Intra-decadal increase in globally-spread Magallana gigas in southern California estuaries.

Introduction and establishment of non-indigenous species (NIS) has been accelerated on a global scale by climate change. NIS Magallana gigas' (formerly Crassostrea gigas') global spread over the past several decades has been linked to warming waters, specifically during summer months, raising the specter of more spread due to predicted warming. We tracked changes in density and size distribution of M. gigas in two southern California, USA bays over the decade spanning 2010-2020 using randomly placed quadrats across multiple intertidal habitats (e.g., cobble, seawalls, riprap) and documented density increases by 2.2 to 32.8 times at 7 of the 8 sites surveyed across the two bays. These increases in density were coincident with 2-4° C increases in median monthly seawater temperature during summer months, consistent with global spread of M. gigas elsewhere. Size frequency distribution data, with all size classes represented across sites, suggest now-regular recruitment of M. gigas. Our data provide a baseline against which to compare future changes in density and abundance of a globally-spread NIS of significant concern.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Taxonomic distinctness and diversity patterns of a polychaete (Annelida) community on the continental shelf of the Southern Gulf of Mexico.

The spatial patterns of taxonomic diversity of annelid polychaete species from the continental shelf in the Southern Gulf of Mexico were examined in this study. We used taxonomic distinctness and its spatial variations to explore the diversity patterns and how they change between Southern Gulf of Mexico regions. In addition, using taxonomic distinctness as a dissimilarity measure and Ward's Clustering, we characterized three distinct faunal assemblages. We also investigated patterns of richness, taxonomic distinctness, and distance decay of similarity between sampling stations as a ß-diversity measure. Finally, we examined the spatial relationships between polychaete assemblages and environmental variables to test the relative importance of spatial and environmental components in annelid polychaete community structure from the Southern Gulf of Mexico. We used a combination of eigenvector-based multivariate analyses (dbMEMs) and distance-based redundancy analysis (dbRDA) to quantify the relative importance of these explanatory variables on the spatial variations of taxonomic distinctness. The significance level of spatial and environmental components to the distribution of polychaete species showed that the combined effect of spatial processes and sediment characteristics explained a higher percentage of the variance than those parameters could alone.

The effects of intensive trapping on invasive round goby densities.

The round goby (Neogobius melanostomus) is an invasive benthic fish first introduced to the Laurentian Great Lakes in 1990 that has negatively impacted native fishes through increased competition for food and habitat, aggressive interactions, and egg predation. While complete eradication of the round goby is currently not possible, intensive trapping in designated areas during spawning seasons could potentially protect critical native fish spawning habitats. Baited minnow traps were spaced 10 meters apart in shallow water along a 100-meter stretch of shoreline within the Duluth-Superior Harbor during the round goby breeding period (June to October) with captured round gobies removed from interior traps (N = 10) every 48 hours. These traps were bracketed by two pairs of reference traps deployed weekly for 48 hours, from which round gobies were also tagged and released. The number of round gobies captured in the interior traps declined by 67% compared to reference traps over the course of the study, with extended periods of no captures. The tagged round gobies showed high site affinity, with 82.8% of tagged fish recaptured at the previous release site. The results indicate that even at open water sites, which allow natural migration of round gobies into the area, extensive trapping could reduce local population numbers.

All-you-can-eat buffet: A spider-specialized bat species (Myotis emarginatus) turns into a pest fly eater around cattle.

