The effect of forest soil and community composition on ectomycorrhizal colonization and seedling growth

Plant–soil feedbacks have been observed in many forest communities, but the role of the mycorrhizal community in perpetuating feedback loops is still poorly understood. Mycorrhizal community composition is closely linked to soil properties and host plant composition, which highlights their potential importance in plant–soil–fungus loops. Eastern hemlock (hemlock; Tsuga canadensis) seedlings were grown in soil bioassays in growth chambers and transplanted under closed forest canopy to examine the effect of hardwood and hemlock forest soil on seedling growth, survival, and ectomycorrhizal fungi (EMF) colonization. Seedlings propagated in hemlock forest soil had greater height growth compared with sterile control soil and achieved greater mycorrhizal colonization than seedlings grown in hardwood forest soils after 9 months in a growth chamber. Outplanted seedlings grown in hemlock communities achieved significantly greater increment growth than those seedlings grown in hardwood communities (mean height difference (95% CI) = 0.39cm (0.14–0.63 cm)), although final survival and EMF colonization was similar between forest types. EMF diversity (Shannon-Wiener index (SE) = 1.88 (0.28) and 1.23 (0.44) for hardwood and hemlock, respectively) and community assemblage (Jaccard index (SE) = 19.0%(4%)) differed between the two forest communities. EMF community assemblage was associated with both the forest type (i.e. plant community/ microsite effects) and initial soil type (i.e. soil characteristics/resistant inoculum). The results support previously observed positive feedbacks between conspecifics under hemlock forest communities and provides evidence for the role of the EMF community within this feedback loop. Alternatively, the reduced growth of hemlocks under hardwoods may be attributed to the different EMF community associated with that forest

Choice of Weapon Sample Based on Fuzzy Logic in Defense Management Measures

The possibility of improving the capability-based planning process is being investigated in order to minimize the need for weapons and military equipment and to maximize the acquisition of capabilities during their life cycle. Using the theory of fuzzy sets, the assessment of alternative samples of weapons and military equipment is carried out. A fuzzy inference model for determining the usefulness of weapons and military equipment in acquiring opportunities has been developed, based on fuzzy logic. The modeling of alternative models of weapons and military equipment was carried out in terms of costs at the stages of the life cycle “Use” and “Support” using the modern software environment MATLAB. The simulation results provided an opportunity at the planning stage to improve the efficiency of defense resource management using the value of the usefulness of weapons and military equipment. The introduction of the developed model into defense management makes it possible to automatically determine weapons and military equipment without the participation of experts, taking into account the cost of their life cycle and to bring the planning process closer to Euro-Atlantic approaches