Three reserve‐selection strategies are developed. (1) Abiotic: the IAE uses no information about species–climate relationships, instead maximizing the climatic and geographic dispersion of reserves. (2) Species distribution models (SDMs): the IAE uses boosted‐regression trees calibrated against pollen data and CCSM3 palaeoclimatic simulations from 21 to 15 ka bp to predict modern taxon distributions, then uses these as input to the Z onation reserve‐ranking program. (3) Rank‐and‐regress: regression models are used to identify climatic predictors of zonation rankings. All strategies are assessed against a Z onation ranking based on modern pollen distributions. Analysis units are ecoregions and grid cells. Results The abiotic strategy has a negative or no correlation between predicted and actual rankings. The SDM‐based strategy fares better, with a significantly positive area‐corrected correlation ( r = 0.474, P 0.001) between predicted and actual rankings. Predictive ability drops when grid cells are the analysis unit ( r = 0.217, P = 0.058). Predictive ability for the rank‐and‐regress strategy is similar to the SDM results. Main conclusions For the IAE, SDMs improve the predictive ability of reserve‐selection strategies. However, predictive ability is limited overall, probably due to shifted realized niches during past no‐analogue climates, new species interactions as species responded individually to climate change, and other environmental changes not included in the model. Twenty‐first‐century conservation planning also faces these challenges, and is further complicated by other anthropogenic impacts. The IAE's limited success does not preclude the use of climate scenarios and niche‐based SDMs when developing adaptation strategies, but suggests that such tools offer at best only a rough guide to identifying possible areas of future conservation value.