Variety Of Vegetation Types Research Articles

ANALISIS VEGETASI PADA BLOK LINDUNG TAMAN HUTAN RAYA (TAHURA) NIPA-NIPA DI KELURAHAN PUNGGALOBA KECAMATAN KENDARI BARAT

The purpose of this study was to determine the level of diversity of vegetation types. This research was carried out in the Nipa-Nipa Forest Park, Protection Block, Punggaloba Village, West Kendari District, from September to October 2021. The sampling intensity used was 1% of an area of 96.07 Ha, so that a sample area of 0.96 Ha was obtained with The number of plots is 24 plots, which are placed using the plotted transect method. The results showed that the level of species diversity (H') for the tree level was 1.388 (medium), the pole level was 1.348 (medium), the sapling level was 0.96 (low) and the seedling level was 1.306 (medium).Keywords : Protection Block, Diversity, Nipa-Nipa Forest Park

The United States National Vegetation Classification: Creating A Common Language To Classify The Nation’s Vegetation

In every introductory biology class, students learn the classification system used to catalogue plants, animals, fungi, and other organisms. In order of increasing specificity, the major levels of classification are: domain, kingdom, phylum, class, order, family, genus, and species. Global adoption of this system allows us to create an inventory of the world’s species diversity. For instance, we classify the Redwood tree of the US Pacific coast as the species sempervirens in the genus Sequoia, or Sequoia sempervirens. Until recently, however, there was no comparable standard available in the United States to classify the nation’s diverse types of vegetation – the various combinations of species, growth forms, and ecological factors that occur in certain regions. Instead, many land-management groups created their own classifications, hindering communication and collaboration. To address this issue, stakeholders established the United States National Vegetation Classification (USNVC).

Driving Forces of the Changes in Vegetation Phenology in the Qinghai–Tibet Plateau

Phenological change is an emerging hot topic in ecology and climate change research. Existing phenological studies in the Qinghai–Tibet Plateau (QTP) have focused on overall changes, while ignoring the different characteristics of changes in different regions. Here, we use the Global Inventory Modeling and Mapping Studies (GIMMS3g) normalized difference vegetation index (NDVI) dataset as a basis to discuss the temporal and spatial changes in vegetation phenology in the Qinghai–Tibet Plateau from 1982 to 2015. We also analyze the response mechanisms of pre-season climate factor and vegetation phenology and reveal the driving forces of the changes in vegetation phenology. The results show that: (1) the start of the growing season (SOS) and the length of the growing season (LOS) in the QTP fluctuate greatly year by year; (2) in the study area, the change in pre-season precipitation significantly affects the SOS in the northeast (p < 0.05), while, the delay in the end of the growing season (EOS) in the northeast is determined by pre-season air temperature and precipitation; (3) pre-season precipitation in April or May is the main driving force of the SOS of different vegetation, while air temperature and precipitation in the pre-season jointly affect the EOS of different vegetation. The differences in and the diversity of vegetation types together lead to complex changes in vegetation phenology across different regions within the QTP. Therefore, addressing the characteristics and impacts of changes in vegetation phenology across different regions plays an important role in ecological protection in this region.

Landscape structure and local variables affect plant community diversity and structure in a Brazilian agricultural landscape

