Geology topics

Zhiliang Zhu

Publications and source records attributed to Zhiliang Zhu.

At least 19 recordsLinked to original sources

USGS2026

The accelerating loss and shifting dynamics of US tidal wetlands

Tidal wetlands are critical ecosystems for coastal sustainability, yet despite growing regulatory protection, they continue to decline globally. Their long-term resilience to interacting chronic stressors and extreme events remains uncertain, in part because comprehensive, high-frequency monitoring has been lacking. While direct land-use conversion has been substantially restricted in the United States, the true trajectory of these protected habitats has remained unclear. Here, we use four decades of high-resolution satellite records to analyze the shifting dynamics of US tidal wetlands. We reveal a widespread and previously unquantified acceleration in the rate of tidal wetland loss, amounting to a net loss of −1640 km 2 at the rate of −40.53 km 2 year −1 , accelerating by −0.73 km 2 year −2 , of which tidal marsh contributed the majority of this loss with a cumulative decline of 1567 km 2 . Furthermore, we show that the drivers of this decline are shifting: while chronic stressors like relative sea level rise have caused the largest cumulative loss (~60% of the total area loss), acute shocks from extreme weather now dominate (1.4 times that of the chronic stressors) the acceleration of that loss. By contrast, direct human activities were a minor driver, accounting for only 4% of total observed losses. These findings indicate that the resilience of these protected ecosystems is declining. It provides an urgent warning that existing conservation strategies, initially concerned with direct human impacts and increasingly focused on relative sea level rise as a slow-moving pressure, are ill-equipped for a future of increasing extreme weather events and highlights the need to redesign adaptation policies.

conterminous United States↗

USGS2026

Excessive phosphorus loading contributes to future vulnerability of mangrove ecosystems by reducing net ecosystem exchange of carbon

J.N. “Ding” Darling National Wildlife Refuge (DDNWR) is located on Sanibel Island along the southwestern coast of Florida, USA. There, eutrophication attributed to agricultural discharge along the Caloosahatchee River has affected the area’s aquatic habitat. In anticipation of additional nutrient loading, we experimentally fertilized mangrove forests with nitrogen (+N; NH4) and phosphorus (+P; P2O5) for 3 years, and monitored soil and pneumatophore CO2 fluxes and tree sap flow from two mangrove species. Furthermore, we modeled individual tree and stand water use, from which we developed carbon (C) budgets for +N and + P vs. control simulations based on a novel application of water use efficiency conversion. Many of the measured response variables provided hints of subtle changes in response to +P rather than +N, which were enhanced when scaled. From this, we found that additional P loading is expected to reduce both gross and net primary productivity as well as CO2 uptake via net ecosystem exchange of C, likely pressing the system beyond metabolic capacity and leading to a 48–62% decrease in projected lateral C export. Greater eutrophication will likely compound vulnerabilities to sea-level rise submergence, especially where P concentrations are high and already reducing soil surface elevations.

Florida↗

USGS2026

Vulnerability of mangrove resources to sea-level rise on Sanibel Island, Florida, USA

Accelerating sea-level rise (SLR) is poised to reshape coastal environments over the coming decades, providing a challenge to land managers who need actionable information. Mangroves have an innate ability to keep pace with some SLR but may drown under the higher rates projected by the end of the century. Understanding local mangrove resilience to SLR requires understanding of historic and contemporary accretion rates, productivity, and forest elevations relative to tidal inundation. We applied the WARMER3 modeling framework to assess future mangrove resilience to SLR and blue carbon storage across the “Ding” Darling National Wildlife Refuge on Sanibel Island in southwest Florida, USA. We found that Sanibel mangroves are sensitive to the SLR scenario, with projected losses ranging from 19 to 70% by 2100. Across SLR scenarios, projected areal extent was similar until about 2035 and then diverge, coincident with projected acceleration in the rate of SLR. Threshold analysis indicates found that Sanibel mangroves are likely to submerge when rates exceed 6.5 mm yr −1 . Currently, the mangrove forest of our study domain holds an estimated 214,000 Mg of carbon but is likely to decrease as mangroves convert to open water in the second half of this century. For “Ding” Darling, these site-specific projections identify when losses in mangrove resources are most likely, providing a basis to prioritize local management actions and conservation resources.