Determining the dietary spectrum of European insectivorous bats over time is the cornerstone of their conservation, as it will aid our understanding of foraging behavior plasticity in response to plummeting insect populations. Despite the global decline in insects, a restricted number of arthropod pest species thrive. Yet past research has overlooked the potential of European bats to suppress pests harmful to woodlands or livestock, in spite of their economic relevance. Here we investigated the diet composition, its breeding season variations and pest consumption of an insectivorous bat species (Myotis emarginatus), at the northern edge of its range (Wallonia, Belgium). We also explored the prey ecology to gain insight into the hunting strategies and foraging habitats of this bat species. We used DNA metabarcoding to amplify two COI markers within 195 bat droppings collected in June, July and August, thereby identifying 512 prey taxa predominated by Diptera, Araneae and Lepidoptera. Overall, in 97% of the samples we detected at least one of the 58 potential pest taxa, 41 of which targeting trees. The June samples were marked by a diet rich in orb-weaver spiders, in accordance with the archetypal diet of M. emarginatus bats. However, during the highly energy demanding July-August parturition and lactation period, roughly 55% of the dropping samples contained two cattle fly pests (Stomoxys calcitrans and Musca domestica). Moreover, among the 88 Diptera species preyed upon by M. emarginatus in July and August, these flies accounted for around 50% of the taxa occurrences. This plasticity-the switch from a spider-rich to a fly-rich diet-seems providential considering the dramatic ongoing drop in insect populations but this involves ensuring bat-friendly cattle farming. Our results revealed that bats widely consume pest entomofauna, thereby highlighting their potential role as allies of forest managers and farmers.

Assessment of land use and land cover change detection and prediction using deep learning techniques for the southwestern coastal region, Goa, India.

Understanding the connections between human activities and the natural environment depends heavily on information about land use and land cover (LULC) in the form of accurate LULC maps. Environmental monitoring using deep learning (DL) is rapidly growing to preserve a sustainable environment in the long term. For establishing effective policies, regulations, and implementation, DL can be a valuable tool for assessing environmental conditions and natural resources that will positively impact the ecosystem. This paper presents the assessment of land use and land cover change detection (LULCCD) and prediction using DL techniques for the southwestern coastal region, Goa, also known as the tourist destination of India. It consists of three components: (i) change detection (CD), (ii) quantification of LULC changes, and (iii) prediction. A new CD assessment framework, Spatio-Temporal Encoder-Decoder Self Attention Network (STEDSAN), is proposed for the LULCCD process. A dual branch encoder-decoder network is constructed using strided convolution with downsampling for the encoder and transpose convolution with upsampling for the decoder to assess the bitemporal images spatially. The self-attention (SA) mechanism captures the complex global spatial-temporal (ST) interactions between individual pixels over space-time to produce more distinct features. Each branch accepts the LULC map of 2 years as one of its inputs to determine binary and multiclass changes among the bitemporal images. The STEDSAN model determines the patterns, trends, and conversion from one LULC type to another for the assessment period from 2005 to 2018. The binary change maps were also compared with the existing state of the art (SOTA) CD methods, with STEDSAN having an overall accuracy of 94.93%. The prediction was made using an recurrent neural network (RNN) known as long short term memory network (LSTM) for the year 2025. Experiments were conducted to determine area-wise changes in several LULC classes, such as built-up (BU), crops (kharif crop (KC), rabi crop (RC), zaid crop (ZC), double/triple (D/T C)), current fallow (CF), plantation (PL), forests (evergreen forest (EF), deciduous forest (DF), degraded/scurb forest (D/SF) ), littoral swamp (LS), grassland (GL), wasteland (WL), waterbodies max (Wmx), and waterbodies min (Wmn). As per the analysis, over the period of 13 years, there has been a net increase in the amount of BU (1.25%), RC (1.17%), and D/TC( 2.42%) and a net decrease in DF (3.29%) and WL(1.44%) being the most dominant classes being changed. These findings will offer a thorough description of identifying trends in coastal areas that may incorporate methodological hints for future studies. This study will also promote handling the spatial and temporal complexity of remotely sensed data employed in categorizing the coastal LULC of a heterogeneous landscape.

A 1 Ma sedimentary ancient DNA (sedaDNA) record of catchment vegetation changes and the developmental history of tropical Lake Towuti (Sulawesi, Indonesia).