AbstractThe biodiversity in agricultural landscapes depends on land‐use types, natural elements, and farming intensity. The Brazilian Cerrado is a biodiversity hotspot, however, the native vegetation loss rates have increased in the last years, leading several plant species to extinction risk. Here, we analyze the effects of local (soil fertility and litter amount) and landscape variables (patch shape, habitat amount, compositional heterogeneity, matrix dominance and connectivity) on alpha species richness and diversity, and basal area of different Cerrado vegetation types (savanna, forested savanna, and forest) using linear models and Akaike information criterion. We calculated landscape metrics at different spatial scales for 49 sampling sites in intensive farming landscapes. Woody plant diversity and richness were positively related to soil fertility and landscape compositional heterogeneity at 1500 m spatial scale. Plant richness was negatively related to the patch shape of remnants at 1000 m spatial scale. The effects of litter amount to explain the basal area varied between vegetation types. We found a positive effect in savanna and forested savanna and a negative effect in forest areas. Our findings suggest that the increase of monocultures lead to a decline on plant diversity in the studied landscapes. Also, local variables and the diversity of vegetation types need to be considered to design restoration actions in Cerrado. Sustainable intensification and biodiversity‐friendly production systems may be alternatives to increase compositional heterogeneity, thus favoring plant diversity in Cerrado farming landscapes.Abstract in Portuguese is available with online material.

Tropical Forests Classification Based on Weighted Separation Index from Multi-Temporal Sentinel-2 Images in Hainan Island

Tropical forests play a vital role in biodiversity conservation and the maintenance of sustainability. Although different time-series spatial resolution satellite images have provided opportunities for tropical forests classification, the complexity and diversity of vegetation types still pose challenges, especially for distinguishing different vegetation types. In this paper, we proposed a Spectro-Temporal Feature Selection (STFS) method based on the Weighted Separation Index (WSI) using multi-temporal Sentinel-2 data for mapping tropical forests in Jianfengling area, Hainan Province. The results showed that the tropical forests were classified with an overall accuracy of 93% and an F1 measure of 0.92 with multi-temporal Sentinel-2 data. As our results also revealed, the WSI based STFS method could be efficient in tropical forests classification by using a fewer feature subset compared with Variable Selection Using Random Forest (14 features and all 40 features, respectively) to achieve the same accuracy. The analysis also showed it was not advisable to only pursue a higher WSI value while ignoring the heterogeneity and diversity of features. This study demonstrated that the WSI can provide a new feature selection method for multi-temporal remote sensing image classification.

Peningkatan Kapasitas Meliponikultur dengan Pengayaan Pakan Lebah Madu di Kelurahan Kahu Kecamatan Bontocani Kabupaten Bone

The purpose of this community service program is to provide knowledge about the importance of forests, woody forage plants and enrichment of feed types around meliponiculture farmer groups. The methods used in this activity as part of the mentoring are pre-tests, lectures, video screenings, discussions about knowledge of forest bee hunting, trigona beekeeping and the importance of forests and bee feed. The next activity was the distribution of flowering tree seedlings and visits to the meliponiculture location for farmer groups. The result of this community service activity is that the community in Kahu Village can develop knowledge about the material presented by seeing the enthusiasm and appreciation of the participants or members of the farmer groups who participated in the many questions during the discussion. Receipt of plant and tree seeds that are distributed immediately to the plant and group reception during visits to their meliponiculture area. Awareness of planting various types of vegetation and maintaining forests is an important factor for the stability of colony strength and can even increase the beekeeping productivity of all types of bees in Kahu Village, Bontocani District and its surroundings. Assistance from various parties is needed in order to increase the productivity of honey bee cultivation in Kahu Village, Bontocani District.

Whole genome duplication increases ecological niche breadth of the perennial herb Urtica dioica