Florida↗

USGS2025

Land change, fire, and climate weaken carbon sink in the conterminous U.S.

The land carbon sink of the conterminous United States was evaluated using a bottom-up modeling framework and 30-meter land change data from 1985 to 2020. This cross-scale, cross-landscape, and cross-system approach tracked fractional land cover changes and applied regional model calibration. Results show average terrestrial and aquatic carbon sinks of +110 ± 37 and +19 ± 0.5 teragrams of carbon per year, respectively. The terrestrial carbon sink, showing no clear trend, peaked in the 1990s, with more years as a carbon source since 2000, contradicting recent national and global studies. Land change had the largest impact (−70 ± 5.5 teragrams of carbon per year), exceeding impacts of climate (−33 ± 48 teragrams of carbon per year), wildfire (−7.7 ± 2.4 teragrams of carbon per year), and erosion transport (−1.9 ± 0.13 teragrams of carbon per year). The positive CO2 fertilization effect (+69 ± 12 teragrams of carbon per year) was insufficient to maintain the carbon sink strength. Our framework reveals key paths of carbon loss, with implications for carbon budget and energy policies in the United States and beyond.

conterminous United States↗

USGS2025

U.S. Geological Survey research and assessments supporting carbon dioxide removal

Both carbon capture and storage (CCS) and carbon dioxide removal (CDR) are methods to limit future global temperature rise and ocean acidification. CCS sequesters (stores) carbon dioxide (CO2) captured from industrial sources thereby preventing the CO2 from reaching the atmosphere. The captured CO2 is injected into underground geologic reservoirs or is converted into stable industrial products. CDR enhances natural processes or uses technical approaches to remove excess CO2 from the atmosphere. Carbon dioxide is sequestered in natural sinks such as vegetation and soil, or injected into underground reservoirs or converted into durable products. The U.S. Geological Survey (USGS) conducts research and resource assessments that support biologic and geologic CDR approaches. This report will review some of the ongoing USGS CDR research and assessment efforts.

Conference Paper↗

USGS2024

Tracking mangrove condition changes using dense Landsat time series

Mangroves in tropical and subtropical coasts are subject to episodic disturbances, notably from severe storms, leading to potential widespread vegetation mortality. The ability of vegetation to recover varies, and with disturbances becoming more frequent and severe, it is vital to track and project vegetation responses to support management and policy decisions. Prior studies have largely focused on binary mangrove mapping (i.e., presence or absence), while tracking conditions and condition change have not received sufficient attention. In this paper, we demonstrate a method based on dense time series Landsat images for continuous monitoring of mangrove conditions, where we track three kinds of post-disturbance mangrove conditions, including disturbed (disturbed, with rebound to the previous state within one growing season), recovering (undergoing natural recovery in longer than one growing season), and declining (showing long-term decline after disturbance). The method starts with disturbance detection using the DEtection and Characterization Of the tiDal wEtland change (DECODE) algorithm, an existing dense time series model designed to detect disturbances in tidal wetlands with adaptation to tidal fluctuations. This algorithm is well suited for the detection of tidal wetland disturbances but does not provide satisfactory post-disturbance monitoring results, due to the substantial variability in post-disturbance Landsat observations. To better monitor post-disturbance conditions, a new time series fitting approach, DECODER (DECODE and Recovery), is proposed for the recovery stage. Additionally, for temporal segments divided by disturbance events, we built a random forest classifier with temporal-spectral variables derived from the time series model to characterize mangrove conditions. Employing this approach in Florida's mangroves, we generated condition maps, such as dieback and recovery, with an overall accuracy of approximately 97.96 ± 0.86- [95 % confidence intervals]. Comparing post-hurricane conditions in Florida revealed that the increased frequency and severity of disturbances are challenging mangrove resilience, potentially diminishing their ability to recover and sustain ecosystem functions.

