Vegetation Types Research Articles

Determinants of rhizospheric organic carbon fractions and accumulation in four different vegetations of coastal saline-alkali soils

Rhizosphere processes are key pathways through which plants influence the carbon cycling of diverse ecosystems and are closely associated with vegetation types. However, the environmental responses of rhizospheric soil organic carbon (SOC) mediated by the interaction between rhizospheric effect and vegetation type remain uncertain, severely limiting our assessment of the carbon sequestration potential of different coastal vegetation. Here, we identified the core factors driving changes in various soil carbon fractions in the rhizosphere of four coastal vegetation types by testing the contents of the reactive, dissolved, particulate, mineral-associated, heavy and light fractions of SOC and their relationships with physicochemical properties and enzyme activities. It was found that the rhizosphere effect significantly influenced SOC, with rhizospheric SOC contents varying significantly among vegetation types, ranging from 2.12 to 9.04 g/kg. Besides, rhizospheric soil pH was found to contribute significantly to SOC fractions (except for light organic carbon) and exert significant inhibitory effects on SOC, reactive organic carbon, mineral-associated organic carbon and heavy organic carbon. Despite the different responses of various SOC fractions to physicochemical properties and enzyme activities, soil available phosphorus and alkaline phosphatase activity emerged as core environmental factors influencing rhizospheric SOC accumulation across different coastal vegetation types. This study presents a promising framework for understanding the determinants of SOC fractions in rhizospheric soil, and their accumulation in the vegetation of coastal saline-alkali soils. In addition to alkalinity, phosphorus acquisition capacity can be a key predictor of coastal SOC fractions and their accumulation.

Sex differences in positional behavior of chimpanzees (Pan troglodytes schweinfurthii) living in the dry and open habitat of Issa Valley, Tanzania.

Many early fossil hominins are associated with savanna-mosaic paleohabitats, and high sexual dimorphism that may reflect differences in positional behavior between sexes. However, reconstructions of hominin behavior and the selective pressures they faced in an open habitat are limited by a lack of studies of extant apes living in contemporary, analogous habitats. Here, we describe adult chimpanzee positional behavior in the savanna-mosaic habitat of the Issa Valley, Tanzania, to test whether Issa chimpanzees show larger sex-differences in positional behavior than their forest-dwelling counterparts. We quantified and compared adult locomotor and postural behavior across sexes (6 females, 7 males) in the riparian forest (closed) and miombo woodland (open) vegetation types at Issa Valley (13,743 focal observations). We then compared our results to published data of chimpanzee communities living in more forested habitats. Issa females and males both spent less time arboreally in open vegetation and showed similar locomotor and postural behavior on the same substrates, notably using a high level of suspensory locomotion when arboreal. Females were, however, more arboreal than males during locomotor behavior, as well as compared with females from other communities. Issa males behaved similarly to males from other communities. Results suggest that open habitats do not elicit less arboreal behaviors in either sex, and may even select for suspensory locomotion to effectively navigate an open canopy. An open habitat may, however, increase sex differences in positional behavior by driving female arboreality. We suggest this is because of higher energetic demands and predator pressures associated with open vegetation, which are likely exaggerated for reproducing females. These results have implications for the interpretation of how sexual dimorphism may influence reconstructions of hominin positional behavior.

Strong decline in grasshopper abundance over 20 years without major land-use changes: Is soil drying one of the drivers?

Strong declines in insect numbers have been described for different taxa and regions. These observations are of great concern such that broad scientific and public attention has been raised. Among other urgencies, the need for long-term insect data has been identified. Here, we present data on grasshopper (Caelifera) abundances recorded between 1992 and 2011 at over 600 sites in north-western Switzerland. While vegetation type, often semi-natural grasslands, had remained largely constant, total grasshopper abundance declined by around 50 % (while many other taxa showed much less decline). Numbers in July remained relatively stable until about 2003 but then declined similar to the declines seen in August–October already before. Greatest losses were observed for drier habitats and steeper slopes, suggesting that soil drying might be an important factor for the decline. Second, more nutrient-rich habitats suffered greater losses; possible reasons for this include small-scale vegetation changes in these habitats e.g. due to atmospheric nitrogen deposition, or isolation of sites. Other than abundance, species richness decreased much less, illustrating that important ecological changes may be strongly underestimated when only species lists are available. The strong declines at our sites, which often are in an agri-environmental scheme, is alarming. Apart from being yet another call to fight climate change, our results also point to the urgent need to reduce atmospheric nitrogen deposition and to continue extensive farming, but also to adapt it in preparation of expected effects of climate change, with the aim to favour a divers, ecologically robust insect community.