Studying past ecosystems from ancient environmental DNA preserved in lake sediments (sedaDNA) is a rapidly expanding field. This research has mainly involved Holocene sediments from lakes in cool climates, with little known about the suitability of sedaDNA to reconstruct substantially older ecosystems in the warm tropics. Here, we report the successful recovery of chloroplast trnL (UAA) sequences (trnL-P6 loop) from the sedimentary record of Lake Towuti (Sulawesi, Indonesia) to elucidate changes in regional tropical vegetation assemblages during the lake's Late Quaternary paleodepositional history. After the stringent removal of contaminants and sequence artifacts, taxonomic assignment of the remaining genuine trnL-P6 reads showed that native nitrogen-fixing legumes, C3 grasses, and shallow wetland vegetation (Alocasia) were most strongly associated with >1-million-year-old (>1 Ma) peats and silts (114-98.8 m composite depth; mcd), which were deposited in a landscape of active river channels, shallow lakes, and peat-swamps. A statistically significant shift toward partly submerged shoreline vegetation that was likely rooted in anoxic muddy soils (i.e., peatland forest trees and wetland C3 grasses (Oryzaceae) and nutrient-demanding aquatic herbs (presumably Oenanthe javanica)) occurred at 76 mcd (~0.8 Ma), ~0.2 Ma after the transition into a permanent lake. This wetland vegetation was most strongly associated with diatom ooze (46-37 mcd), thought to be deposited during maximum nutrient availability and primary productivity. Herbs (Brassicaceae), trees/shrubs (Fabaceae and Theaceae), and C3 grasses correlated with inorganic parameters, indicating increased drainage of ultramafic sediments and laterite soils from the lakes' catchment, particularly at times of inferred drying. Downcore variability in trnL-P6 from tropical forest trees (Toona), shady ground cover herbs (Zingiberaceae), and tree orchids (Luisia) most strongly correlated with sediments of a predominantly felsic signature considered to be originating from the catchment of the Loeha River draining into Lake Towuti during wetter climate conditions. However, the co-correlation with dry climate-adapted trees (i.e., Castanopsis or Lithocarpus) plus C4 grasses suggests that increased precipitation seasonality also contributed to the increased drainage of felsic Loeha River sediments. This multiproxy approach shows that despite elevated in situ temperatures, tropical lake sediments potentially comprise long-term archives of ancient environmental DNA for reconstructing ecosystems, which warrants further exploration.

Using neural ordinary differential equations to predict complex ecological dynamics from population density data.

Simple models have been used to describe ecological processes for over a century. However, the complexity of ecological systems makes simple models subject to modelling bias due to simplifying assumptions or unaccounted factors, limiting their predictive power. Neural ordinary differential equations (NODEs) have surged as a machine-learning algorithm that preserves the dynamic nature of the data (Chen et al. 2018 Adv. Neural Inf. Process. Syst.). Although preserving the dynamics in the data is an advantage, the question of how NODEs perform as a forecasting tool of ecological communities is unanswered. Here, we explore this question using simulated time series of competing species in a time-varying environment. We find that NODEs provide more precise forecasts than autoregressive integrated moving average (ARIMA) models. We also find that untuned NODEs have a similar forecasting accuracy to untuned long-short term memory neural networks and both are outperformed in accuracy and precision by empirical dynamical modelling . However, we also find NODEs generally outperform all other methods when evaluating with the interval score, which evaluates precision and accuracy in terms of prediction intervals rather than pointwise accuracy. We also discuss ways to improve the forecasting performance of NODEs. The power of a forecasting tool such as NODEs is that it can provide insights into population dynamics and should thus broaden the approaches to studying time series of ecological communities.

Is competitive ability the key adaptation to benign environments? Revisiting experiments on closely related species of tidal plants.

