Long-term Monitoring Sites Research Articles

Assessing changes in threatened black rockcod Epinephelus daemelii abundance and length over the past 15 years in New South Wales, Australia.

Ideally, protection of a threatened fish will lead to their recovery in abundance, distribution, and size structure within the population, to a point where they are no longer considered threatened. Monitoring abundance and size is crucial to evaluate this, although low numbers associated with being threatened can strongly constrain the methods used. To assess if population recovery is occurring for the black rockcod Epinephelus daemelii, a large subtropical grouper endemic to shallow reefs in the southwest Pacific, surveys were undertaken across northern New South Wales and Lord Howe Island using roving diver timed counts and diver stereo-video measurements to assess relative abundance and length. Surveys in 2023 were compared with initial baseline data captured in 2009-2011 using the same methods. Relative abundance of E. daemelii at long-term monitoring sites has remained relatively constant or declined since 2010 rather than increasing. Comparisons between 84 broadscale sites in 2009-2011 versus 2023 (117 vs. 69 observed E. daemelii) indicate a recent decline in abundance. Although protected from fishing and spearfishing for over 40 years, the relative abundance of E. daemelii does not appear to be increasing over the past 15 years since monitoring commenced. This is a concerning trend that does not indicate recovery, although an increase in the proportion of mature females in the population from 2010 to 2023 is positive. As E. daemelii is slow growing, long lived, late to mature and still susceptible to incidental capture mortality, more active management may be needed to help assist with the slow recovery of this threatened species.

Co-mast: Harmonized seed production data for woody plants across US long-term research sites.

Plants display a range of temporal patterns of inter-annual reproduction, from relatively constant seed production to "mast seeding," the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long-lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community-level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long-Term Ecological Research (LTER) or long-term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community-level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent-scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.

The development and application of a new method for quantifying total atmospheric sulfur in the Alberta Oil Sands

ABSTRACT Continuous ambient sulfur measurements are routinely conducted around the globe at numerous monitoring sites impacted by industrial sources such as gas and oil processing facilities, pulp and paper mills, smelters, sewage treatment facilities, or concentrated animal feeding operations, as well as natural sources such as volcanoes. Various jurisdictions have or plan to establish Air Ambient Quality Objectives/Guidelines/Standards for Total Reduced Sulfur (TRS) based on odor perception and/or health effects. A conventional TRS monitoring technique is widely used, but few studies have looked at potential biases in the resulting TRS measurements. This paper presents a novel method to quantify Total Sulfur (TS) concentrations to investigate odor events caused by sulfur compounds, and to construct the sulfur budget for sulfur dioxide, particle sulfate, hydrogen sulfide (H2S) and the sum of all remaining reduced sulfur compounds (non-H2S RSCs). This methodology was tested and improved through multi-year monitoring (2013-2017) at the Oski-ôtin site in the indigenous community of Fort McKay, in the Alberta Oil Sands Region (AOSR). Comparisons with SO2 and conventional TRS data from two long-term monitoring sites located within five kilometers of Oski-ôtin suggest that the conventional approach for TRS is biased low by 20% on average. Based on this new method, Sulfur dioxide (SO2) was observed to be responsible for about 40% of the TS mass in Fort McKay, while TRS and particulate sulfate made up 50% and 10%, respectively. TRS dominated the distribution during winter months when SO2 plumes emitted from stacks tended to remain elevated due to diminished vertical mixing. During periods with TS below 5 ppb, which was 84% of the time, TRS (with H2S) accounted for 55% of the sulfur mass observed in Fort McKay.

Spatiotemporal Monitoring of Cropland Soil Organic Carbon Changes From Space.

