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The idea that tropical forest and savanna are alternative states is crucial to how we manage these biomes and predict their future under global change. Large-scale empirical evidence for alternative stable states is limited, however, and comes mostly from the multimodal distribution of structural aspects of vegetation. These approaches have been criticized, as structure alone cannot separate out wetter savannas from drier forests for example, and there are also technical challenges to mapping vegetation structure in unbiased ways. Here, we develop an alternative approach to delimit the climatic envelope of the two biomes in Africa using tree species lists gathered for a large number of forest and savanna sites distributed across the continent. Our analyses confirm extensive climatic overlap of forest and savanna, supporting the alternative stable states hypothesis for Africa, and this result is corroborated by paleoecological evidence. Further, we find the two biomes to have highly divergent tree species compositions and to represent alternative compositional states. This allowed us to classify tree species as forest vs. savanna specialists, with some generalist species that span both biomes. In conjunction with georeferenced herbarium records, we mapped the forest and savanna distributions across Africa and quantified their environmental limits, which are primarily related to precipitation and seasonality, with a secondary contribution of fire. These results are important for the ongoing efforts to restore African ecosystems, which depend on accurate biome maps to set appropriate targets for the restored states but also provide empirical evidence for broad-scale bistability.

Freshwater ecosystems are under great threat from humans, among which habitat heterogeneity is the most obvious, being one of the important reasons for the decline of fish diversity. This phenomenon is particularly prominent in the Wujiang River, where the continuous rapids of the mainstream have been divided into 12 mutually isolated sections by 11 cascade hydropower reservoirs. Based on the fact that conventional survey methods are more harmful to the ecological environment, the efficient and noninvasive environmental DNA metabarcoding (eDNA) approach was used in this study to conduct an aquatic ecological survey of the 12 river sections of the mainstream of the Wujiang River. A total of 2299 operational taxonomic units (OTUs) were obtained, corresponding to 97 species, including four nationally protected fish species and 12 alien species. The results indicate that the fish community structure of the Wujiang River mainstream, which was originally dominated by rheophilic fish species, has been changed. And there are differences in fish species diversity and species composition among the reservoir areas of the mainstream of the Wujiang River. The fish species in the area have gradually declined under the influence of anthropogenic factors such as terraced hydropower and overfishing. The fish populations consequently have demonstrated a tendency to be species miniaturized, and the indigenous fish are severely threatened. In addition, the fish composition monitored by the eDNA approach was found to be close to the fish composition of historical information on the Wujiang River, indicating that eDNA approach may be used as a complementary tool to conventional methods in this basin. Freshwater ecosystems are under great threat from humans, among which habitat heterogeneity is the most obvious, being one of the important reasons for the decline of fish diversity. This phenomenon is particularly prominent in the Wujiang River, where the continuous rapids of the mainstream have been divided into 12 mutually isolated segments by 11 cascade hydropower reservoirs. Based on the fact that traditional survey methods are more harmful to the ecological environment, the efficient and noninvasive environmental DNA metabarcoding (eDNA) technology was used in this study to conduct an aquatic ecological survey of the 12 river sections of the mainstream of the Wujiang River.

Question: Anthropogenic climate change is altering temperature and precipitation in grasslands worldwide. As grasslands are primarily water-limited, these changes in climate will likely have dramatic impacts on ecosystem function and community structure, yet the magnitude of change and the types of species favoured may differ among ecosystems or even among local communities within ecosystems. How much might plant community responses to altered precipitation vary at two sites within one grassland region? Location: Semi-arid and sub-humid natural grasslands in the US Great Plains. Methods: At two sites we used rainfall shelters and irrigation to create irrigation, drought and control treatments. We measured changes in species composition, richness, Shannon's diversity, evenness and cover by plant functional groups across 4 yr (2008-2011). Results: The semi-arid grassland community was relatively insensitive to precipitation manipulations, and in the few cases where there was a significant relationship between treatment precipitation and the response variable, the slope of the relationship was weak. In contrast, the sub-humid grassland community was very sensitive to changes in treatment precipitation throughout the experiment, and responded more strongly, and negatively, to drought compared to irrigation. Conclusions: The differing sensitivity of the dominant species to altered precipitation amount appears to largely determine the overall differences in community response at these sites. The variable responses we observed within a single grassland region highlight the challenge of forecasting community impacts of climate change.