A central goal in biology is to understand which traits underlie adaptation to different environments. Yet, few studies have examined the relative contribution of competitive ability towards adaptive divergence among species occupying distinct environments. Here, we test the relative importance of competitive ability as an adaptation to relatively benign versus challenging environments, using previously published studies of closely related species pairs of primarily tidal plants subjected to reciprocal removal with transplant experiments in nature. Subordinate species typically occupy more challenging environments and showed consistent evidence for adaptation to challenging conditions, with no significant competitive effect on non-local, dominant species. In contrast, dominant species typically occupy relatively benign environments and performed significantly better than non-local, subordinate species that faced competition from the dominant species. Surprisingly, when the two species were not allowed to compete, the subordinate species performed as well as the dominant species in the benign environments where the subordinate species do not occur. These results suggest that competitive ability is the most important adaptation distinguishing the species that occupy relatively benign environments. The limited scope and number of suitable experimental studies encourage future work to test if these results are generalizable across taxa and environments.

The role of turnover in structuring subterranean aquatic communities in Southeastern Brazil.

Similarly to other animal communities, the diversity of subterranean aquatic fauna is influenced by several factors and processes, such as habitat fragmentation, dispersion, environmental heterogeneity, and physical and chemical water characteristics. Here, we studied cave aquatic communities of the Alto Ribeira hydrographic basin, regarding troglobitic and non-troglobitic species, located in a single karst area to evaluate the influence of sub-basins in fauna differentiation. We investigated how abiotic variables (flow, electrical conductivity, temperature, pH, and substrate) influence the fauna composition and the contribution of beta diversity components (nestedness and turnover) in explaining communities' dissimilarities. Fauna composition differed between sub-basins, as most species did not co-occur in different caves. Caves with higher flow and substrate diversity were the richest. In addition, each cave community was influenced by a unique set of abiotic variables. Dissimilarity among caves was mainly explained by turnover, and our findings suggest the restricted species distribution could be due to ecological (e.g., limited dispersion capacity, tolerance to abiotic variables), hydrogeological (e.g., dispersion barriers, isolation of sub-basins), and historical (e.g., colonization, paleoclimatic events) factors and processes. Therefore, different elements are responsible for determining the composition of cave aquatic communities in different sub-basins, reflecting the variability within a single karst area.

Ecological aspects of sand fly fauna (Diptera: Psychodidae, Phlebotominae) of Sumidouro District, State of Rio de Janeiro, Brazil.

Aiming to compare and update the sand fly fauna of Portão de Pedra site, Sumidouro District, Rio de Janeiro State, Brazil, and considering the environmental changes occurred, the biology and ecology of the local sandfly species were examined five years later as a complementary study carried. Captures were made in the cave, surroundings of cave and forest of the region, from 6 p.m. to 6 a.m. Among the 2323 sandflies of eigth species of the Lutzomyia were captured: L. gasparviannai, L. edwardsi, L. tupynambai, L. hirsuta, L. whitmani, L. migonei, L. intermedia, Lutzomyia. sp and one species of the Brumptomyia Kind: B. brumpti. In 2009 and 2010 were collected 1756 samples from ten species of the former genus and two of the second. L. gasparviannai was predominant, in the three collection sites, in both periods. Five species implicated as vectors of Leishmania: L. intermedia, L. whitmani, L. migonei, L. hirsuta and L. davisi have been collected in the area. Poisson regression and ANOVA were used to perform statistical analysis of species most relevant. The record of L. intermedia and a case of American tegumentary leishmaniasis are relevant to the public health of municipality and of state of Rio de Janeiro.

Co-located ecological data for exploring top- and subsoil carbon dynamics across grassland-woodland contrasts.