Environmental niche modelling and associated species distribution models often ignore intraspecific ecological differentiation linked with ploidal differentiation, i.e. the occurrence of several cytotypes of the same species. Here we tested the hypotheses that (i) the tetraploid (4x) cytotype is characterized by a broader ecological niche than the diploid (2x), and (ii) niche differentiation at the regional scale can serve as a proxy measure for differentiation at a smaller landscape scale in Urtica dioica, a perennial herbaceous plant with two prevailing cytotypes (2x and 4x). We focused on southern Moravia (Czech Republic), an area with a high diversity of vegetation types and the occurrence of both diploid and tetraploid cytotypes of U. dioica. To explore the geographical distribution, ecological preferences and habitat affinities of the diploid and tetraploid plants, we collected individuals at two different spatial scales: regional (~1200 km2) and landscape (9.1 km2). We used flow cytometry to determine the ploidy level of all the plants collected and determined the distribution of the different cytotypes both in geographical and ecological space. We also compared the habitat affinities of the diploid and tetraploid plants. Analyses of ploidy revealed 93 diploids and 325 tetraploids (regional scale: 42 diploids, 85 tetraploids; landscape scale: 51 diploids and 240 tetraploids). Diploid plants occurred only in the wetter parts of the landscape and this pattern was very similar at both scales. In contrast, tetraploids occurred along the whole moisture gradient at both scales. Diploids and tetraploids differed also in their habitat affinities. While diploids occurred relatively more frequently in alluvial and wet forests, managed broadleaved forests, alluvial and wet meadows, and wetlands and riverbanks, tetraploids preferred oak and oak-hornbeam forests, ravine forests, actively managed meadows, human settlements and vineyards. Our data clearly show an ecological niche differentiation between diploid and tetraploid cytotypes of Urtica dioica. While tetraploids have a broad ecological tolerance and consequently a wide geographical distribution, diploids occur only in a narrow range of ecological conditions and their distribution is restricted to areas with a shallow water table in the bottoms of valleys. Thus, ploidal differentiation, confirmed for many plant species, should be included in environmental niche modelling and species distribution models.

Keanekaragaman Jenis Vegetasi di Kawasan Resort Kembang Kuning Kabupaten Lombok Timur

The purpose of this study was to determine the diversity of vegetation types in the Kembang Kuning Resort Area, Jeruk Manis Village, Sikur District, East Lombok Regency, based on the density of vegetation types. The type of research used is descriptive quantitative. The population in this study were all plant species in the Kembang Kuning Resort Area. Purposive sampling method was used to determine the location and grouping based on growth criteria to obtain data on species richness. A total of 3 research plot locations were determined, namely: plot A (top), plot B (middle), and plot C (bottom). The analysis was carried out descriptively quantitatively based on the Shannon-Wiener (H') species diversity index. The results obtained for plot A area are 19 species with an H' value of 1.117 in the medium category, for plot B area there are 17 species with an H' value of 2.001 in the medium category, and for plot C area 16 species are found with an H' value of 7,045 in the high category. The conclusions obtained are the tree-level diversity index in all areas of plot A, plot B, and plot C of 3.38 in the high category.

Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying Karst wetland vegetation communities using ultra-high spatial resolution UAV data

Karst wetlands have the characteristics of small scale and poor stability. At present, the wetland is being severely damaged and its area is seriously degraded, and the accurate identification of vegetation communities is very important for the rapid assessment and management of karst wetland. In this paper, Huixian Karst National Wetland Park, located in Guilin city, China, was taken as the study area, the digital orthophoto map (DOM) and digital surface model (DSM) of UAV images were selected as the data sources, and the vegetation communities of karst wetland were classified by using the object-based Random Forest (RF)-Decision Tree (DT) algorithm and SegNet algorithm. When the object-based RF algorithm and SegNet algorithm were used for coarse classification of karst vegetation, the parameters (mtry, ntree) of the object-based RF algorithm were optimized, and the data dimensionality reduction and RFE variable selection algorithm were used for selecting feature, and the single-class SegNet model was integrated based on the soft voting method to improve the applicability of vegetation classification in karst wetlands. In the classification of vegetation communities in karst wetlands, the optimized object-based RF-DT algorithm were used to extract the vegetation communities in the Areas A, B, and C. The statistical analysis of the importance of the feature variables (spectral features, texture features, geometric features, and position features) of various types of land cover in the three areas was carried out to explore the optimal classification variables of various types of vegetation. The results showed that: (1) the optimized object-based RF algorithm performed better than the SegNet algorithm in classifying karst vegetation at 95% confidence level during the coarse classification. The average accuracy of wetland vegetation was improved by 1.06–13.58%; (2) the object-based RF-DT algorithm had high classification ability for the karst wetland vegetation community, with overall accuracy and kappa coefficient above 0.85; and that (3) although geometric features accounted for the largest proportion (52.2%) in the classification of bermudagrass, water hyacinth, lotus, linden and other vegetation, texture features accounted for the highest proportion of 56.3% in the classification of vegetation whose importance was more than 90.