Soil monitoring requires accurate and spatially explicit information on soil organic carbon (SOC) trends and changes over time. Spatiotemporal SOC models based on Earth Observation (EO) satellite data can support large-scale SOC monitoring but often lack sufficient temporal validation based on long-term soil data. In this study, we used repeated SOC samples from 1986 to 2022 and a time series of multispectral bare soil observations (Landsat and Sentinel-2) to model high-resolution cropland SOC trends for almost four decades. An in-depth validation of the temporal model uncertainty and accuracy of the derived SOC trends was conducted based on a network of 100 long-term monitoring sites that were continuously resampled every 5 years. While the general SOC prediction accuracy was high (R2 = 0.61; RMSE = 5.6 g kg-1), the direct validation of the derived SOC trends revealed a significantly greater uncertainty (R2 = 0.16; p < 0.0001), even though predicted and measured values showed similar distributions. Classifying the results into declining and increasing SOC trends, we found that 95% of all sites were either correctly identified or predicted as stable (p < 0.001), highlighting the potential of our findings. Increased accuracies for SOC trends were found in soils with higher SOC contents (R2 = 0.4) and sites with reduced tillage (R2 = 0.26). Based on the signal-to-noise ratio and temporal model uncertainty, we were able to show that the necessary time frame to detect SOC trends strongly depends on the absolute SOC changes present in the soils. Our findings highlight the potential to generate significant cropland SOC trend maps based on EO data and underline the necessity for direct validation with repeated soil samples and long-term SOC measurements. This study marks an important step toward the usability and integration of EO-based SOC maps for large-scale soil carbon monitoring.

Effects of burning on vegetation, soil physicochemistry and prokaryotic microbial communities in surface and subsurface peat

Prescribed burning is a common management strategy in peatlands that has the potential to affect soil physicochemistry, alter biogeochemical cycles and trigger changes in vegetation structure. How burning affects prokaryotic community composition across different soil profiles is not well understood. This study explored the effects of prescribed burning on the diversity of prokaryotic communities in peat soils. Soil samples were collected from Moor House Nature Reserve, UK, a long-term monitoring site initiated in 1954 subject to three burning treatments: Burning at short rotations every 10 years, burning at long rotations every 20 years and a non-burn control. Observed species richness for archaea was highest in the topsoil of the non-burn control plots and highest for bacteria in the topsoil of the non-burn control and plots under a long rotation regime. Community composition was significantly different between different burn treatments and soil depth. Archaeal community structure was shaped by NH4+ and pH in the topsoil; by Pb, moisture and Al in the 20–40 cm profile; and by total N, total C, Al, Ca, Fe and pH in the 40–60 cm profile. Bacterial community structure was shaped by NH4+, heather cover, pH and Mg in the topsoil; by Fe, K and Pb in the 20–40 cm profile; and by Al, Ca and Fe in the 40–60 cm profile. A co-occurrence network analysis revealed that the topsoil of the non-burn control plots had a more complex network structure with more positive links than those under a rotational burn, but a higher average connectivity with a higher number of negative links was observed in the long rotation 20–40 cm profile. The results provide a new insight into the response processes of soil prokaryotic communities to burning in peatland soils, providing valuable knowledge that can support the evaluation and management of ecosystem services in peatlands.

Mapping South Africa's canopy-forming kelp forests using low-cost, high-resolution Sentinel-2 imagery

Globally, kelp forests play a vital role in providing ecological, social and economic services. They contribute to the livelihoods and resilience of many coastal communities. To date, a gap exists in contemporary, comprehensive and consistent maps of South African kelp forests, since they were last mapped partially in 2006 by covering 900 km of South Africa's coastline. This study addresses this gap by producing a comprehensive remotely sensed high-resolution 2016 map of canopy forming coastal kelp forests. Using the 10m resolution Sentinel-2 A and B spectral bands 4 (RED) and 8 (NIR), an expert derived Normalized Difference Vegetation Index (NDVI) threshold was used to detect surface protruding kelp forests along 1300 km coastline. The results were validated with expert verification and using Google Earth, data from historic maps, remote sensing and biomass estimation of South African kelp resources. Our study demonstrates the aptitude of Sentinel-2 for detecting canopy-forming kelps at low cost along South Africa's west and south coast. We report the encountered drawbacks in mapping an expansive coastline with varied sea conditions including wave activity, tides and turbidity. Comprehensive ground validation, long-term monitoring sites and the use of time series datasets remain a gap towards improving the calibration of remote sensing methods and long-term monitoring of South African kelp forests. Our results provide a foundation for continuous monitoring of South African kelp forests as well as exploring other unmapped kelp/similar habitats to inform research and environmental management.