For monitoring protected forest landscapes over time it is essential to follow changes in tree species composition and forest dynamics. Data driven remote sensing methods provide valuable options if terrestrial approaches for forest inventories and monitoring activities cannot be applied efficiently due to restrictions or the size of the study area. We demonstrate how species can be detected at a single tree level utilizing a Random Forest (RF) model using the Black Forest National Park as an example of a Central European forest landscape with complex relief. The classes were European silver fir (Abies alba, AA), Norway spruce (Picea abies, PA), Scots pine (Pinus sylvestris, PS), European larch (Larix decidua including Larix kampferii, LD), Douglas fir (Pseudotsuga menziesii, PM), deciduous broadleaved species (DB) and standing dead trees (snags, WD). Based on a multi-temporal (leaf-on and leaf-off phenophase) and multi-spectral mosaic (R-G-B-NIR) with 10 cm spatial resolution, digital elevation models (DTM, DSM, CHM) with 40 cm spatial resolution and a LiDAR dataset with 25 pulses per m2, 126 variables were derived and used to train the RF algorithm with 1130 individual trees. The main objective was to determine a subset of meaningful variables for the RF model classification on four heterogeneous test sites. Using feature selection techniques, mainly passive optical variables from the leaf-off phenophase were considered due to their ability to differentiate between conifers and the two broader classes. An examination of the two phenological phases (using the difference of the respective NDVIs) is important to clearly distinguish deciduous trees from other classes including snags (WD). We also found that the variables of the first derivation of NIR and the tree metrics play a crucial role in discriminating PA und PS. With this unique set of variables some classes can be differentiated more reliably, especially LD and DB but also AA, PA and WD, whereas difficulties exist in identifying PM and PS. Overall, the non-parametric object-based approach has proved to be highly suitable for accurately detecting (OA: 89.5%) of the analyzed classes. Finally, the successful classification of complex 265 km2 study area substantiates our findings.

The realization that anthropogenic nitrogen (N) deposition is causing significant environmental change in many ecosystems has led to lower emissions of reactive N and deposition rates in many regions. However, the impacts of N deposition on terrestrial ecosystems can be long lasting, with significant inertia in the return of the biota and biogeochemical processes to baseline levels. To better understand patterns of recovery and the factors that may contribute to slow or no responses following declines in N deposition, we followed plant species composition, microbial abundance, N cycling rates, soil pH, and pools of NO₃⁻ and extractable cations in an impacted alpine ecosystem following cessation of 12-yr experiment increasing N deposition rates by 0, 20, 40, and 60 kg N·ha−1·yr−1. Simulated N deposition had resulted in a tripling in the cover of the nitrophilic species Carex rupestris, while the dominant sedge Kobresia myosuroides had decreased by more than half at the highest N input level. In addition, nitrification rates were elevated, soil extractable magnesium (Mg2+) and pH decreased, and aluminum (Al3+) and manganese (Mn2+) were elevated at the highest N treatment inputs. Over the nine years following cessation of N additions to the impacted plots, only the cover of the nitrophilic C. rupestris showed any recovery to prior levels. Abundances of both bacteria and fungi were lower with N addition in both treatment and recovery plots. Rates of nitrification and pools of NO₃⁻ remained elevated in the recovery plots, likely contributing to the lack of biotic response to the cessation of N inputs. In addition, nutrient base cations (Ca2+ and Mg2+) and soil pH remained depressed, and the toxic metal cations (Al3+ and Mn2+) remained elevated in recovery plots, also potentially influencing biotic recovery. These results emphasize the importance of considering long-term environmental impacts of N deposition associated with legacy effects, such as elevated N cycling and losses of base cations, in determining environmental standards such as the metrics used for critical loads.

Aims Long-duration drought can alter ecosystem plant species composition with subsequent effects on carbon cycling. We conducted a rainfall manipulation field experiment to address the question: how does drought-induced vegetation change, specifically shrub encroachment into grasslands, regulate impacts of subsequent drought on soil CO 2 efflux (R s ) and its components (autotrophic and heterotrophic, R a and R h )? Methods We conducted a two-year experiment in Inner Mongolia plateau, China, using constructed steppe communities including graminoids, shrubs and their mixture (graminoid + shrub) to test the effects of extreme-duration drought (60-yr return time) on R s , R h and R a. Results Our results indicated that extreme-duration drought reduced net primary production, with subsequent effects on R s , R h and R a in all three vegetation communities. There was a larger relative decline in R a (35–54%) than R s (30–37%) and R h (28–35%). Interestingly, we found R s in graminoids is higher than in shrubs under extreme drought. Meanwhile, R h declines were largest in the shrub community. Although R a and R h both decreased rapidly during drought treatment, R h recovered quickly after the drought, while R a did not, limiting the R s recovery. Conclusions This study suggests that plant species composition regulates several aspects of soil CO 2 efflux response to climate extremes. This regulation may be limited by above- and below-ground net primary production depending on soil water availability . The results of this experiment address a critical knowledge gap in the relationship between soil respiration and plant species composition. With shrub encroachment into grasslands, total soil respiration is reduced and can partly offset the effect of reduction in productivity under drought stress.