Synergy of multi-temporal polarimetric SAR and optical image satellite for mapping of marsh vegetation using object-based random forest algorithm

The accurate classification of marsh vegetation is an important prerequisite for wetland management and protection. In this study, the Honghe National Nature Reserve was used as the research area. The VV and VH polarized backscattering coefficients of Sentinel-1B, the polarimetric decomposition parameters of Sentinel-1B, and Sentinel-2A multi-spectral images from June and September were selected to construct 18 multi-dimensional data sets. A highly correlated variable elimination algorithm, a recursive feature elimination variable selection algorithm (RFE-RF), and an optimized random forest algorithm (RF) were used to construct a marsh vegetation identification model. In this study, we searched for an RF model to achieve the accurate classification of marsh vegetation and find the best feature for identifying various types of vegetation. Additionally, the applicability of different optimized RF models to the task of the identification of wetland vegetation and the stability of the identification of marsh vegetation using different classification models were quantitatively analyzed. The results show the following: (1) RFE-RF variable selection and RF parameter optimization can reduce the data dimensionality, improve the accuracy and stability of the wetland vegetation classification model, and achieve a training accuracy of up to 85.39%. (2) The RF model integrating multi-spectral data, backscattering coefficients, and polarimetric decomposition parameters for June and September can obtain the highest overall accuracy (91.16%), and the model has the strongest applicability. (3) The importance of multi-spectral variables in wetland vegetation classification is higher than that of backscattering coefficients and polarimetric decomposition parameters. The visible bands and vegetation index are the most important variables, while the cross-polarized backscattering coefficient (Mean_VH), polarimetric decomposition eigenvalue (Mean_l1, Mean_l2), and calculated eigenvalues of the matrix (Mean_lambda) are the backscattering coefficient features and polarimetric decomposition parameters with the highest contributions. (4) The modified normalized difference water index in June (MNDWI_ Jun), blue band in September (Mean_B_Sep), location feature pixel coordinates (Y_Max_Pxl), and ratio vegetation index in September (RVI_Sep) have the highest contribution to the identification and classification of deep-water marsh vegetation, shallow-water marsh vegetation, forest, and shrubs, respectively. (5) The identification of forest is the strongest, and the classification accuracy for shrubs and deep-water marsh vegetation is greatly affected by the combination of time phase and data sources.

Response of net reduction rate in vegetation carbon uptake to climate change across a unique gradient zone on the Tibetan Plateau

The Tibetan Plateau (TP) has a variety of vegetation types that range from alpine tundra to tropic evergreen forest, which play an important role in the global carbon (C) cycle and is extremely vulnerable to climate change. The vegetation C uptake is crucial to the ecosystem C sequestration. Moreover, net reduction in vegetation C uptake (NRVCU) will strongly affect the C balance of terrestrial ecosystem. Until now, there is limited knowledge on the recovery process of vegetation net C uptake and the spatial-temporal patterns of NRVCU after the disturbance that caused by climate change and human activities. Here, we used the MODIS-derived net primary production to characterize the spatial-temporal patterns of NRVCU. We further explored the influence factors of the net reduction rate in vegetation C uptake (NRRVCU) and recovery processes of vegetation net C uptake across a unique gradient zone on the TP. Results showed that the total net reduction amount of vegetation C uptake gradually decreased from 2000 to 2015 on the TP (Slope = −0.002, P < 0.05). Specifically, an increasing gradient zone of multi-year average of net reduction rate in vegetation carbon uptake (MYANRRVCU) from east to west was observed. In addition, we found that the recovery of vegetation net C uptake after the disturbance caused by climate change and anthropogenic disturbance in the gradient zone were primarily dominated by precipitation and temperature. The findings revealed that the effects of climate change on MYANRRVCU and vegetation net C uptake recovery differed significantly across geographical space and vegetation types. Our results highlight that the biogeographic characteristics of the TP should be considered for combating future climate change.