Florida↗

USGS2023

Above- and belowground biomass carbon stock and net primary productivity maps for tidal herbaceous marshes of the United States

Accurate assessments of greenhouse gas emissions and carbon sequestration in natural ecosystems are necessary to develop climate mitigation strategies. Regional and national-level assessments of carbon sequestration require high-resolution data to be available for large areas, increasing the need for remote sensing products that quantify carbon stocks and fluxes. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on how to quantify carbon flux using land cover land change and biomass carbon stock information. Net primary productivity (NPP), carbon uptake, and storage in vegetation, can also be used to model net carbon sequestration and net carbon export from an ecosystem (net ecosystem carbon balance). While biomass and NPP map products for terrestrial ecosystems are available, there are currently no conterminous United States (CONUS) biomass carbon stock or NPP maps for tidal herbaceous marshes. In this study, we used peak soil adjusted vegetation index (SAVI) values, derived from Landsat 8 composites, and five other vegetation indices, plus a categorical variable for the CONUS region (Pacific Northwest, California, Northeast, Mid-Atlantic, South Atlantic-Gulf, or Everglades), to model spatially explicit aboveground peak biomass stocks in tidal marshes (i.e., tidal palustrine and estuarine herbaceous marshes) for the first time. Tidal marsh carbon conversion factors, root-to-shoot ratios, and vegetation turnover rates, were compiled from the literature and used to convert peak aboveground biomass to peak total (above- and belowground) biomass and NPP. An extensive literature search for aboveground turnover rates produced sparse and variable values; therefore, we used an informed assumption of a turnover rate of one crop per year for all CONUS tidal marshes. Due to the lack of turnover rate data, the NPP map is identical to the peak biomass carbon stock map. In reality, it is probable that turnover rate varies by region, given seasonal length differences; however, the NPP map provides the best available information on spatially explicit CONUS tidal marsh NPP. This study identifies gaps in the scientific knowledge, to support future studies in addressing this lack of turnover data. Across CONUS, average total peak biomass carbon stock in tidal marshes was 848 g C m −2 (871 g C m −2 in palustrine and 838 g C m −2 in estuarine marshes), and based on a median biomass turnover rate of 1, it is expected that the mean NPP annual flux for tidal marshes is similar (e.g., 848 g C m −2 y −1 ). Peak biomass carbon stocks in tidal marshes were lowest in the Florida Everglades region and highest in the California regions. These are the first fine-scale national maps of biomass carbon and NPP for tidal wetlands, spanning all of CONUS. These estimates of CONUS total peak biomass carbon stocks and NPP rates for tidal marshes can support regional- and national-scale assessments of greenhouse gas emissions, as well as natural resource management of coastal wetlands, as part of nature-based climate solution efforts.

Remote Sensing↗

USGS2023

Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA)

J.N. “Ding” Darling National Wildlife Refuge (DDNWR) is located on Sanibel Island along the southwestern coast of Florida, USA. Sanibel Island is heavily developed, but DDNWR provides protection for a large mangrove area that supports biodiversity and recreational opportunity. However, nitrogen (N) and phosphorus (P) eutrophication attributed to agriculture discharge along the Caloosahatchee River has affected the area’s aquatic habitat with algal blooms and may be causing untimely degradation of Sanibel’s mangrove forests. We launched a series of studies to understand how additional nutrient loading to the levels expected in the future might affect DDNWR’s mangrove resource. We experimentally fertilized selected mangrove forest areas with N fertilizer (+N; NH4) and P fertilizer (+P; P 2 O 5 ) for three years, and monitored soil surface elevation change, soil and pneumatophore CO 2 fluxes from respiration, mangrove tree sap flow from two species ( Avicennia germinans , Rhizophora mangle ), and individual tree and stand water use, from which we developed carbon (C) budgets for +N and +P vs. control simulations as applied to DDNWR’s 1112 ha mangrove area. Many of the measured response variables provided hints of subtle changes in response to +P rather than +N, which were compounded when scaled. From this, we found that additional P loading is expected to stimulate CO 2 uptake via net ecosystem exchange of C, likely pressing the system beyond metabolic capacity and leading to a projected 41% increase in lateral C export to the estuary. Additional lateral C export is concomitant to a reduction in vertical soil surface elevation with +P. Furthermore, an inability of DDNWR’s mangroves to bury additional P and a release of P-bound ions to lateral export may exacerbate estuarine eutrophication. We also modelled the effect of sea-level rise influences on DDNWR’s mangroves through 2100 using a soil cohort model (WARMER-Mangroves) and found that the mangroves may be resilient to current rates of sea-level rise into the future but may also be susceptible to moderate accelerations. Greater eutrophication could create additional vulnerabilities to mangrove submergence, especially to basin mangroves where P concentrations are high and already reducing soil surface elevations in some mangroves. Our results suggest that amelioration of current P concentrations and avoidance of additional P loading to Sanibel Island’s mangroves are management options to consider.