Soil organic carbon (SOC) is a soil health indicator and understanding dynamics changing SOC stocks will help achieving net zero goals. Here we present four datasets featuring 11,750 data points covering co-located aboveground and below-ground metrics for exploring ecosystem SOC dynamics. Five sites across England with an established land use contrast, grassland and woodland next to each other, were rigorously sampled for aboveground (n = 109), surface (n = 33 soil water release curves), topsoil, and subsoil metrics. Commonly measured soil metrics were analysed in five soil increments for 0-1 metre (n = 4550). Less commonly measured soil metrics which were assumed to change across the soil profile were measured on a subset of samples only (n = 3762). Additionally, we developed a simple method for soil organic matter fractionation using density fractionation which is part of the less common metrics. Finally, soil metrics which may impact SOC dynamics, but with less confidence as to their importance across the soil profile were only measured on topsoil (~5-15 cm = mineral soil) and subsoil (below 50 cm) samples (n = 2567).

Multispectral analysis-ready satellite data for three East African mountain ecosystems.

The East African mountain ecosystems are facing increasing threats due to global change, putting their unique socio-ecological systems at risk. To monitor and understand these changes, researchers and stakeholders require accessible analysis-ready remote sensing data. Although satellite data is available for many applications, it often lacks accurate geometric orientation and has extensive cloud cover. This can generate misleading results and make it unreliable for time-series analysis. Therefore, it needs comprehensive processing before usage, which encompasses multi-step operations, requiring large computational and storage capacities, as well as expert knowledge. Here, we provide high-quality, atmospherically corrected, and cloud-free analysis-ready Sentinel-2 imagery for the Bale Mountains (Ethiopia), Mounts Kilimanjaro and Meru (Tanzania) ecosystems in East Africa. Our dataset ranges from 2017 to 2021 and is provided as monthly and annual aggregated products together with 24 spectral indices. Our dataset enables researchers and stakeholders to conduct immediate and impactful analyses. These applications can include vegetation mapping, wildlife habitat assessment, land cover change detection, ecosystem monitoring, and climate change research.

Conservation units alone are insufficient to protect Brazilian Amazonian chelonians.

The creation of protected areas (PAs) is not always based on science; consequently, some aquatic species may not receive the same level of protection as terrestrial ones. The objective of this study was to identify priority areas for the conservation of chelonians in the Brazilian Amazon basin and assess the contribution of PAs, distinguishing between Full Protection Areas, Sustainable Use Areas, and Indigenous Lands for group protection. The entire species modeling procedure was carried out using Species Distribution Models. Location records were obtained from platforms such as SpeciesLink, GBIF, the Hydroatlas database, and WorldClim for bioclimatic variables adjusted with algorithms like Maximum Entropy, Random Forest, Support Vector Machine, and Gaussian-Bayesian. Indigenous lands cover more than 50% of the distribution areas of chelonian species in the Brazilian Amazon. Protected areas with higher conservation importance (Full Protection Areas and Sustainable Use Areas) hold less than 15% of the combined species distribution. Researchers face significant challenges when making decisions with models, especially in conservation efforts involving diverse taxa that differ significantly from one another within a group of individuals.

Interactive effects of drought and deforestation on multitrophic communities and aquatic ecosystem functions in the Neotropics-a test using tank bromeliads.

Background: Together with the intensification of dry seasons in Neotropical regions, increasing deforestation is expected to exacerbate species extinctions, something that could lead to dramatic shifts in multitrophic communities and ecosystem functions. Recent studies suggest that the effects of habitat loss are greater where precipitation has decreased. Yet, experimental studies of the pure and interactive effects of drought and deforestation at ecosystem level remain scarce. Methods: Here, we used rainshelters and transplantation from rainforest to open areas of natural microcosms (the aquatic ecosystem and microbial-faunal food web found within the rainwater-filled leaves of tank bromeliads) to emulate drought and deforestation in a full factorial experimental design. We analysed the pure and interactive effects of our treatments on functional community structure (including microorganisms, detritivore and predatory invertebrates), and on leaf litter decomposition in tank bromeliad ecosystems. Results: Drought or deforestation alone had a moderate impact on biomass at the various trophic level, but did not eliminate species. However, their interaction synergistically reduced the biomass of all invertebrate functional groups and bacteria. Predators were the most impacted trophic group as they were totally eliminated, while detritivore biomass was reduced by about 95%. Fungal biomass was either unaffected or boosted by our treatments. Decomposition was essentially driven by microbial activity, and did not change across treatments involving deforestation and/or drought. Conclusions: Our results suggest that highly resistant microorganisms such as fungi (plus a few detritivores) maintain key ecosystem functions in the face of drought and habitat change. We conclude that habitat destruction compounds the problems of climate change, that the impacts of the two phenomena on food webs are mutually reinforcing, and that the stability of ecosystem functions depends on the resistance of a core group of organisms. Assuming that taking global action is more challenging than taking local-regional actions, policy-makers should be encouraged to implement environmental action plans that will halt habitat destruction, to dampen any detrimental interactive effect with the impacts of global climate change.