Areas of endemism of Lauraceae: new insights on the biogeographic regionalization of the Espinhaço Range, Brazil.

Using Lauraceae as a study case, we aimed in this article to: (i) delimit areas of endemism in the Espinhaço Range, Brazil; (ii) compare these areas of endemism with those previously delimited, as well as with the centres of endemism; (iii) evaluate the association between areas of endemism and vegetation types; and (iv) classify the areas of endemism according to the International Code of Area Nomenclature (ICAN). Based on a recent survey of 99 species from the Espinhaço Range, our dataset consisted of 34 endemic species belonging to nine genera. Following previous studies, we performed parsimony analysis of endemicity (PAE) using a grid square size of 0.5° × 0.5°. We delimited four areas of endemism of Lauraceae: (i) Antônio dos Santos, (ii) Conceição do Mato Dentro, (iii) Itambé do Mato Dentro, and (iv) Rio de Contas; and confirmed six previously delimited areas of endemism: (i) Southern MG, (ii) Southern Mountains Complex, (iii) Conceição do Mato Dentro, (iv) Diamantina Plateau, (v) Serra do Cabral, and (vi) Chapada Diamantina. The areas of endemism Conceição do Mato Dentro, Serra do Cabral, Diamantina, and Serra do Cipó were classified as subdistricts in the Diamantina Plateau district of the Southern Espinhaço province. We summarized and mapped all areas of endemism corresponding to the provinces, districts, and subdistricts that cover the Espinhaço Range. Areas of endemism and centres of endemism are contrasted. Finally, we highlight that the biogeographic studies along this mountain range should embrace higher taxa with representative species in different types of vegetation in order to enrich the majority of the endemism studies mainly concentrated on the campo rupestre. Unusual distribution patterns, diversity of vegetation types, and the presence of restricted species and monophyletic groups open up opportunities to carry out integrative studies concerning the biogeographic regionalization of the ER at multiple spatio-temporal scales.

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

AbstractAimsUnderstanding fine‐grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine‐grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups).LocationPalaearctic biogeographic realm.MethodsWe used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class.ResultsPatterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi‐natural) grasslands and natural grasslands are the richest vegetation type. The open‐access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats.ConclusionsThe GrassPlot Diversity Benchmarks provide high‐quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation‐plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology.

Identifying Policy-relevant Indicators for Assessing Landscape Vegetation Patterns to Inform Planning and Management on Multiple-use Public Lands

Understanding the structure and composition of landscapes can empower agencies to effectively manage public lands for multiple uses while sustaining land health. Many landscape metrics exist, but they are not often used in public land decision-making. Our objectives were to (1) develop and (2) apply a process for identifying a core set of indicators that public land managers can use to understand landscape-level resource patterns on and around public lands. We first developed a process for identifying indicators that are grounded in policy, feasible to quantify using existing data and resources, and useful for managers. We surveyed landscape monitoring efforts by other agencies, gathered science and agency input on monitoring goals, and quantified the prevalence of potential indicators in agency land health standards to identify five landscape indicators: amount, distribution, patch size, structural connectivity, and diversity of vegetation types. We then conducted pilot applications in four bureau of land management (BLM) field offices in Arizona, California, and Colorado to refine procedures for quantifying the indicators and assess the utility of the indicators for managers. Results highlighted the dominance of upland and the limited extent of riparian/wetland vegetation communities, moderate connectivity of priority vegetation patches, and lower diversity of native vegetation types on BLM compared to non-BLM lands. Agency staff can use the indicators to inform the development of quantitative resource management objectives in land use plans, evaluate progress in meeting those objectives, quantify potential impacts of proposed actions, and as a foundation for an all-lands approach to landscape-level management across public lands.