Influence of atmospheric state on variability of long-term residual ambient sound level measurements in a subalpine valley.

Two natural influences on the acoustic environments of mountainous parks and communities are flowing water and shifting weather. A central purpose of the acoustic measurement design used by the United States National Park Service is to provide spectral estimates of residual ambient sound level metrics at a seasonal time scale. Acoustic monitoring sampling methodologies are often designed using a sequence of similar measurements. When source and residual ambient spectra overlap, an estimate of variability in the latter is beneficial to successful monitoring design. The observed and modelled effects of atmospheric state on sound level are analyzed to reveal variability due to these effects at a long-term monitoring site in Denali National Park, Alaska. The analysis of variability incorporates a covariate that is otherwise challenging to estimate in remote settings: vertical temperature gradients in the atmospheric boundary layer. Results reveal inversions (positive gradients) in the atmosphere ≥30% between 19:00 and 09:00. Inversion strengths above 0.06 °C/m are associated with 10-15 dB increases in sound level over hourly time scales. Because inversions tend to occur during otherwise quiescent times of day, they ultimately reduce seasonal variability at the site and corresponding uncertainty in noise metrics for transportation noise arriving from varied directions.

Total deposition of sulphur to coniferous forests in Sweden - Taking canopy exchange into account

In the low deposition situation of today at many of the long-term Swedish forest monitoring sites, the deposition measured as precipitation to the open field, i.e. bulk deposition of oxidized sulphur (S) is often higher or equal to deposition of S sampled under the forest canopies, i.e. as throughfall. This suggests that the total S deposition estimated using throughfall is underestimated. The reason for this is direct exchange of S with the forest canopies, leading to an underestimation which becomes evident in low-deposition areas. We describe a new method to estimate the dry deposition of S to coniferous forest based on measurements with Teflon string samplers as surrogate surfaces, in combination with measurements of the net throughfall for sodium (throughfall subtracted with wet deposition). The wet deposition was estimated from bulk deposition measurements on the open field, corrected for dry deposition to the collectors. The method was applied for Norway spruce forests at monitoring sites across Sweden during nine years 2014–2022, and total deposition was calculated based on wet deposition and the estimated dry deposition. The estimated annual total deposition of S as a mean value for coniferous forests ranged between 0.8 and 5.2 kg S ha−1 yr−1 with lowest values in northern Sweden and highest in southwest Sweden. The share of dry deposition of the total S deposition was between 20 and 53%. The mean annual deposition of S measured as throughfall during 2014–2022 for three different regions in Sweden was between 16 and 41% lower compared to the corresponding total deposition estimated with the new method. The canopy exchange of S was analyzed on a monthly basis as the difference between the estimated total deposition and the measured throughfall deposition of S. At most sites, there was a canopy uptake of S during the summer months and a leakage of S during the winter months. This indicates that the canopy exchange of S is a phenomenon that involves some biological activity.

Tracking aquatic non-native macroinvertebrate species in Germany using long-term data

Biological invasions pose a global challenge, threatening both biodiversity and human well-being. Projections suggest that as invasions increase, the financial costs associated with management and the ecological harm they cause will also escalate. Here, we examined whether long-term biomonitoring strategies were adequate to identify and track benthic aquatic non-native macroinvertebrate species by using the German subset (151 time series; 129 of which reported non-native species) of the currently most comprehensive European long-term dataset of 1816 macroinvertebrate community time series from 22 European countries. The detection of aquatic non-native species was directly linked to the availability of long-term sites and thus, monitoring effort, having identified the spatio-temporal occurrence of 32 non-native species. The available long-term monitoring site data were mostly concentrated in the western part of Germany, predominantly covering the Rhine River and its tributaries. The spatially biased network of long-term monitoring sites, therefore, naturally skews the detection and reporting of aquatic non-native species toward this area and underestimates Eastern and Southern regions, impeding the comprehension of invasion dynamics. However, based on the available data, we found that the absolute number of non-native species increased and the proportion of non-native species relative to native species decreased over time. This indicates complex ecological interactions between native and non-native species and underlines the value of long-term data for investigating invasion dynamics. Considering the value of comprehensive monitoring networks, a spatially biased network delays the application of management and mitigation plans, possibly worsening the ecological and economic effects of biological invasions in Germany. The results provided here indicate the disadvantages of biased datasets, but simultaneously underline the enormous potential of a dense network of long-term monitoring. Our results also highlight the urgent need to increase and diversify long-term biomonitoring efforts throughout Germany to cover the main freshwater resources and their connections where the introduction risk of non-native species is the highest. Centrally collating such data would provide a profound basis for the monitoring of spreading aquatic non-native species and could serve the implementation of national biosecurity efforts.