Vegetation community recovery on restored bottomland hardwood forests in northeast Indiana, USA.

Vegetation communities in restored bottomland hardwood forests in northeast Indiana were studied 6-21 years after restoration to assess progress toward restoration objectives. The study focused on four sites that were restored to compensate for resource injuries after contaminant releases. The restored sites were compared with four reference-site conditions, including crops (prerestoration condition), old field communities representing a no-management alternative, locally sampled second-growth mature forests, and forest community types described by the US National Vegetation Classification (USNVC), which represent ideal or defining conditions of recognized vegetation communities. Fixed-area plots provided data on field-sampled environmental variables, vegetation, soil, and hydrological conditions for crops, old fields, restored areas, and mature forests. The USNVC database provided quantitative data for three historically and geographically relevant reference forest community types for comparison with the sampled communities. Results of nonmetric multidimensional scaling based on species cover revealed clear gradients relating to site age and canopy development. Along those gradients, restored areas demonstrated increasing similarity to mature forest reference communities in terms of floristic composition. Specifically, the floristic quality of restored areas was significantly greater than that of crops and old fields. Furthermore, soil health measurements of physical, chemical, and hydrological conditions indicated significant improvements in restored site soils compared with prerestoration conditions represented by cropland soils. Descriptions and data from the USNVC provided ecological context for restoration target conditions and facilitated the assessment of restoration recovery along a trajectory from starting conditions to those target conditions. Descriptions by USNVC also helped identify deviations from the intended restoration objectives (e.g., invasive species recruitment) and potential adaptive management actions to return sites to their intended trajectories. Integr Environ Assess Manag 2024;20:1917-1938. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Influence of vegetation phenological carryover effects on plant autumn phenology under climate change

Vegetation phenological carryover effects refer to the influence of previous phenological events on the current or subsequent ones. These effects can modulate the responses of autumn phenology to climate change, but the magnitude and duration of this effect remain poorly understood. Therefore, we employed multiple remote sensing datasets from 1982 to 2018 in the Northern Hemisphere (> 30°N) and partial correlation to investigate the influence of the carryover effect and environmental factors on the end of the growing season (EOS) over time. The importance of the variables in the projection score was used to quantify their relative importance. Our results showed that the previous year's EOS had a robust positive impact on the EOS for 40.02 % of the study area during 1982–2015, which was mainly located in the northern 50°N region. In contrast, the start of the growing season (SOS) was the main contributor to the EOS during 2001–2018, mainly at 40°N-50°N and in northern Russia. The carryover effect persisted into the subsequent year, but its strength and positive impacts varied dramatically in the next year. Concurrently, the mean correlation coefficient between climate factors and EOS rose from 0.20 to 0.22. Notably, the correlation coefficient for frost day frequency increased significantly (P < 0.05) from 0.15 to 0.36, with its influence area expanding from 10.29 % to 11.85 % of the study area. Compared with climate factors, the phenological carryover effect was the dominant driver of the EOS for each vegetation type, accounting for 72.8 % and 44.23 % of the total pixels during 1982–2015 and 2001–2018, respectively. Our study reveals a cascade of ecological consequences that extend beyond the initial occurrence and emphasizes the interconnectedness of growth stages in the plant life cycle, providing valuable insights into the adaptability and vulnerability of plant communities.

Potential Distribution and Carbon Sequestration of Rhizophora mangle L. in El Vizcaíno Biosphere Reserve, Baja California Sur, Mexico