Vegetation Reconstruction From Siberia and the Tibetan Plateau Using Modern Analogue Technique–Comparing Sedimentary (Ancient) DNA and Pollen Data

To reconstruct past vegetation from pollen or, more recently, lake sedimentary DNA (sedDNA) data is a common goal in palaeoecology. To overcome the bias of a researcher’s subjective assessment and to assign past assemblages to modern vegetation types quantitatively, the modern analogue technique (MAT) is often used for vegetation reconstruction. However, a rigorous comparison of MAT-derived pollen-based and sedDNA-based vegetation reconstruction is lacking. Here, we assess the dissimilarity between modern taxa assemblages from lake surface-sediments and fossil taxa assemblages from four lake sediment cores from the south-eastern Tibetan Plateau and northern Siberia using receiver operating characteristic (ROC) curves, ordination methods, and Procrustes analyses. Modern sedDNA samples from 190 lakes and pollen samples from 136 lakes were collected from a variety of vegetation types. Our results show that more modern analogues are found with sedDNA than pollen when applying similarly derived thresholds. In particular, there are few modern pollen analogues for open vegetation such as alpine or arctic tundra, limiting the ability of treeline shifts to be clearly reconstructed. In contrast, the shifts in the main vegetation communities are well captured by sedimentary ancient DNA (sedaDNA). For example, pronounced shifts from late-glacial alpine meadow/steppe to early–mid-Holocene coniferous forests to late Holocene Tibetan shrubland vegetation types are reconstructed for Lake Naleng on the south-eastern Tibetan Plateau. Procrustes and PROTEST analyses reveal that intertaxa relationships inferred from modern sedaDNA datasets align with past relationships generally, while intertaxa relationships derived from modern pollen spectra are mostly significantly different from fossil pollen relationships. Overall, we conclude that a quantitative sedaDNA-based vegetation reconstruction using MAT is more reliable than a pollen-based reconstruction, probably because of the more straightforward taphonomy that can relate sedDNA assemblages to the vegetation surrounding the lake.

A framework for measuring the effects of disturbance in restoration projects

Ecological resilience is widely acknowledged as a vital attribute of successful ecosystem restoration, with potential for restoration practice to contribute to this goal. Hence, defining common metrics of resilience to naturally occurring disturbances is essential for restoration planning, efforts, and monitoring. Here, we reviewed how plant community ecologists have measured resilience of restoration projects to disturbances and propose a framework to guide measurement of restoration projects to disturbance. We found 22 studies that investigated the impact of disturbances on restoration projects, from three continents and for three disturbance types. Over half of the studies were from Australia, with the dataset biased toward fire responses of restored, or partially restored, forest ecosystems. Native plant species richness, cover, and density were common response variables. Studies varied in restoration context, design, response variables, and statistical approaches, limiting generalizations. Nonetheless we have identified several response variables that offer potential as lagging indicators (e.g. species richness) and leading indicators (e.g. recruitment) of resilience in diverse vegetation types exposed to a variety of disturbance regimes. We suggest a third set of variables, proxy measures of resilience (e.g. functional redundancy), to complement lagging and leading indicators. We conclude with a framework to guide decisions about when to use each of the three types of measures to assess resilience of restoration projects to disturbance, providing some clarity to decision‐making despite the uncertainty of changing disturbance regimes. Lastly, we invite researchers to understand the impact of disturbance on the resilience of restoration projects, rather than assume resilience.

