Mangrove forests are typically considered resilient to natural disturbances, likely caused by the evolutionary adaptation of species-specific traits. These ecosystems play a vital role in the global carbon cycle and are responsible for an outsized contribution to carbon burial and enhanced sedimentation rates. Using eddy covariance data from two coastal mangrove forests in the Florida Coastal Everglades, we evaluated the impact hurricanes have on mangrove forest structure and function by measuring recovery to pre-disturbance conditions following Hurricane Wilma in 2005 and Hurricane Irma in 2017. We determined the “recovery debt,” the deficit in ecosystem structure and function following a disturbance, using the leaf area index (LAI) and the net ecosystem exchange (NEE) of carbon dioxide (CO2). Calculated as the cumulative deviation from pre-disturbance conditions, the recovery debt incorporated the recapture of all the carbon lost due to the disturbance. In Everglades mangrove forests, LAI returned to pre-disturbance levels within a year, and ecosystem respiration and maximum photosynthetic rates took much longer, resulting in an initial recovery debt of 178 g C m−2 at the tall forest with limited impacts at the scrub forest. At the landscape scale, the initial recovery debt was 0.40 Mt C, and in most coastal mangrove forests, all lost carbon was recovered within just 4 years. While high-intensity storms could have prolonged impacts on the structure of subtropical forests, fast canopy recovery suggests these ecosystems will remain strong carbon sinks.
Understanding the fates of organisms and ecosystems under global change requires consideration of the organisms' rapid adaptation potential. In the Arctic, the recent temperature increase strongly impacts freshwater ecosystems which are important sentinels for climate change. However, a mechanistic understanding of the adaptive capacity of their key zooplankton grazers, among them polyploid, obligate parthenogenetic Daphnia, is lacking. Theory suggests low adaptation potential of asexual animals, yet examples exist of asexuals persisting through marked environmental changes. Here, we studied asexual Daphnia pulicaria from a meromictic lake in South-West Greenland. Its oxycline hosts purple sulfur bacteria (PSB), a potential food source for Daphnia. We tested two key phenotypic traits: (1) thermal tolerance as a response to rapid regional warming and (2) hypoxia tolerance tied to grazing of PSB in the hypoxic/anoxic transition zone. To assess Daphnia's adaptive capacity, we resurrected Daphnia from dormant eggs representing a historical subpopulation from 2011, sampled modern subpopulation representatives in 2022, and measured phenotypic variation of thermal (time to immobilization—Timm) and hypoxia tolerance (respiration rate and critical oxygen limit—Pcrit) in clonal lineages of both subpopulations. Whole genome sequencing of the tested clonal lineages identified three closely related genetic clusters, one with clones from both subpopulations and two unique to each subpopulation. We observed significantly lower Timm and a trend for higher Pcrit and respiration rates in the modern subpopulation, indicating a lower tolerance to both high temperature and hypoxia in comparison with the historical subpopulation. As these two traits share common physiological mechanisms, the observed phenotypic divergence might be driven by a relaxed selection pressure on hypoxia tolerance linked to variation in PSB abundance. Our results, while contrary to our expectation of higher thermal tolerance in the modern subpopulation, provide evidence for phenotypic change within a decade in this asexual Daphnia population.
Inland waters are significant sources of greenhouse gases (GHGs) in an increasingly human-dominated world, yet the mechanisms by which human activities reshape GHG emissions from these systems remain poorly understood. Here, we synthesized research from three human-dominated landscapes—agricultural, urban, and impounded river systems—to demonstrate that inland waters within these systems exhibit significantly higher GHG emissions compared to their natural or seminatural counterparts. This is particularly evident for CH4 and N2O emissions, which show median enhancement ratios of 2.0–10 and 2.4–13 across the systems, respectively. In contrast, CO2 emissions exhibit overall lower enhancement (median enhancement ratios of < 2.0–3.1), largely due to simultaneously increased photosynthetic uptake from aquatic eutrophication. These observations underscore a clear human footprint on aquatic GHG emissions and the underlying biogeochemical processes. The observed changes in GHG emissions are driven by increased inputs of sediments, carbon, and nutrients from human-disturbed landscapes, coupled with the expansion of aquatic anoxia resulting from increased aquatic metabolism, fine sediment deposition, and eutrophication. Beyond altering emission rates, human activities also modify the abundance and distribution of inland waters, potentially exerting substantial, yet unquantified, effects on landscape-scale GHG emissions. We highlight the importance of understanding these processes for accurately quantifying and mitigating the human footprint on aquatic GHG emissions. Future research and mitigation efforts should account for the variability and mechanisms discussed in this review to effectively address human-induced GHG emissions from inland waters.
Boreal forest regions, including East Siberia, have experienced elevated fire activity in recent years, leading to record-breaking greenhouse gas emissions and severe air pollution. However, our understanding of the factors that eventually halt fire spread and thus limit fire growth remains incomplete, hindering our ability to model their dynamics and predict their impacts. We investigated the locations and timing of 2.2 million fire stops—defined as 300 m unburned pixels along fire perimeters—across the vast East Siberian taiga. Fire stops were retrieved from remote sensing data covering over 27,000 individual fires that collectively burned 80 Mha between 2012 and 2022. Several geospatial datasets, including hourly fire weather data and landscape variables, were used to identify the factors contributing to individual fire stops. Our analysis attributed 87% of all fire stops to a statistically significant (p < 0.01) change in one or more of these drivers, with fire-weather drivers limiting fire growth over time and landscape drivers constraining it across space. We found clear regional and temporal variations in the importance of these drivers. For instance, landscape drivers—such as less flammable land cover and the presence of roads—were key constraints on fire growth in southeastern Siberia, where the landscape is more populated and fragmented. In contrast, fire weather was the primary constraint on fire growth in the remote northern taiga. Additionally, in central Yakutia, a major fire hotspot in recent years, fuel limitations from previous fires increasingly restricted fire spread. The methodology we present is adaptable to other biomes and can be applied globally, providing a framework for future attribution studies on global fire growth limitations. In northeast Siberia, we found that with increasing droughts and heatwaves, remote northern fires could potentially grow even larger in the future, with major implications for the global carbon cycle and climate.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：