Florida↗

USGS2022

A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia

Mangrove forests are the most important ecosystems on Pohnpei Island, Federated States of Micronesia, as the island communities of the central Pacific rely on the forests for many essential services including protection from sea-level rise that is occurring at a greater pace than the global average. As part of a multi-component assessment to evaluate vulnerabilities of mangrove forests on Pohnpei, mangrove forests were mapped at two points in time: 1983 and 2018. In 2018, the island had 6,426 ha of mangrove forest. Change analysis indicated a slight (0.76%) increase of mangrove area between 1983 and 2018, contrasting with global mangrove area declines. Forest structure and aboveground carbon (AGC) stocks were inventoried using a systematic sampling of field survey plots and extrapolated to the island using k-nearest neighbor and random forest species models. A gridded or wall to wall approach is suggested when possible for defining carbon stocks of a large area due to high variability seen in our data. The k-nearest neighbor model performed better than random forest models to map species dominance in these forests. Mean AGC was 167 ± 11 MgC ha -1 , which is greater than the global average of mangroves (115 ± 7 MgC ha -1 ) but within their global range (37–255 MgC ha -1 ) Kauffman et al. (2020). In 2018, Pohnpei mangroves contained over 1.07 million MgC in AGC pools. By assigning the mean AGC stock per species per area to the map, carbon stock distributions were visualized spatially, allowing future conservation efforts to be directed to carbon dense stands.

Pohnpei Island↗

USGS2022

Operational assessment tool for forest carbon dynamics for the United States: A new spatially explicit approach linking the LUCAS and CBM-CFS3 models

Background Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Results We estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year −1 . Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source. Conclusions The new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.

Continental United States↗

USGS2022

Active forest management accelerates carbon storage in plantation forests in Lishui, southern China

Background China has committed to achieving peak CO 2 emissions before 2030 and carbon neutrality before 2060; therefore, accelerated efforts are needed to better understand carbon accounting in industry and energy fields as well as terrestrial ecosystems. The carbon sink capacity of plantation forests contributes to the mitigation of climate change. Plantation forests throughout the world are intensively managed, and there is an urgent need to evaluate the effects of such management on long-term carbon dynamics. Methods We assessed the carbon cycling patterns of ecosystems characterized by three typical plantation species (Chinese fir ( Cunninghamia lanceolata (Lamb.) Hook.), oak ( Cyclobalanopsis glauca (Thunb.) Oerst.), and pine ( Pinus massoniana Lamb.)) in Lishui, southern China, by using an integrated biosphere simulator (IBIS) tuned with localized parameters. Then, we used the state-and-transition simulation model (STSM) to study the effects of active forest management (AFM) on carbon storage by combining forest disturbance history and carbon cycle regimes. Results 1) The carbon stock of the oak plantation was lower at an early age (<50 years) but higher at an advanced age (>50 years) than that of the Chinese fir and pine plantations. 2) The carbon densities of the pine and Chinese fir plantations peaked at 70 years (223.36 Mg·ha ‒1 ) and 64 years (232.04 Mg·ha ‒1 ), respectively, while the carbon density in the oak plantation continued increasing (>100 years). 3) From 1989 to 2019, the total carbon pools of the three plantation ecosystems followed an upward trend (an annual increase of 0.16–0.22 Tg C), with the largest proportional increase in the aboveground biomass carbon pool. 4) AFM increased the recovery of carbon storage after 1996 and 2009 in the pine and Chinese fir plantations, respectively, but did not result in higher growth in the oak plantation. 5) The proposed harvest planning is reasonable and conducive to maximizing the carbon sequestration capacity of the forest. Conclusions This study provides an example of a carbon cycle coupling model that is potentially suitable for simulating China's plantation forest ecosystems and supporting carbon accounting to monitor peak CO 2 emissions and reach carbon neutrality.