Mangroves are a type of vegetation distributed in warm areas of the planet. Despite their importance, this flora is seriously threatened by both human activities and climate change. One of the main benefits provided by mangroves is carbon capture and storage, which is key for climate change mitigation. The main objective of this study was to identify the potential distribution and carbon sequestration potential of Rhizophora mangle L. in El Vizcaíno Biosphere Reserve. Potential distribution models were obtained for Baja California Sur, Mexico, using the MaxLike algorithm. For each projection, we used bioclimatic variables from the WorldClim project for current and future conditions (2050 and 2070), two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) and three General Circulation Models (ACCESS-CM2, EC-Earth3-Veg and MPI-ESM1-2-HR). The potential distribution models were developed within the perimeter of El Vizcaíno Biosphere Reserve as a case study to establish the potential for carbon sequestration under different climate change scenarios. Our results show a possible future carbon sequestration from 10,177,174 Mg of CO2 and up to 14,022,367 Mg of CO2 for the ACCESS-CM2 SSP5-8.5 to 2070 and MPI-ESM1-2-HR SSP2-4.5 to 2070 projections, respectively. Mangrove species such as Rhizophora mangle can be an important part of climate change mitigation and adaptation.

Soil Physicochemical Properties and Carbon Storage Reserve Distribution Characteristics of Plantation Restoration in a Coal Mining Area

The Bulianta Coal Mine is among the problematic coal mining areas in China that is still creating environmental damage, especially associated with soil destruction. Therefore, a scientific investigation was conducted to establish a scientific basis for evaluating the impact of planted forest on soil physical and chemical properties, as well as the ecological benefits following 15 years of vegetation restoration in the area. The soil physicochemical characteristics and distribution of organic carbon storage in the 0–80 cm layer soils of Pinus sylvestris forests, Prunus sibirica forests, and Hippophae rhamnoides forests restored after 5, 10, and 15 years were investigated. The immersion method was used to determine soil porosity and density followed by the determination of soil indicators, and a statistical ANOVA test was applied to examine the differential effects of different vegetation types and restoration years on soil properties. The results clearly demonstrated the following: (1) The recovery of vegetation was achieved after a period of 15 years, with the average bulk density of the 0–80 cm soil layer as follows: P. sylvestris forest (1.513 g·cm−3) &gt; P. sibirica forest (1.272 g·cm−3) &gt; H. rhamnoides forest (1.224 g·cm−3), and the differences among different forest types were statistically significant (p &lt; 0.05). (2) In planted forests, soil nutrients were predominantly concentrated in the 0–20 cm layer, while soil carbon storage exhibited a decline with an increasing soil depth. (3) The soil carbon storage across the three forest types was as follows: P. sylvestris forest (45.42 t·hm−2) &gt; P. sibirica forest (44.56 t·hm−2) &gt; H. rhamnoides forest (41.87 t·hm−2). In summary, during the ecological vegetation restoration process in the Bulianta Core Mine, both P. sylvestris forest and P. sibirica forest exhibit superior carbon storage capacities compared to H. rhamnoides forest, as well as more effective soil improvement outcomes.

Mapping perceived sentiments in university campuses with varied landscape metrics and climatic conditions

A sustainable university campus should accommodate students to experience positive emotions, which can be evoked by sustainable landscape with green and blue spaces (GBS). This effect is location-dependent because local vegetative type is climate-determinative, but evidence is not sufficient for sentiments of people experiencing campus landscapes. Forty-seven university campuses were selected along a latitudinal gradient in mainland China, and 100 subjects were chosen per campus (50 indoor and 50 outdoor). Photos of the subjects’ faces on Sina Weibo were collected. Facial expressions were assigned happy, sad, and neutral scores (n = 4,334). The average temperature (AveT) and blue space area (BlueA) showed negative relationships with latitude, thereby generating neutral emotion scores for subjects at indoor and outdoor locations. The ratio of green space area to host campus was the only landscape metric that depressed the presentation of happiness and enhanced sadness levels. Large water bodies should be built on campuses to induce calmness, and a high ratio of green spaces should be avoided. Mapping results show that campuses in eastern regions (Beijing and Liaoning) tend to elicit positive sentiments more frequently.

Optimizing key parameters (biological-control factor) of soil erosion simulation models at a regional scale– The case of Jiangxi Province, China