Leopard density and determinants of space use in a farming landscape in South Africa.

Protected areas are traditionally the foundation of conservation strategy, but land not formally protected is of particular importance for the conservation of large carnivores because of their typically wide-ranging nature. In South Africa, leopard (Panthera pardus) population decreases are thought to be occurring in areas of human development and intense negative interactions, but research is biased towards protected areas, with quantitative information on population sizes and trends in non-protected areas severely lacking. Using Spatially Explicit Capture-Recapture and occupancy techniques including 10 environmental and anthropogenic covariates, we analysed camera trap data from commercial farmland in South Africa where negative human-wildlife interactions are reported to be high. Our findings demonstrate that leopards persist at a moderate density (2.21 /100 km2) and exhibit signs of avoidance from areas where lethal control measures are implemented. This suggests leopards have the potential to navigate mixed mosaic landscapes effectively, enhancing their chances of long-term survival and coexistence with humans. Mixed mosaics of agriculture that include crops, game and livestock farming should be encouraged and, providing lethal control is not ubiquitous in the landscape, chains of safer spaces should permit vital landscape connectivity. However, continuing to promote non-lethal mitigation techniques remains vital.

Temporal niche partitioning among sympatric wild and domestic ungulates between warm and cold seasons.

The coexistence of sympatric species with similar ecological niches has been a central issue in ecology. Clarifying the daily activity patterns of sympatric wild ungulates can help understand their temporal niche differentiation and the mechanisms of coexistence, providing information for their conservation. The Baotianman National Nature Reserve in northern China is rich in wild ungulates, but little is known about the daily activity patterns of wild ungulates in the area, making it difficult to develop effective conservation strategies. We studied five representative wild ungulates (i.e. forest musk deer, Chinese goral, Reeve's muntjac, Siberian roe deer, and wild boar) of the region using camera-trapping data, focusing on the seasonal daily activity patterns and effects of seasonal grazing of domestic sheep, to reveal their coexistence based on temporal ecological niche differentiation. Comparative analyses of the seasonal daily activity showed that forest musk deer exhibited a single-peak activity in the warm season. Other ungulates exhibited multipeak activity. All five ungulates differed significantly in daily activity patterns. Notably, wild boar and Reeve's muntjac showed high overlap coefficients between the cold and warm seasons. In both cold and warm seasons, the five wild ungulates and domestic sheep displayed low overlap in their daily activity rhythms potentially indicating temporal ecological niche differentiation. The results suggest that temporal isolation might be a strategy for wild ungulates to avoid domestic sheep and reduce interspecific competition, and that temporal ecological niche differentiation potentially promoted the coexistence among the studied sympatric ungulates. This understanding may provide new insights for the development of targeted conservation strategies.

Unexpected bat community changes along an urban-rural gradient in the Berlin-Brandenburg metropolitan area.

