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Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from Ω decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yr⁻¹, but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yr⁻¹) is considered in discussion on the use of flux data to validate and interpolate models.

Twenty common plant species were screened for emissions of biogenic volatile organic compounds (BVOCs) at a lowland tropical wet forest site in Costa Rica. Ten of the species examined emitted substantial quantities of isoprene. These species accounted for 35-50% of the total basal area of old-growth forest on the major edaphic site types, indicating that a high proportion of the canopy leaf area is a source of isoprene. A limited number of canopy-level BVOC flux measurements were also collected by relaxed eddy accumulation (REA). These measurements verify that the forest canopy in this region is indeed a significant source of isoprene. In addition, REA fluxes of methanol and especially acetone were also significant, exceeding model estimates and warranting future investigation at this site. Leaf monoterpene emissions were non-detectable or very low from the species surveyed, and ambient concentrations and REA fluxes likewise were very low. Although the isoprene emission rates reported here are largely consistent with phylogenetic relations found in other studies (at the family, genus, and species levels), two species in the family Mimosaceae, a group previously found to consist largely of non-isoprene emitters, emitted significant quantities of isoprene. One of these, Pentaclethra macroloba (Willd.) Kuntze, is by far the most abundant canopy tree species in the forests of this area, composing 30-40% of the total basal area. The other, Zygia longifolia (Humb. & Bonpl.) Britton & Rose is a common riparian species. Our results suggest that the source strength of BVOCs is important not only to tropical atmospheric chemistry, but also may be important in determining net ecosystem carbon exchange.