Unveiling the spatial information of actual soil erosion is a prerequisite for subsequent soil erosion research and is critical for soil and water conservation as well as ecological resource protection. However, the existing regional-scale soil erosion simulation models often ignore the vertical structure of vegetation, particularly near-surface vegetation information, which leads to discrepancies with the real-world conditions. This study aims to optimize the biological-control factor (B factor) of the Chinese Soil Loss Equation (CSLE) model to improve simulation accuracy. The Global Ecosystem Dynamics Investigation (GEDI) can provide accurate layered vegetation data. Thus, this study focuses on the forest of Jiangxi Province, simulating the understory vegetation structure by vegetation type using a combination of GEDI data and sampled data. By considering the soil and water conservation benefits of different vegetation layers, we developed a B factor optimization method to simulate soil erosion in forests at a regional scale. Compared to previous methods, the optimized B factor mean value for Jiangxi Province’s forested areas increased from 0.0034 to 0.0096. The estimated soil erosion changed from 38 t·km-2a-1 (with 86.6 % of forests exhibiting no soil erosion) to 166.7t·km-2a-1 (with 28.2 % of forests exhibiting no soil erosion). Our findings indicate that the optimized assessment results are more consistent with the actual situation. The optimization method is a good attempt at regional-scale B factor simulation and can provide a more accurate depiction of the spatial information of soil erosion in forest at the regional scale. This study can lay a solid foundation for future regional-scale soil erosion assessments and offer valuable data support and methodological references for the regional-scale dynamic monitoring of soil and water loss, as well as research in soil and water conservation.

Observed response of microwave land surface emissivity to antecedent rainfall in Hainan Island

ABSTRACT Microwave emissivity is an important parameter for over-land retrieval of atmospheric variables such as water vapour, rainfall, and snowfall. However, it remains unclear for the dynamic response of multi-frequency microwave emissivity to prior rainfall over heterogeneous land surfaces. This study combined multi-frequency Microwave Land Surface Emissivity (MLSE) under all-weather conditions with hourly in-situ rainfall to investigate the response of MLSE to rainfall over different vegetation types in Hainan Island in China. Specifically, we explored the change of MLSE at 6.925, 10.65, 18.7, 23.8 and 36.5 Ghz to rainfall intensity in four rainfall cases, followed with statistical characteristics of MLSE to rainfall and dry duration (DD) across different vegetation types during 2003–2010. We found that the magnitude of decline in MLSE (0.004–0.06) is dependent on the rainfall intensity and duration, and the reduction caused by short-lasting heavy rain (daily rainfall >100 mm) was 2–6 times higher than that by light long-lasting rain (daily rainfall <80 mm). Among different microwave frequencies, the MLSE at 23.8 Ghz was most reduced by rainfall, while less reduction was found at low microwave frequencies such as at 6.925 and 10.65 Ghz. More importantly, the change of MLSE after rainfall was significantly different among vegetation types. Over woody savannas and forested lands, MLSE slightly decreased (about 0.004) in the first two hours of DD, whereas a rapid increase was observed in the first hour of DD over areas dominated with woody savanna, grassland, and cropland. These findings improve our understanding of the multi-frequency MLSE in response to rainfall over complex land surfaces, and benefit the microwave retrieval of rainfall over land.

Study on Shear Strength of Soil–Root Systems of Different Vegetation Types

The root systems of vegetation significantly contribute to enhancing slope stability. The shear strength of soil–root systems is a crucial parameter for assessing slope stability. This study focuses on six types of vegetation in the Yellow River Basin of China (woodland: Populus przewalskii and Broussonetia papyrifera; shrubland: Periploca sepium and Ziziphus jujuba; grassland: Artemisia hedinii and Setaria viridis), employing in situ shear tests and the Wu–Waldron model (Wu model) to investigate the shear strength of soil–root systems. The results show that the shear stress–displacement curves for P. przewalskii, B. papyrifera, and Z. jujuba are higher and steeper, with clear inflection points. The tensile strength of the roots from the six vegetation types decreases as the root diameter increases. According to the Wu model, the additional root cohesion is ranked as follows: A. hedinii &gt; B. papyrifera &gt; P. przewalskii &gt; Z. jujuba &gt; P. sepium &gt; S. viridis. Based on the in situ shear tests, the shear strength increments are ranked as follows: Z. jujuba &gt; B. papyrifera &gt; P. przewalskii &gt; A. hedinii &gt; P. sepium &gt; S. viridis. Overall, the additional root cohesion obtained by the Wu model in each soil layer is greater than the shear strength increment measured from the in situ shear tests. In the 0–30 cm soil layers, the soil–root systems of Z. jujuba, B. papyrifera, P. przewalskii, and A. hedinii exhibit a better shear strength, whereas P. sepium and S. viridis perform poorly. A principal component analysis reveals that the shear strength of the soil–root systems of different vegetation types is primarily influenced by the soil moisture content and root mass density. Z. jujuba, B. papyrifera, P. przewalskii, and A. hedinii are recommended for ecological restoration projects in the Yellow River Basin of China.