Urbanization gradients are increasingly used in ecological studies to discover responses of species communities to different intensities of human-induced habitat transformation. Here, we investigated patterns of bat communities against the background of different urbanization levels using a priori defined urbanization categories based on distance classes (5 km intervals) along a linear transect from the urban core of the city of Berlin westwards into the rural outskirts of the state of Brandenburg. Using linear-mixed effects models, we found that "distance class", as a proxy for urbanization level, is a meaningful and suitable predictor of bat species richness and diversity. We observed an unexpectedly sudden increase in bat species richness and diversity and changes in species-specific activity levels relatively close to the urban center at the transition between urban and peri-urban areas. This change suggests a relevant influence of the peri-urban areas as a "buffer zone" for specific bat species not able to adapt to the heavily modified inner core of the metropolitan area. Although we could demonstrate that anthropogenic noise and artificial light have the potential to predict the variability of bat species activity along the urban-rural gradient, the actual influence on observed shifts in the bat community needs further research.

Environmental specificity of karst cave habitats evidenced by diverse symbiotic bacteria in Opiliones.

BACKGROUND: Karst caves serve as natural laboratories, providing organisms with extreme and constant conditions that promote isolation, resulting in a genetic relationship and living environment that is significantly different from those outside the cave. However, research on cave creatures, especially Opiliones, remains scarce, with most studies focused on water, soil, and cave sediments. RESULTS: The structure of symbiotic bacteria in different caves were compared, revealing significant differences. Based on the alpha and beta diversity, symbiotic bacteria abundance and diversity in the cave were similar, but the structure of symbiotic bacteria differed inside and outside the cave. Microorganisms in the cave play an important role in material cycling and energy flow, particularly in the nitrogen cycle. Although microbial diversity varies inside and outside the cave, Opiliones in Beijing caves and Hainan Island exhibited a strong similarity, indicating that the two environments share commonalities. CONCLUSIONS: The karst cave environment possesses high microbial diversity and there are noticeable differences among different caves. Different habitats lead to significant differences in the symbiotic bacteria in Opiliones inside and outside the cave, and cave microorganisms have made efforts to adapt to extreme environments. The similarity in symbiotic bacteria community structure suggests a potential similarity in host environments, providing an explanation for the appearance of Sinonychia martensi in caves in the north.

Quantitative analysis of the impact of climate variability and human activities on grassland productivity of the Qilian Mountain National Park, China.

To quantitatively analyze the impact of climate variability and human activities on grassland productivity of China's Qilian Mountain National Park, this study used Carnegic-Ames-Stanford Approach model (CASA) and Integrated Vegetation model improved by the Comprehensive and Sequential Classification System (CSCS) to assess the trends of grassland NPP from 2000 to 2015, the residual trend analysis method was used to quantify the impact of human activities and climate change on the grassland based on the NPP changes. The actual grassland NPP accumulation mainly occurred in June, July and August (autumn); the actual NPP showed a fluctuating upward trend with an average increase of 2.2 g C·m-2 a-1, while the potential NPP increase of 1.6 g C·m-2 a-1 and human-induced NPP decreased of 0.5 g C·m-2 a-1. The annual temperature showed a fluctuating upward trend with an average increase of 0.1°C 10a-1, but annual precipitation showed a fluctuating upward trend with an average annual increase of 1.3 mm a-1 from 2000 to 2015. The area and NPP of grassland degradation caused by climate variability was significantly greater than that caused by human activities and mainly distributed in the northwest and central regions, but area and NPP of grassland restored caused by human activities was significantly greater than that caused by climate variability and mainly distributed in the southeast regions. In conclusion, grassland in Qilian Mountain National Park showed a trend of degradation based on distribution area, but showed a trend of restoration based on actual NPP. Climate variability was the main cause of grassland degradation in the northwestern region of study area, and restoration of grassland in the eastern region was the result of the combined effects of human activities and climate variability. Under global climate change, the establishment of Qilian Mountain National Park was of great significance to the grassland's protection and the grasslands ecological restoration that have been affected by humans.