Plateau pika (Ochotona curzoniae, hereafter pika) is considered to exert a profound impact on vegetation species diversity of alpine grasslands. Great efforts have been made at mound or quadrat scales; nevertheless, there is still controversy about the effect of pika. It is vital to monitor vegetation species composition in natural heterogeneous ecosystems at a large scale to accurately evaluate the real role of pika. In this study, we performed field survey at 55 alpine grassland sites across the Shule River Basin using combined methods of aerial photographing using an unmanned aerial vehicle (UAV) and traditional ground measurement. Based on our UAV operation system, Fragmentation Monitoring and Analysis with aerial Photography (FragMAP), aerial images were acquired. Plot-scale vegetation species were visually identified, and total pika burrow exits were automatically retrieved using the self-developed image processing software. We found that there were significant linear relationships between the vegetation species diversity indexes obtained by these two methods. Additionally, the total number of identified species by the UAV method was 71, which was higher than the Quadrat method recognition, with the quantity of 63. Our results indicate that the UAV was suitable for long-term repeated monitoring vegetation species composition of multiple alpine grasslands at plot scale. With the merits of UAV, it confirmed that pika’s disturbance belonged to the medium level, with the density ranging from 30.17 to 65.53 ha−1. Under this density level, pika had a positive effect on vegetation species diversity, particularly for the species richness of sedge and forb. These findings conclude that the UAV was an efficient and economic tool for species monitoring to reveal the role of pika in the alpine grasslands.

The species composition of aquatic (Nepomorpha) and semiaquatic (Gerromorpha) Heteroptera were examined from protected and unprotected study sites in three streams associated with Kaeng Krachan National Park. At each stream, both quantitative and qualitative sampling methods were used during seven collecting events (November 2018 to June 2020). A total of 11 families, representing 33 genera and 60 species, were collected in this study, with more Nepomorpha families but higher species richness in Gerromorpha. The species richness of both protected and unprotected sampling sites were lowest during the fifth sampling event. Nevertheless, there was no significant difference in richness between protected and unprotected sampling sites for any sampling event based on a paired t-test analysis. Based on an nMDS analysis, the patterns of species composition of aquatic and semiaquatic heteropterans were unclear among protected and unprotected sampling sites. The use of aquatic and semiaquatic Heteroptera as bioindicators for habitat quality is still uncertain. Additional physiochemical characters of the water and physical characters of the stream may lead to a clearer picture of the relationship between aquatic and semiaquatic Heteroptera and stream habitat quality.

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.

Tree species composition in forest ecosystems is an important biological factor affecting the diversity of ectomycorrhizal fungi (EMF). However, little is known about the composition and diversity of EMF communities associated with Pinus massoniana in different P. massoniana association habitats (MpAHs) in subtropical mountains. This study investigated the EMF community characteristics of P. massoniana in different MpAHs using plant community surveys, soil property analyses, and mycorrhizal identification. A total of 56 operational taxonomic units (OTUs), belonging to 20 families and 22 genera, were identified. OTU richness of Basidiomycota (58.93%) was higher than that of Ascomycota (41.07%). Unclassified Helotiales, Russula, Lactarius, and Tomentella were the dominant groups. Different stand types significantly altered the EMF communities of P. massoniana (p < 0.05, for Shannon index) and the associations of P. massoniana + Populus adenopoda (Mp_Pa) had the highest diversity of EMF, while P. massoniana + Cunninghamia lanceolata (Mp_Cl) had the lowest diversity. The number of specific OTUs was higher than shared OTUs. Similarity index and principal coordinate analysis indicated that the EMF communities of P. massoniana varied significantly in different MpAHs (R2 = 0.21, p = 0.001). The linear regression model showed that the EMF diversity of P. massoniana was positively related to tree species diversity, indicating that the EMF diversity of P. massoniana is influenced by tree species diversity. The findings provide a reasonable reference for tree species configuration in the process of mixed transformation or near-natural management of plantations.