Characteristics and Typical Influential Factors of Wildfire Caused by High-Voltage Transmission Line Breakage Faults

In order to investigate the characteristics and typical influential factors of wildfires caused by accidental faults in high-voltage transmission lines, a bespoke platform was constructed for the purpose of conducting simulation experiments. Discharge and ignition experiments were conducted on a variety of substrates, including kidney fern fragments, cedar needle fragments, poplar sawdust, and eucalyptus leaf fragments, to investigate the effects of different gaps on the initiation and propagation of wildfires. The results demonstrate that the discharge-inducing ignition stages can be succinctly summarized as “two phases and two points” (the discharge induction period, the gap breakdown point, the arc induction period and the fault removal point) when a suitable gap is maintained between the simulated falling lines and the vegetation surface. In the event of direct contact, the removal of the fault is not possible. The potential for ignition of the aforementioned vegetation types by the discharge is as follows: cedar needles &gt; eucalyptus leaf fragments ≈ poplar sawdust &gt; kidney fern fragments. As the water content increases, eucalyptus leaf fragments can still be ignited, and the breakdown voltages required for discharge-inducing ignitions gradually decrease. In the case of different forest ground vegetation types, when ignited by the discharge between the falling lines and the vegetation under conditions of proper gap and moisture content, the resulting ignition and sustained flames will promote the formation of streamer channels and further aggravate the discharges and burning processes, potentially leading to the ignition of a wildfire.

Vegetation classification in the Neotropics – Novel insights from Latin America and the Caribbean

Our editorial introduces a Special Collection of scientific articles on current vegetation research in the most biodiverse of all biogeographic realms, the Neotropics. It contains nine scientific contributions dedicated to vegetation data, description and classification. Four research papers provide new vegetation classifications of important Neotropical biomes, namely the Arid Chaco in Argentina, Mexican temperate forests, and Andean wetlands in the Argentine Puna and southern Peru. Furthermore, one study provides a novel bioclimatic-vegetation classification approach applied to Mexican vegetation, while another proposes a new synthesis of the South American terrestrial biomes as geocomplexes. Finally, three vegetation databases are presented in the Special Collection: ArgVeg – Database of Central Argentina (GIVD ID: SA-AR-002), CACTUS – Vegetation database of the Dutch Caribbean Islands (GIVD ID: SA-00-004) and VegAndes: the vegetation database for the Latin American highlands (GIVD ID: SA-00-005). The Special Collection provides fundamental data and tools to better understand the diversity and complexity of Neotropical vegetation. Abbreviations: GIVD = Global Index of Vegetation-Plot Databases, IAVS = International Association for Vegetation Science, IAVS-LACS = IAVS Regional Section for the Latin America and the Caribbean, VCS = Vegetation Classification and Survey

Improving AGB estimations by integrating tree height and crown radius from multisource remote sensing.

Precise estimation of forest above ground biomass (AGB) is essential for assessing its ecological functions and determining forest carbon stocks. It is difficult to directly obtain diameter at breast height (DBH) based on remote sensing imagery. Therefore, it is crucial to accurately estimate the AGB with features extracted directly from RS. This paper demonstrates the feasibility of estimating AGB from crown radius (R) and tree height (H) features extracted from multi-source RS data. Accurate information on tree height (H), crown radius (R), and diameter at breast height (DBH) can be obtained through point clouds generated by airborne laser scanning (ALS) and terrestrial laser scanning (TLS), respectively. Nine allometric growth equations were used to fit coniferous forests (Larix principis-rupprechtii) and broadleaf forests (Fraxinus chinensis and Sophora japonica). The fitting performance of models constructed using only "H" or "R" was compared with that of models constructed using both combined. The results showed that the quadratic polynomial model constructed with "H+R" fitted the AGB estimation better in each vegetation type, especially in the scenario of mixed tall and short coniferous forests, in which the R2 and RMSE were 0.9282 and 25.30 kg (rRMSE 17.31%), respectively. Therefore, using high-resolution data to extract crown radius and tree height can achieve high-precision, global-scale estimation of forest above ground biomass.