Tree species richness and mycorrhizal types drive soil nitrogen cycling by regulating soil microbial community composition and diversity in tropical forests

A growing body of evidence indicates that tree mycorrhizal association and species richness pronouncedly affect soil nitrogen (N) cycling. However, most studies have been conducted in temperate forests, and the roles of soil microbial communities have been largely overlooked. Here, based on 11 long-term dynamic monitoring sites in tropical forests, we investigated the effects of the dominance of trees associated with arbuscular mycorrhizal (AM) (by basal area) and tree species richness on soil N cycling, and explored the role of soil bacteria, archaea and fungi. Our results showed contrasting effects of AM tree dominance and tree species richness, with AM tree dominance-induced increases in soil ammonium N, nitrate N and the rate of net N nitrification, and tree species richness-caused decreases in ammonium N, nitrate N, the rate of net N mineralization and ammonification. Moreover, we found that the “plant-soil-microbe” interactions mainly triggered the changes in net N mineralization, ammonification and nitrification. It was mainly bacterial composition that directly affected soil N mineralization and ammonification, while fungal diversity only changed soil N ammonification. For soil N nitrification, the abundance of ammonia-oxidizing archaea (AOA) was the main drivers. These findings reveal the discrepancy in effects of the AM tree dominance and tree species richness on soil N cycling, highlighting microbe-mediated mechanisms in regulating soil N mineralization, ammonification and nitrification.

20-year permafrost evolution documented through petrophysical joint inversion, thermal and soil moisture data

This study investigates the ground characteristics of the high altitude (3410 m a.s.l.) permafrost site Stockhorn in the Swiss Alps using a combination of surface and subsurface temperature, soil moisture, electrical resistivity and P-wave velocity time series data including a novel approach to explicitly quantify changes in ground ice content. This study was motivated by the clear signal of permafrost degradation visible in the full dataset at this long-term monitoring site within the PERMOS (Permafrost Monitoring Switzerland) network. Firstly, we assess the spatio-temporal evolution of the ground ice and water content by a combined analysis of all available in situ thermal (borehole and ground surface temperature), hydrological (soil moisture) and geophysical (geoelectric and seismic refraction) data over two decades (2002–2022) regarding the driving factors for the spatially different warming. Secondly, we explicitly quantify the volumetric water and ice content and their changes in the subsurface from 2015 to 2022 using a time-consistent petrophysical joint inversion scheme within the open-source library pyGIMLi. The petrophysical joint inversion scheme has been improved by constraining the rock content to be constant in time for six subsequent inversions to obtain consistent changes in ice and water content over the monitoring period based on jointly inverted resistivity and traveltime data. All different data show a warming trend of the permafrost. The ice content modeled from the petrophysical joint inversion has decreased by about 15 vol.% between 2015 and 2022. Changes in ice content are first observed in the lower, south-facing part of the profile. As a result, resistivity and P-wave velocity have been decreasing significantly. Permafrost temperatures measured in the boreholes have increased between 0.5 °C and 1 °C in 20 years. Our study shows the high value of joint and quantitative analysis of datasets comprising complementary subsurface variables for long-term permafrost monitoring.