Lishui↗

USGS2022

Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?

Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.

Great Xing'an Mountains↗

USGS2022

Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series

Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management . Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km 2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km 2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.

Remote Sensing of Environment↗

USGS2021

Summary of wetland carbon and environmental management: Path forward

Wetlands around the world are under pressure from both anthropogenic sources such as land-use change and accelerating climate change (Erwin, 2009; Moomaw et al., 2018). Storage of carbon resources is a key ecosystem service of wetlands and offer natural solutions to climate change mitigation; policies and management actions could determine the fate of these resources and their contributions to climate mitigation and society needs. Inland and tidal wetlands store and sequester more carbon in soil and biomass than any other ecosystems on a per unit area basis, but also are responsible for the majority of ecosystem methane emissions (NASEM, 2019; Knox et al., 2019). Most of wetland carbon is stored deep in soils, thus providing long-term preservation of the resource (Nahlik and Fennessy, 2016). In addition to productive carbon sequestration in situ, wetlands also play a major role in lateral fluxes of carbon and other greenhouse gases along the continuum of different landscape features, including lakes, rivers, and coastal waters (Aufdenkampe et al., 2011; Ciais et al., 2008; Troxler et al., 2013). The ability of wetlands to regulate key processes of the carbon cycle is related to characteristics of the ecosystem, particularly hydrologic functions (Zhou et al., 2018). Disturbances to wetland hydrology, from land use change to natural disturbances such as wildfire, could lead to major disruptions to the wetland carbon cycle (Moomaw et al., 2018). This book is organized to first introduce fundamentals of wetland biogeochemistry (Neubauer and Megonigal, 2020) and carbon stock distribution and management in broad geographic and temporal domains, then provide a more in-depth treatment of case studies of different wetland types across the world (Fig. 1). A range of wetland management actions are described in the context of carbon sequestration and greenhouse gas emissions, including hydrology, sediment, avoided loss, restoration, wildfire, and co-habitation of multiple uses. Different wetland types or land uses considered in this book include freshwater herbaceous wetlands, peatlands of temperate as well as tropical climate, coastal tidal marshes and mangroves, drained croplands, and rice paddies.

Book chapter↗

USGS2021

Preface to book: Wetland carbon and environmental management

The idea for this book, including its organization and contents, has its origin in the latest environmental and climate policy requirements in the United States, as well as science advances. In 2007, the U.S. Congress passed the Energy Independence and Security Act (EISA), from which Section 712 required U.S. Federal agencies to provide a better understanding of carbon and greenhouse gas fluxes across the United States. As a result, largescale and coordinated efforts were launched to assess carbon storage, carbon fluxes, and greenhouse gas fluxes including CO2, CH4, and N2O from all major terrestrial and freshwater aquatic ecosystems, including forest, grassland/shrub, agricultural lands, wetlands, and rivers, streams, lakes, and impoundments. The EISA assessment produced major results (Selmants et al., 2017; Zhu, 2011; Zhu & McGuire, 2016; Zhu & Reed, 2012, 2014), but recognized that wetlands remained a significant source of uncertainty, especially for those wetlands that were being actively managed. The more recent Second State of the Carbon Cycle Report by the U.S. Global Change Research Program (USGCRP), which devoted two separate chapters to inland and coastal wetlands, respectively, noted that large knowledge gaps still remain, ranging from inadequate analysis of restored and managed wetlands, and consequences of management decisions, to future wetland responses to climate change (USGCRP, 2018). In recent literature, wetland management is suggested as a potential natural solution to mitigate climate change (Fargione et al., 2018, Kroeger et al., 2017) and help offset direct losses of wetlands from sea level rise, subsidence, and coastal erosion (Wang et al., 2017). The recognition that a synthesis of wetland carbon management was urgently needed was the genesis of Wetland Carbon and Environmental Management; discerning the relationships between wetland management and carbon flux (loss or gain) is an international goal.