Diversity and composition of Coreidae (Hemiptera: Heteroptera) in a seasonal forest of central Mexico

ABSTRACT The diversity of the Coreidae family in the tropical deciduous forest (TDF) of Coaxitlán, Tlaquiltenango, Morelos, Mexico, is presented. From the collection carried out during an annual cycle, 34 species, 18 genera, 8 tribes, and 2 subfamilies were recorded. The sample coverage was 99% and according to the Chao 1 richness estimator, 90% of the species in the study area were represented. The greatest richness, abundance, and diversity occur during the months of greatest rainfall. The faunal similarities between months show groupings in species composition corresponding to the TDF’s seasonality. The community structure reflects a high diversity, integrated by a high proportion (>60%) of species with a low abundance. The data show that the diversity of Coreidae in the TDF is high, but the environmental heterogeneity of this type of vegetation suggests that the species composition could still be different in other sites, which shows the need to continue documenting it.

Extraction of deterioration and analysis of vegetation impact effects on the south palace wall of Weiyang Palace

Weiyang Palace, the royal palace of the Western Han Dynasty, is a part of the Silk Roads: the Routes Network of Chang’an-Tianshan Corridor on the World Heritage list. The south palace wall of Weiyang Palace is a well-preserved earthen heritage site within the palace, but it is undergoing continuous deterioration due to the influence of vegetation and external environmental factors. This study pioneers the integration of high-resolution three-dimensional LiDAR scanning with multi-source data analysis, including unprecedented on-site botanical surveys, to explore the subtle effects of different vegetation types on the structural integrity of the south palace wall. Through contour line analysis and facade grid analysis, we extracted the deterioration locations of typical sections of the earthen heritage sites. And we classified the overlying vegetation types on the wall using an object-oriented classification algorithm. Our findings reveal a complex interaction between vegetation and earthen structures: paper mulberry exhibits protective qualities against erosion, while Ziziphus jujuba significantly exacerbates structural vulnerabilities. The methodologies applied in this study for extracting deterioration at earthen heritage sites and integrating multi-source spatial data can serve as a technical application model for monitoring and analyzing the driving forces of earthen heritage sites along the entire Silk Road network, thereby better guiding the conservation of earthen heritage sites.

Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai–Tibetan Plateau Based on Hyperspectral Data

Grassland degradation poses a significant challenge to achieving the Sustainable Development Goals (SDGs) on the Qinghai–Tibetan Plateau (QTP). Effective monitoring of grassland degradation is essential for ecological restoration. Hyperspectral technology offers efficient and accurate identification of degradation. However, the influence of observation time, data analysis methods and classification techniques on the accuracy of identifying alpine grasslands remains unclear. In this study, the spectral reflectance of degraded alpine meadow, alpine meadow, alpine shrub and Tibetan barley was measured from May to September 2023 using a ground spectrometer in the northeastern QTP. First-order derivatives (FDR) and continuum removal were applied to the spectra, and characteristic parameters and vegetation indices were calculated. Support vector machine (SVM), random forest (RF), artificial neural network (ANN) and decision tree (DT) were then used to compare the classification accuracy between different months, transformation methods and characteristic parameters. The results showed that the spectral reflectance peaked in July, with significant differences in the near infrared (NIR) bands between alpine meadow and degraded alpine meadow. Alpine shrub and Tibetan barley showed greater differences in reflectance compared to other vegetation types, especially in the NIR bands. Data transformations improved reflectance and absorption characteristics in the NIR and visible bands. Indices such as DVI, RVI and NDGI effectively differentiated vegetation types. Optimal accuracy for the identification of degraded alpine meadow in July was achieved using FDR transformations and ANN or SVM for classification. This study provides methodological insights for monitoring grassland degradation on the QTP.