Exploring the interplay between soil thermal and hydrological changes and their impact on carbon fluxes in permafrost ecosystems

Accelerated warming of the Arctic can affect the global climate system by thawing permafrost and exposing organic carbon in soils to decompose and release greenhouse gases into the atmosphere. We used a process-based biosphere model (DVM-DOS-TEM) designed to simulate biophysical and biogeochemical interactions between the soil, vegetation, and atmosphere. We varied soil and environmental parameters to assess the impact on cryohydrological and biogeochemical outputs in the model. We analyzed the responses of ecosystem carbon balances to permafrost thaw by running site-level simulations at two long-term tundra ecological monitoring sites in Alaska: Eight Mile Lake (EML) and Imnavait Creek Watershed (IMN), which are characterized by similar tussock tundra vegetation but differing soil drainage conditions and climate. Model outputs showed agreement with field observations at both sites for soil physical properties and ecosystem CO2 fluxes. Model simulations of Net Ecosystem Exchange (NEE) showed an overestimation during the frozen season (higher CO2 emissions) at EML with a mean NEE of 26.98 ± 4.83 gC/m2/month compared to observational mean of 22.01 ± 5.67 gC/m2/month, and during the fall months at IMN, with a modeled mean of 19.21 ± 7.49 gC/m2/month compared to observation mean of 11.9 ± 4.45 gC/m2/month. Our results underscore the importance of representing the impact of soil drainage conditions on the thawing of permafrost soils, particularly poorly drained soils, which will drive the magnitude of carbon released at sites across the high-latitude tundra. These findings can help improve predictions of net carbon releases from thawing permafrost, ultimately contributing to a better understanding of the impact of Arctic warming on the global climate system.

Changes in endangered hornbill populations over space and time and potential ecological impacts in peninsular Thailand

Hornbills are particularly important seed dispersers in tropical Asian forests, but most of the species in the region are declining. In addition, long-term data on the extent of the declines and how forest degradation impacts hornbills remain mostly unquantified. Here, we used multi-covariate distance sampling to estimate the densities of hornbills in 2021–2022 in Hala-Bala Wildlife Sanctuary and Budo Su-Ngai Padi National Park protected areas in southern Thailand. These two sites are particularly useful for comparison due to differences in protection levels, with Bala being relatively less disturbed than Budo Mountain and because Bala was surveyed 20 years prior (2001–2002). Fig tree watches were also conducted in 2021–2022 to assess the potential impact of forest disturbance on hornbill visitation rates. Results indicated significant differences in hornbill densities between the two sites. The mean density of the Rhinoceros (Buceros rhinoceros) and Wreathed Hornbill (Rhyticeros undulatus) was 3.2 and 5.1 times higher in Bala than in Budo, while the mean density of the Great Hornbill (Buceros bicornis) was 2.2 times higher in Budo than in Bala. The density of the Helmeted Hornbill (Rhinoplax vigil) was notably lower than other hornbill species. There were also significant changes over the past 20 years in large hornbill densities, with Great Hornbill and Wreathed Hornbill significantly increasing, while the Helmeted Hornbill declined more than 90 %. Also, the probability of hornbills visiting fruiting Ficus trees was higher in the less-disturbed Bala than the Budo Mountain, making hornbills more reliable visitors in the less-disturbed site. We demonstrate the applicability of the multi-covariate distance sampling approach to estimate densities of rare hornbills, the negative impacts of habitat degradation on hornbills and the ecological role they play as seed dispersers. Additional surveys are needed throughout tropical Asia to establish further sites for long-term monitoring, especially in the Sunda region, where the Helmeted Hornbill is under extreme threat.