Geophysical Monograph Series↗

USGS2021

The changes in species composition mediate direct effects of climate change on future fire regimes of boreal forests in northeastern China

Direct effects of climate change (i.e. temperature rise, changes in seasonal precipitation, wind patterns and atmospheric stability) affect fire regimes of boreal forests by altering fire behaviour, fire seasons and fuel moisture. Climate change also alters species composition and fuel characteristics, which subsequently alter fire regimes. However, indirect effects of climate change are often simplified or neglected in the direct climate–fire relationship models and dynamic global vegetation models. This may result in high uncertainties associated with existing projections of fire regimes for climate change scenarios. Moreover, few studies have examined fire regime predictions beyond the 21st century, and consequently, how the fire regimes of boreal forests would respond to climate change at the long term (>100 years) are not clear. We develop a coupled modelling framework integrating direct and indirect effects of climate change to predict fire occurrence probability and burned area for boreal forests in northeastern China. We applied repeated measures ANOVA to quantify direct and indirect effects of climate change on fire regimes in the short (0–50 years), medium (60–100 years) and long term (150–200 years). Results showed that for the 21st century, direct effects of climate change are likely to exert a stronger influence on fire regimes than indirect effects. However, increases in fire occurrence probability and burned area will accelerate the transition of boreal forests to temperate forests in the period 2100–2200, and thereby reduce fire occurrence probability and burned area. This suggests that vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. Synthesis and applications . Vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. This finding suggested that policymakers may consider adaptive management by planting deciduous species to reduce fire occurrence probability and resistant management by reducing competition to promote boreal species under changing climate conditions.

Journal of Applied Ecology↗

USGS2021

Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida

Studies integrating mangrove in-situ observations and remote sensing analysis for specific sites often lack precise estimates of carbon stocks over time frames that include disturbance events. This study quantifies change in mangrove area from 1985 to 2018 with Landsat time series analysis, estimates above and belowground stored carbon using field data, and evaluates aboveground carbon stock changes after the 2004 Category 4, Hurricane Charley, in J.N. “Ding” Darling National Wildlife Refuge. Two allometric equation methods yielding similar results were used to estimate aboveground carbon content in three mangrove species found in the refuge. Aboveground carbon contained 67 (SE = 2) MgC ha −1 with a total refuge estimate of 74,504 MgC in 2018. Sediment contained 259 (SE = 28) MgC ha −1 for a total of 288,008 MgC in the refuge. The initial reduction in mangrove area caused by Hurricane Charley was between 0.6% and 5.3%, equivalent to between 427 MgC and 3,599 MgC under three different scenarios of carbon loss. As a result of the hurricane, approximately 61 ha of mangroves were disturbed, of which 24 ha had recovered by 2018, with 37 ha (~3% of the pre-hurricane mangrove area) still not recovered 14 years after the event. The 37 ha of mangroves that have not recovered are located in a tidally restricted area of the refuge. A longer recovery time in this area will likely result in a greater loss of carbon storage than in the rest of the refuge.

Florida↗

USGS2020

Increased burning in a warming climate reduces carbon uptake in the Greater Yellowstone Ecosystem despite productivity gains

1. The effects of changing climate and disturbance on mountain forest carbon stocks vary with tree species distributions and over elevational gradients. Warming can increase carbon uptake by stimulating productivity at high elevations but also enhance carbon release by increasing respiration and the frequency, intensity, and size of wildfires. 2. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species, and their combined effects on regional carbon stocks in forests of the Greater Yellowstone Ecosystem, USA with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario. 3. Total ecosystem carbon increased by 67% through 2100 in simulations with historical climate, and by 38 – 69% with GCM climate. Differences in carbon uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper treeline, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27 – 215% under GCM climate, with the largest increases after 2050. With warming >3 °C in mean annual temperature, the increased frequency of large fires reduced live carbon stocks by 4 – 36% relative to the control, historical climate scenario. However, relative losses in total carbon were delayed under GCMs with large increases in summer precipitation and buffered by carbon retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and carbon uptake. 4. Synthesis. Forests in the GYE can maintain a carbon sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live aboveground biomass, and ultimately, ecosystem carbon. Future changes in carbon stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions.

Idaho, Montana, Wyoming↗