Holocene palaeoecological changes in a transitional climate zone of western-central Mexico: The pollen and non-pollen palynomorphs record

The Alberca de Tacámbaro (AT) is located at a transitional zone between tropical and temperate climates at the core of the North American Monsoon area. This location features a mosaic vegetation comprising pine-oak forests and tropical dry forests. Currently there is no information regarding the dynamics or evolution during the Holocene of these vegetation types. The palynological record of the last 9400 years BP preserved in the lacustrine sequence of the AT was used to document changes in the composition of terrestrial and aquatic communities, evenness, and rate of change. Pinus and Quercus forests dominated the terrestrial palynological record, but mesophytic forests were also recorded throughout the sequence. Four tropical dry forest taxa assemblage expansions were identified at 9200 to 8420 yr BP; 5900 to 5230 yr BP; 3100 to 2800 yr BP; and 2300 to 2000 yr BP. These phases correlated with times of reduced North American Monsoon intensity, suggesting that these communities thrived during drought periods. Variations in non-pollen palynomorphs were synchronic with the lithostratigraphic, geochemical data as well as with the terrestrial changes. During the Meghalayan, compositional shifts in the vegetation and increases in the herbaceous elements indicated human impact, while aquatic taxa, suggested eutrophic and warmer conditions in the lake. By examining the history of this vegetation mosaic, the data on temporal vegetation dynamics during the Holocene offered clues about the response to ongoing global warming and how climate change will likely shape plant communities in western-central Mexico.

Sensitivity and Uncertainty Analysis of the GeeSEBAL Model Using High-Resolution Remote-Sensing Data and Global Flux Site Data

Actual evapotranspiration (ETa) is an important component of the surface water cycle. The geeSEBAL model is increasingly being used to estimate ETa using high-resolution remote-sensing data (Landsat 4/5/7/8). However, due to surface heterogeneity, there is significant uncertainty. By optimizing the quantile values of the reverse-modelling automatic calibration algorithm (CIMEC) endpoint-component selection algorithm under extreme conditions through 212 global flux sites, we obtained the optimized quantile values of 11 vegetation types of cold- and hot-pixel endpoint components (Ts and NDVI). Based on the observation data of the global FLUXNET tower, the sensitivity of 20 parameters in the improved geeSEBAL model was determined through Sobol’s sensitivity analysis. Among them, the parameters dT and SAVI,hot were confirmed as the most sensitive parameters of the algorithm. Subsequently, we used the differential evolution Markov chain (DE-MC) method to analyse the uncertainty of the parameters in the geeSEBAL model used the posterior distribution of the parameters to modify the sensitive parameter values or ranges in the improved geeSEBAL model and to simulate the daily ETa. The results indicate that by analysing the end element components of the geeSEBAL model (Ts and NDVI), quantile numerical optimization and parameter optimization can be performed. Compared with the original algorithm, the improved geeSEBAL model has significantly improved simulation performance, as shown by higher R2 values, higher NSE values, smaller bias values, and lower RMSE values. The most suitable values of the predefined parameter Zoh were determined, and the reanalysis of meteorological data inputs (relative humidity (RH), temperature (T), wind speed (WS), and net radiation (Rn)) was also found to be an important source of uncertainty for the accurate estimation of ETa. This study indicates that optimizing the quantiles and key parameters of the model end component has certain potential for further improving the accuracy of the geeSEBAL model based on high-resolution remote-sensing data in estimating the ETa for various vegetation types.

Microarthropod responses to fire: vegetation cover modulates impacts on Collembola and Acari assemblages in Mediterranean area

BackgroundIn the Mediterranean region, fire is a recurring disturbance that impacts both surface and underground organisms. While the effects on plants and surface animals are well-studied, the consequences for soil microarthropods are often overlooked. This research addresses the microarthropod responses to fire by comparing post-fire Collembola and Acari assemblages in soils with different vegetation covers. Three years post-fire, surface soils were sampled within the Vesuvius National Park (Southern Italy) from a total of 24 sites, comprising 6 sites each under holm oak (HO), pine (P), black locust (BL), and herbaceous (H) vegetation. Within each vegetation cover, sites were further categorized into three unburnt (NB) and three burnt (B) sites for comprehensive analysis. Collembola and Acari were extracted, identified at the family and suborder level, respectively and analyzed for density and taxa richness.ResultsThe results highlighted that fire alone did not impact microarthropod communities, but its effects varied according to the vegetation covers. Microarthropod abundance declined in burnt soils under P, and increased in burnt soils under BL. Furthermore, eu-edaphic organisms (Onychiuridae, Oribatida), typical of stable environments, decreased in soils under P, and increased in soils under black locust.ConclusionsFire impact on microarthropod communities changed according to the vegetation covers, highlighting the importance of considering vegetation type when managing post-fire landscapes. The rapid recovery of microarthropod communities under some vegetation covers suggests that fire may not universally impair soil biodiversity in Mediterranean environments.