This study investigated the spatial variability in soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN) and their possible relationships with other soil properties in the Hongqipao reservoir, which is dominated by different vegetation types. The results showed that there were high spatial variabilities in SOC, TN, SMBC and SMBN, and that the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth in the Hongqipao reservoir. The SOC was significantly positively correlated with TN, SMBC, moisture content (MC) and negatively correlated with carbon to nitrogen ratio (C:N ratio) and bulk density (BD). Soil TN was significantly positively correlated with SMBC, SMBN, MC and negatively correlated with the C:N ratio, BD and pH. The SMBC was significantly positively correlated with SMBN, MC and negatively correlated with the C:N ratio, BD and pH. The SMBN was significantly negatively correlated with the C:N ratio and BD. All of the measures of soil properties in this study could explain the higher significant variability in the response variables (SOC, TN, SMBC and SMBN contents). The generalized additive model (GAM) showed that SOC and TN had different influencing factors in different soil depths. The structural equation model (SEM) showed that vegetation types had a significantly positive effect on TN and SMBN, and the soil depths had a significantly positive effect on SOC and a significantly negative effect on TN and SMBC. This study further suggests that vegetation types play a major role in determining the spatial characteristics of soil carbon and nitrogen, and any changes in the vegetation types in the reservoir may influence the distributions of soil carbon and nitrogen. This may affect the global carbon and nitrogen budgets and the atmospheric greenhouse gas concentration significantly.

Plants regulate greenhouse gas (GHG) fluxes in wetland ecosystems, but the mechanisms of plant removal and plant species that contribute to GHG emissions remain unclear. In this study, the fluxes of carbon dioxide (CO₂) and nitrous oxide (N₂O) were measured using the static chamber method from an island forest dominated by two different species, namely Betula platyphylla (BP) and Larix gmelinii (LG), in a marsh wetland in the Great Xing’an Mountains. Four sub-plots were established in this study: (1) bare soil after removing vegetation under BP (SBP); (2) bare soil after removing vegetation under LG (SLG); (3) soil with vegetation under BP (VSBP); and (4) soil with vegetation under LG (VSLG). Additionally, the contributions of the dark respiration from plant aerial parts under BP (VBP) and LG (VLG) to GHG fluxes were calculated. We found that the substantial spatial variability of CO₂ fluxes ranged from −25.32 ± 15.45 to 187.20 ± 74.76 mg m⁻² h⁻¹ during the study period. The CO₂ fluxes decreased in the order of SBP > VSLG > VSBP > SLG > VLG > VBP, indicating that vegetation species had a great impact on CO₂ emissions. Particularly, the absence of vegetation promoted CO₂ emission in both BP and LG. Additionally, CO₂ fluxes showed dramatically seasonal variations, with high CO₂ fluxes in late spring (May) and summer (June, July, and August), but low fluxes in late summer (August) and early autumn (September). Soil temperatures at 0–20 cm depth were better predictors of CO₂ fluxes than deeper soil temperatures. N₂O fluxes were varied in different treatments with the highest N₂O fluxes in SLG and the lowest N₂O fluxes in VBP. Meanwhile, no significant correlation was found between N₂O fluxes and air or soil temperatures. Temporally, negative N₂O fluxes were observed from June to October, indicating that soil N₂O fluxes were reduced and emitted as N₂, which was the terminal step of the microbial denitrification process. Most of the study sites were CO₂ sources during the warm season and CO₂ sinks in the cold season. Thus, soil temperature plays an important role in CO₂ fluxes. We also found that the CO₂ flux was positively related to pH in a 10 cm soil layer and positively related to moisture content (MC) in a 50 cm soil layer in VSBP and VSLG. However, the CO₂ flux was negatively related to pH in a 30 cm soil layer in SBP and SLG. Our findings highlight the effects of vegetation removal on GHG fluxes, and aid in the scientific management of wetland plants.

Geographic heterogeneity, encompassing both species‐environment interactions and interspecific relationships, significantly influences the ecological attributes of wildlife habitat selection and population distribution. However, the impact of geographic heterogeneity on the distribution of target species within predator–prey systems, particularly in human‐dominated landscapes, remains unclear. By conducting line transect surveys, utilizing a monitoring network, and applying logistic geographically weighted regression (GWR) in conjunction with generalized linear models (GLM), we examined the spatial heterogeneity of habitat selection by the Amur tiger, Amur leopard, and their main ungulate prey, wild boar and roe deer, in Northeast China. Our results suggest that the factors affecting the spatial distribution of predators are more complex than those for prey. More significantly, the selection coefficients of roe deer and wild boar for certain habitat factors serve as crucial explanatory variables in the Amur tiger and leopard models. Our findings emphasize the importance of spatial non‐stationarity in predator–prey habitat selections, and the heterogeneous selection by prey may drive dispersals of large felids across complex road landscapes. This study offers new insights into how to help apex predators cross road barriers by effectively managing prey habitat selection in a landscape dominated by roads, providing valuable guidance for future habitat conservation policies.

Background: Niche differentiation is a fundamental mechanism facilitating the coexistence of sympatric species, yet the extent to which dietary partitioning is associated with gut microbial differentiation remains poorly understood in wild cervids. Methods: Here, we investigated winter dietary composition and fecal microbiome communities of three sympatric cervid species—moose ( Alces alces ), red deer ( Cervus elaphus ), and roe deer ( Capreolus pygargus )—in Youhao National Nature Reserve, northeastern China. A total of 55 fresh fecal samples were collected in January 2024, including 19 moose, 7 red deer, and 29 roe deer samples. Dietary composition was characterized using rbcL DNA metabarcoding, while microbiome communities were assessed using full-length 16S rRNA gene sequencing. Results: Our results showed the three cervid species exhibited distinct dietary patterns, moose showed a relatively narrow woody-plant-dominated diet, whereas red deer and roe deer exhibited higher dietary diversity, and roe deer exhibited broader use of shared plant resources; microbiome communities also differed significantly among host species, with moose showing the clearest separation from red deer and roe deer in community composition and predicted microbial metabolic potentials; Procrustes analysis revealed significant concordance between dietary composition and microbiome community, and redundancy analysis also indicated that dietary plant composition explained a significant proportion of variation in microbiome community. Conclusion: These findings demonstrate that trophic differentiation among sympatric cervids is accompanied by coordinated variation in gut microbial community structure and predicted functional potential. The results support a close ecological association between dietary niche differentiation and host-associated microbiome variation, while causal and directional mechanisms require confirmation through longitudinal, experimental, and direct functional studies.