Ecological and societal disruptions by modern climate change are critically determined by the time frame over which climates shift beyond historical analogues. Here we present a new index of the year when the projected mean climate of a given location moves to a state continuously outside the bounds of historical variability under alternative greenhouse gas emissions scenarios. Using 1860 to 2005 as the historical period, this index has a global mean of 2069 (±18 years s.d.) for near-surface air temperature under an emissions stabilization scenario and 2047 (±14 years s.d.) under a ‘business-as-usual’ scenario. Unprecedented climates will occur earliest in the tropics and among low-income countries, highlighting the vulnerability of global biodiversity and the limited governmental capacity to respond to the impacts of climate change. Our findings shed light on the urgency of mitigating greenhouse gas emissions if climates potentially harmful to biodiversity and society are to be prevented.

Focal Taxa: Laupala, AMC Clade Drosophila, Tetragnatha, and Nesosydne. We assembled comprehensive occurrence datasets of all known records for each of the four lineages (included here), modeled their distributions using Maxent across the entire archipelago, and quantified niche overlap. Final base layers Mean Annual Air Temperature (°C), Mean Annual Rainfall (mm), Vegetation Height (m), and Normalized Difference Vegetation Index (NDVI) were selected based on optimum AUC values of trial models run. Rasters were obtained for the Rainfall Atlas of Hawaii, Climate of Hawaii, and USGS and resampled to a ~1km by ~1km resolution using smoothing for quantitative variables and nearest neighbor resampling for categorical variables (Giambelluca et al. 2013, Giambelluca et al. 2014, Hawaii Soil Survey 2000). Data presented here are the full set of georeferenced occurrence records, the filtered model inputs, and the final SDM models in ASCII format for each species. See the supplementary material in the corresponding publication (Hiller et al. 2017) for details on the georeferencing protocols used and a list of museum specimen numbers. Note that not all models were included in subsequent analyses due to poor quality (<3 records as model input or low AUC score)

The Hawaiian Islands have one of the most spatially diverse rainfall patterns on earth. Knowledge of these patterns is critical for a variety of resource management issues and, until now, only long‐term mean monthly and annual rainfall maps have been available for Hawai‘i. In this study, month‐year rainfall maps from January 1920 to December 2012 were developed for the major Hawaiian Islands. The maps were produced using climatologically aided interpolation (CAI), where the station anomalies were interpolated first, and then combined with the mean maps. A geostatistical method comparison was performed to choose the best interpolation method. The comparison focuses on three kriging algorithms: ordinary kriging (OK), ordinary cokriging (OCK), and kriging with an external drift (KED). Two covariates, elevation and mean rainfall, were tested with OCK and KED. The combinations of methods and covariates were compared using cross‐validation statistics, where OK produced the lowest error statistics. Station anomalies for each month were interpolated using OK and combined with the mean monthly maps to produce the final month‐year rainfall maps.

Under climate change, ecosystems are experiencing novel drought regimes, often in combination with stressors that reduce resilience and amplify drought’s impacts. Consequently, drought appears increasingly likely to push systems beyond important physiological and ecological thresholds, resulting in substantial changes in ecosystem characteristics persisting long after drought ends (i.e., ecological transformation). In the present article, we clarify how drought can lead to transformation across a wide variety of ecosystems including forests, woodlands, and grasslands. Specifically, we describe how climate change alters drought regimes and how this translates to impacts on plant population growth, either directly or through drought's interactions with factors such as land management, biotic interactions, and other disturbances. We emphasize how interactions among mechanisms can inhibit postdrought recovery and can shift trajectories toward alternate states. Providing a holistic picture of how drought initiates long-term change supports the development of risk assessments, predictive models, and management strategies, enhancing preparedness for a complex and growing challenge.