Aquatic photosynthetic carbon pump driven by periodic temperature variations affects dissolved inorganic carbon and hydrochemical characteristics in a groundwater-fed reservoir

Under the influence of periodic temperature variations, biogeochemical cycling in water bodies is markedly affected by the periodic thermal stratification processes in subtropical reservoirs or lakes. In current studies, there is insufficient research on the influence and mechanism of dissolved inorganic carbon (DIC) distribution in karst carbon-rich groundwater-fed reservoirs under the coupled effects of thermal structure stratification and the biological carbon pump (BCP) effect. To address this issue, the Dalongdong (DLD) reservoir in the subtropical region of southern China was chosen as the site for long-term monitoring and research on relevant physicochemical parameters of water, DIC, and its stable carbon isotope (δ13CDIC), CO2 emission flux, as well as the reservoir's thermal stratification index. The results show that: (1) the DLD reservoir is a typical warm monomictic reservoir, which exhibits regular variations of mixing period-stratification period-mixing period on a yearly scale due to thermal structure changes; (2) DIC was consumed by aquatic photosynthetic organisms in the epilimnion during the stratification period, leading to a decrease in DIC concentration, partial pressure of CO2 (pCO2) and CO2 emission flux, and an increase in stable carbon isotope (δ13CDIC). During the mixing period, the trend was reversed; (3) During the thermal stratification, aquatic photosynthesis and water temperature were the primary factors controlling DIC variations in both the epilimnion and thermocline. Regarding the hypolimnion, calcite dissolution, organic matter decomposition, and water temperature were the dominant controlling factors. These results indicate that although carbon-rich karst groundwater provides a plentiful supply of DIC in the DLD reservoir, its availability is still influenced by variations in the reservoir's thermal structure and the metabolic processes of aquatic photosynthetic organisms. Therefore, to better estimate the regional carbon budget in a reservoir or lake, future studies should especially consider the combined effects of BCP and thermal structure variations on carbon variations.

Hydroclimatic non-stationarity drives stream hydrochemistry dynamics through controls on catchment connectivity and water ages

We used data from 17 years of routine stream flow sampling to characterise hydrochemical dynamics in the Girnock Burn, an internationally important long-term catchment monitoring site. We combined hydrochemical time series analysis with hydrological modelling to understand short- and long-term dynamics in relation to dominant runoff processes. Isotopic tracer data employed within the model enabled flux tracking of water as it transited the catchment, facilitating water age estimates. The stream drains an upland 31 km2 catchment with complex topography and variable geology, which influences soil distributions; peaty soils dominate valley bottoms which receive drainage from more permeable podzolic soils on steeper slopes. Short-term hydrochemical dynamics largely reflect the relative dominance of hydrological sources: summer low flows are dominated by alkaline groundwater high in weathering products (Ca2+, Mg2+, SiO2) whilst high flows generated by overland flow from peaty soils are more acidic, DOC enriched, and dominated by atmospheric solutes (Na+, Cl-, SO42-). Baseflows are dominated by older groundwater (>∼3years) in contrast to storm runoff dominated by younger (<∼0.5 years), near-surface, waters. Usual seasonal distributions of stream flows, with high flows in winter and summer low flows, result in strong seasonality in most solutes. However, coupled effects of hydroclimatic variability and catchment heterogeneity dictates marked scatter in flow-concentration relationships for most determinands. A long-term decreasing trend was evident for SO42-concentrations, reflecting continuing effects of reductions in atmospheric deposition of pollutants from coal burning. Reductions in large storm event frequency post-2016 and protracted periods of low flows in the droughts of 2018 and 2022 have resulted in the catchment becoming dominated by low flows, derived from older groundwater with more alkaline chemistry for longer periods. Changing climatic conditions and stream flow responses seem likely to continue to cause changes in stream water quality and associated ecosystem services of the Girnock Burn and similar upland catchments.

Ground-Based NDVI Network: Early Validation Practice with Sentinel-2 in South Korea.

As satellite launching increases worldwide, uncertainty quantification for satellite data becomes essential. Misunderstanding satellite data uncertainties can lead to misinterpretations of natural phenomena, emphasizing the importance of validation. In this study, we established a tower-based network equipped with multispectral sensors, SD-500 and SD-600, to validate the satellite-derived NDVI product. Multispectral sensors were installed at eight long-term ecological monitoring sites managed by NIFoS. High correlations were observed between both multispectral sensors and a hyperspectral sensor, with correlations of 0.76 and 0.92, respectively, indicating that the calibration between SD-500 and SD-600 was unnecessary. High correlations, 0.8 to 0.96, between the tower-based NDVI with Sentinel-2 NDVI, were observed at most sites, while lower correlations at Anmyeon-do, Jeju, and Wando highlighting challenges in evergreen forests, likely due to shadows in complex canopy structures. In future research, we aim to analyze the uncertainties of surface reflectance in evergreen forests and develop a biome-specific validation protocol starting from site selection. Especially, the integration of tower, drone, and satellite data is expected to provide insights into the effect of complex forest structures on different spatial scales. This study could offer insights for CAS500-4 and other satellite validations, thereby enhancing our understanding of diverse ecological conditions.