APPLICATION OF A MODEL INSTALLATION FOR EVALUATION OF EFFICIENCY OF PHYTOREMEDIATION METHODS OF SURFACE WASTEWATER TREATMENT

The article provides an assessment of the phytoremediation method as a promising direction of passive protection of soils and water bodies from pollution by surface waste waters, especially those contaminated as a result of fire extinguishing processes. Particular attention is paid to the danger of contamination with anionic surfactants. Natural methods of surface runoff purification have been analyzed, the efficiency of wastewater treatment in troughs with the use of industrial waste has been investigated. The prospects of using environmentally friendly plastic waste (PET, polypropylene, etc.) for the creation of artificial bioengineering structures are noted. An experimental model installation was developed and installed for testing and evaluating the effectiveness of various methods and methods of phytoremediation. Based on the results of experimental studies, a method is proposed for assessing the effectiveness of using various types of filtering nozzles in troughs for purifying wastewater and various types of vegetation in a research model installation. The effectiveness of phytoremediation to reduce the harmful effect of anionic surfactants on the composition of wastewater after the use of foaming agents in extinguishing fires has been analyzed. An analysis of the use of a filter nozzle from defibrated PET containers showed an increase in the efficiency of phytoremediation processes.

Mapping Early Pleistocene environments and the availability of plant food as a potential driver of early Homo presence in the Guadix-Baza Basin (Spain)

The Guadix-Baza Basin, in SE Spain, harbors hominin fossils and lithic artifacts dated to ca. 1.4–1.3 Ma, representing the first hominin habitat in the Iberian Peninsula and possibly in Western Europe. Recent palynological studies have described a high diversity of plant taxa and biomes existing in the basin at the time of hominin presence. However, the relationship between these hominins and their environment has not been fully explored. Two novel methodologies are developed. The first method maps the distribution of the Early Pleistocene vegetation units based on paleobotanical and paleogeographic data. The second method assesses the availability of edible plant parts using a combination of Early Pleistocene and modern taxa lists. The resulting vegetation maps reveal a great diversity of vegetation types. During dry (glacial) periods, the vegetation of the basin was represented mostly by steppes, with the appearance of forested vegetation only in the mountainous regions. During humid (interglacial) periods, Mediterranean woodlands represented the dominant vegetation, accompanied by deciduous and conifer forests in the areas of higher altitude. The lake system present in the basin also allowed for the presence of marshland vegetation. The assessment of the availability of edible plant parts reveals that early Homo could have found a high number of resources in marshland and riparian environments throughout the year. Mediterranean woodlands and deciduous forests also provided numerous edible plant parts. During dry periods, the availability of plant resources decreased heavily, but the prevalence of marshland and riparian vegetation and of forested vegetation in the areas of higher altitude could have sustained hominin communities during harsher climatic periods. However, the disappearance of the lake system and an increase of aridity after the Mid-Pleistocene Transition and during the Middle Pleistocene probably led to an impoverishment of plant resources available to early Homo in the Guadix-Baza Basin.

Are Climate Factors Driving the Contemporary Wildfire Occurrence in China?

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

Behavioral state resource selection in invasive wild pigs in the Southeastern United States

Elucidating correlations between wild pig (Sus scrofa) behavior and landscape attributes can aid in the advancement of management strategies for controlling populations. Using GPS data from 49 wild pigs in the southeastern U.S., we used hidden Markov models to define movement path characteristics and assign behaviors (e.g., resting, foraging, travelling). We then explored the connection between these behaviors and resource selection for both sexes between two distinct seasons based on forage availability (i.e., low forage, high forage). Females demonstrated a crepuscular activity pattern in the high-forage season and a variable pattern in the low-forage season, while males exhibited nocturnal activity patterns across both seasons. Wild pigs selected for bottomland hardwoods and dense canopy cover in all behavioral states in both seasons. Males selected for diversity in vegetation types while foraging in the low-forage season compared to the high-forage season and demonstrated an increased use of linear anthropogenic features across seasons while traveling. Wild pigs can establish populations and home ranges in an array of landscapes, but our results demonstrate male and female pigs exhibit clear differences in movement behavior and there are key resources associated with common behaviors that can be targeted to improve the efficiency of management programs.