Climate-human interaction associated with southeast Australian megafauna extinction patterns

The mechanisms leading to megafauna (>44 kg) extinctions in Late Pleistocene (126,000-12,000 years ago) Australia are highly contested because standard chronological analyses rely on scarce data of varying quality and ignore spatial complexity. Relevant archaeological and palaeontological records are most often also biased by differential preservation resulting in under-representated older events. Chronological analyses have attributed megafaunal extinctions to climate change, humans, or a combination of the two, but rarely consider spatial variation in extinction patterns, initial human appearance trajectories, and palaeoclimate change together. Here we develop a statistical approach to infer spatio-temporal trajectories of megafauna extirpations (local extinctions) and initial human appearance in south-eastern Australia. We identify a combined climate-human effect on regional extirpation patterns suggesting that small, mobile Aboriginal populations potentially needed access to drinkable water to survive arid ecosystems, but were simultaneously constrained by climate-dependent net landscape primary productivity. Thus, the co-drivers of megafauna extirpations were themselves constrained by the spatial distribution of climate-dependent water sources.Frédérik Saltré, Joël Chadoeuf, Katharina J. Peters, Matthew C. McDowell, Tobias Friedrich, Axel Timmermann, Sean Ulm and Corey J. A. Bradsha

Guidelines and considerations for designing field experiments simulating precipitation extremes in forest ecosystems

1. Precipitation regimes are changing in response to climate change, yet understanding of how forest ecosystems respond to extreme droughts and pluvials remains incomplete. As future precipitation extremes will likely fall outside the range of historical variability, precipitation manipulation experiments (PMEs) are critical to advancing knowledge about potential ecosystem responses. However, few PMEs have been conducted in forests compared to short‐statured ecosystems, and forest PMEs have unique design requirements and constraints. Moreover, past forest PMEs have lacked coordination, limiting cross‐site comparisons. Here, we review and synthesize approaches, challenges, and opportunities for conducting PMEs in forests, with the goal of guiding design decisions, while maximizing the potential for coordination. 2. We reviewed 63 forest PMEs at 70 sites world‐wide. Workshops, meetings, and communications with experimentalists were used to generate and build consensus around approaches for addressing the key challenges and enhancing coordination. 3. Past forest PMEs employed a variety of study designs related to treatment level, replication, plot and infrastructure characteristics, and measurement approaches. Important considerations for establishing new forest PMEs include: selecting appropriate treatment levels to reach ecological thresholds; balancing cost, logistical complexity, and effectiveness in infrastructure design; and preventing unintended water subsidies. Response variables in forest PMEs were organized into three broad tiers reflecting increasing complexity and resource intensiveness, with the first tier representing a recommended core set of common measurements. 4. Differences in site conditions combined with unique research questions of experimentalists necessitate careful adaptation of guidelines for forest PMEs to balance local objectives with coordination among experiments. We advocate adoption of a common framework for coordinating forest PME design to enhance cross‐site comparability and advance fundamental knowledge about the response and sensitivity of diverse forest ecosystems to precipitation extremes.New Hampshire Agricultural Experiment Station, Grant/Award Number: NH00071-M; Northern States Research Cooperative, Grant/Award Number: 14-DG-11242307- 142; National Science Foundation Long-Term Ecological Research, Grant/Award Number: 1637685; USDA Forest Service; University of New Hampshire; NASA, Grant/Award Number: NNX14AD31G; USDA National Institute of Food and Agriculture McIntire- Stennis Project, Grant/Award Number: NH00071-M; U.S. Department of Energy; Office of Science’s Terrestrial Ecosystem Science program; Pacific Northwest National Labs’ LDRD program; MSCA-IF 2015; EU-Horizon2020 program; NSF’s Research Coordination Network Progra