Aboveground Biomass Estimation and Time Series Analyses in Mongolian Grasslands Utilizing PlanetScope Imagery

Mongolia, situated in central Asia and bordered by Russia to the north and China to the south, experiences a semi-arid climate across most of its territory. Grasslands are pivotal in Mongolia’s agricultural sustainability and food security, facing rapid changes in the last two decades that underscore the ongoing need for innovative approaches to assess vegetation conditions. This study aims to evaluate grassland biomass measurement and prediction through the analysis of high-resolution satellite data. By conducting a time series assessment of grazing-induced changes in vegetation dynamics at the long-term monitoring sites of the Botanic Garden and Research Institute, Mongolian Academy of Sciences, we seek to refine our understanding. The investigation covers biomass estimation across various Mongolian grassland landscapes, encompassing desert, steppe, and mountain regions. Spanning the grassland growing season from May 2020 to October 2023, the research leveraged diverse ground data types, including surface reflectance measurements, geographic coordinates for satellite data correction, and aboveground dry biomass. These components were instrumental in developing a biomass estimation model reliant on establishing correlations between the satellite-derived Normalized Difference Vegetation Index and biomass. The predicted biomass facilitated the time series map analysis and dynamic analysis. The PlanetScope surface reflectance correlates strongly at 0.97 with field measurements, indicating robust relations. Biomass and the Normalized Difference Vegetation Index show correlations of 0.82 for dry grassland, 0.80 for mountain grassland, and 0.65 for desert grassland, with a combined correlation coefficient of 0.62, revealing distinct characteristics across these grasslands. Time series dynamic analysis reveals rising biomass differences between grazed and ungrazed areas, suggesting potential grassland degradation. Variations in the slope coefficient of biomass differences among grassland types indicate differing degradation patterns, emphasizing the need for effective grazing management practices to sustain and conserve Mongolian grasslands. This highlights the potential of remote sensing in monitoring and managing grassland ecosystems.

Higher absorption enhancement of black carbon in summer shown by 2-year measurements at the high-altitude mountain site of Pic du Midi Observatory in the French Pyrenees

Abstract. Black-carbon-containing particles strongly absorb light, causing substantial radiative heating of the atmosphere. The climate-relevant properties of black carbon (BC) are poorly constrained in high-altitude mountain regions, where many complex interactions between BC, radiation, clouds and snow have important climate implications. This study presents 2-year measurements of BC microphysical and optical properties at the Pic du Midi (PDM) research station, a high-altitude observatory located at 2877 m above sea level in the French Pyrenees. Among the long-term monitoring sites in the world, PDM is subject to limited influence from the planetary boundary layer (PBL), making it a suitable site for characterizing the BC in the free troposphere (FT). The classification of the dominant aerosol type using aerosol spectral optical properties indicates that BC is the predominant aerosol absorption component at PDM and controls the variation in single-scattering albedo (SSA) throughout the 2 years. Single-particle soot photometer (SP2) measurements of refractory BC (rBC) show a mean mass concentration (MrBC) of 35 ng m−3 and a relatively constant rBC core mass-equivalent diameter of about 180 nm, which are typical values for remote mountain sites. Combining the MrBC with in situ absorption measurements, a rBC mass absorption cross-section (MACrBC) of 9.2 ± 3.7 m2 g−1 at λ=880 nm has been obtained, which corresponds to an absorption enhancement (Eabs) of ∼2.2 compared to that of bare rBC particles with equal rBC core size distribution. A significant reduction in the ΔMrBC/ΔCO ratio when precipitation occurred along the air mass transport suggests wet removal of rBC. However we found that the wet removal process did not affect the rBC size, resulting in unchanged Eabs. We observed a large seasonal contrast in rBC properties with higher MrBC and Eabs in summer than in winter. In winter a high diurnal variability in MrBC (Eabs) with higher (lower) values in the middle of the day was linked to the injection of rBC originating from the PBL. On the contrary, in summer, MrBC showed no diurnal variation despite more frequent PBL conditions, implying that MrBC fluctuations are rather dominated by regional and long-range transport in the FT. Combining the ΔMrBC/ΔCO ratio with air mass transport analysis, we observed additional sources from biomass burning in summer leading to an increase in MrBC and Eabs. The diurnal pattern of Eabs in summer was opposite to that observed in winter with maximum values of ∼2.9 observed at midday. We suggest that this daily variation may result from a photochemical process driving the rBC mixing state rather than a change in BC emission sources. Such direct 2-year observations of BC properties provide quantitative constraints for both regional and global climate models and have the potential to close the gap between model-predicted and observed effects of BC on the regional radiation budget and climate. The results demonstrate the complex influence of BC emission sources, transport pathways, atmospheric dynamics and chemical reactivity in driving the light absorption of BC.

