Freshwater wetlands have a disproportionately large influence on the global carbon cycle, with the potential to serve as long-term carbon sinks. Many of the world's freshwater wetlands have been destroyed or degraded, thereby affecting carbon-sink capacity. Ecological restoration of degraded wetlands is thus becoming an increasingly sought-after natural climate solution. Yet the time required to revert a degraded wetland from a carbon source to sink remains largely unknown. Moreover, increased methane (CH₄) and nitrous oxide (N₂O) emissions might complicate the climate benefit that wetland restoration may represent. We conducted a global meta-analysis to evaluate the benefits of wetland restoration in terms of net ecosystem carbon and greenhouse gas balance. Most studies (76 %) investigated the benefits of wetland restoration in peatlands (bogs, fens, and peat swamps) in the northern hemisphere, whereas the effects of restoration in non-peat wetlands (freshwater marshes, non-peat swamps, and riparian wetlands) remain largely unexplored. Despite higher CH₄ emissions, most restored (77 %) and all natural peatlands were net carbon sinks, whereas most degraded peatlands (69 %) were carbon sources. Conversely, CH₄ emissions from non-peat wetlands were similar across degraded, restored, and natural non-peat wetlands. When considering the radiative forcings and atmospheric lifetimes of the different greenhouse gases, the average time for restored wetlands to have a net cooling effect on the climate after restoration is 525 years for peatlands and 141 years for non-peat wetlands. The radiative benefit of wetland restoration does, therefore, not meet the timeframe set by the Paris Agreement to limit global warming by 2100. The conservation and protection of natural freshwater wetlands should be prioritised over wetland restoration as those ecosystems already play a key role in climate change mitigation.

Farm dams are a ubiquitous limnological feature of agricultural landscapes worldwide. While their primary function is to capture and store water, they also have disproportionally large effects on biodiversity and biogeochemical cycling, with important relevance to several Sustainable Development Goals (SDGs). However, the abundance and distribution of farm dams is unknown in most parts of the world. Therefore, we used artificial intelligence and remote sensing data to address this critical global information gap. Specifically, we trained a deep learning convolutional neural network (CNN) on high-definition satellite images to detect farm dams and carry out the first continental-scale assessment on density, distribution and historical trends. We found that in Australia there are 1.765 million farm dams that occupy an area larger than Rhode Island (4678 km²) and store over 20 times more water than Sydney Harbour (10,990 GL). The State of New South Wales recorded the highest number of farm dams (654,983; 37% of the total) and Victoria the highest overall density (1.73 dams km⁻²). We also estimated that 202,119 farm dams (11.5%) remain omitted from any maps, especially in South Australia, Western Australia and the Northern Territory. Three decades of historical records revealed an ongoing decrease in the construction rate of farm dams, from >3% per annum before 2000, to ~1% after 2000, to <0.05% after 2010—except in the Australian Capital Territory where rates have remained relatively high. We also found systematic trends in construction design: farm dams built in 2015 are on average 50% larger in surface area and contain 66% more water than those built in 1989. To facilitate sharing information on sustainable farm dam management with authorities, scientists, managers and local communities, we developed AusDams.org—a free interactive portal to visualise and generate statistics on the physical, environmental and ecological impacts of farm dams.

Agricultural ponds have some of the highest methane emissions per area among freshwater systems, and these anthropogenic emissions should be included in national greenhouse gas inventories. Here we deliver a continental-scale assessment of methane emissions from agricultural ponds in the United States and Australia. We source maps of agricultural ponds, compile a meta-analysis for their emissions and use published data to correct for temperature and the relative contributions of two methane fluxes (diffusion and ebullition). In the United States, 2.56 million agricultural ponds cover 420.9 kha and emit about 95.8 kt year⁻¹ of methane. In Australia, 1.76 million agricultural ponds cover 291.2 kha and emit about 75.1 kt year⁻¹ of methane. Despite large uncertainties, our findings suggest that small water bodies emit twice as much methane than is currently accounted for in national inventories. Managing these systems can reduce these emissions while benefiting productivity, ecosystem services, and biodiversity.