Mapping Soil Carbon Dynamics and Permafrost Thaw Response to Abrupt Climate Change in the Usa River Basin, Russia

A computer-based map is considered a crucial foundational resource for conducting comprehensive carbon budget studies in northern latitudes. Detailed soil maps were created for the intensive study sites located in the forest-tundra and tundra regions using QuickBird 61 cm panchromatic and 2.4 m multispectral resolution satellite images, alongside a database containing morphological descriptions and analytical data from 153 soil profiles, long-term permafrost monitoring sites, and meteorological records. The results of GIS-analysis indicate that approximately 60% of all infrastructure is situated in areas with a "high risk" of permafrost degradation. These areas, defined as zones with isolated to discontinuous permafrost coverage ranging from 3% to 90% and ground temperatures ranging from 0 to -2 °C, are expected to experience significant thawing within the next few decades to a century. Long-term measurements taken at CALM (Circumpolar Active Layer Monitoring) sites in the region have shown a continuous increase in thaw depths, resulting in a lowering of the permafrost table. This trend poses significant challenges for permafrost engineering and highlights the need for long-term investments in arctic infrastructure that will yield returns over time. The database has been utilized to assess soil organic carbon stocks.

Environmental variables influence patterns of mammal co-occurrence following introduced predator control.

Co-occurring species often overlap in their use of resources and can interact in complex ways. However, shifts in environmental conditions or resource availability can lead to changes in patterns of species co-occurrence, which may be exacerbated by global escalation of human disturbances to ecosystems, including conservation-directed interventions. We investigated the relative abundance and co-occurrence of two naturally sympatric mammal species following two forms of environmental disturbance: wildfire and introduced predator control. Using 14 years of abundance data from repeat surveys at long-term monitoring sites in south-eastern Australia, we examined the association between a marsupial, the common brushtail possum Trichosurus vulpecula, and a co-occurring native rodent, the bush rat Rattus fuscipes. We asked: In a fox-controlled environment, are the abundances of common brushtail possums and bush rats affected by environmental disturbance and each other's presence? Using Bayesian regression models, we tested hypotheses that the abundance of each species would vary with changes in environmental and disturbance variables, and that the negative association between bush rats and common brushtail possums was stronger than the association between bush rats and disturbance. Our analyses revealed that bush rat abundance varied greatly in relation to environmental and disturbance variables, whereas common brushtail possums showed relatively limited variation in response to the same variables. There was a negative association between common brushtail possums and bush rats, but this association was weaker than the initial decline and subsequent recovery of bush rats in response to wildfires. Using co-occurrence analysis, we can infer negative relationships in abundance between co-occurring species, but to understand the impacts of such associations, and plan appropriate conservation measures, we require more information on interactions between the species and environmental variables. Co-occurrence can be a powerful and novel method to diagnose threats to communities and understand changes in ecosystem dynamics.