Effect of Insecticides on Natural-Enemies

Pesticides management options for control of invertebrate pests in many parts of the world. Despite an increase in the use of pesticides, crop losses due to pests have remained largely unchanged for 30–40 years. Beyond the target pests, broad-spectrum pesticides may affect non-target invertebrate species, including causing reductions in natural enemy population abundance and activity, and competition between pest species. Assays of invertebrates against weathered residues have shown the persistence of pesticides might play an important part in their negative impacts on natural enemies in the field. A potential outcome of frequent broad-spectrum pesticide use is the emergence of pests not controlled by the pesticides but benefiting from reduced mortality from natural enemies and competitive release, commonly known as secondary pests.

Migration routes, population status and important sites used by the globally threatened Black-faced Spoonbill (Platalea minor): a synthesis of surveys and tracking studies

Background The Black-faced Spoonbill (Platalea minor) is a globally threatened species, nesting mainly in western Korea with smaller numbers breeding in Liaoning Province, China, and Far East Russia. Recent winter field surveys to estimate the species’ population size were almost totally conducted in coastal areas, but tracking studies showed that some individuals now winter inland. To ensure its long-term survival, we need a more comprehensive assessment of the current distribution and abundance of the species. Methods We combined the most recent count data and satellite tracking information to update existing information about the population abundance and distribution of the Black-faced Spoonbill at all stages of its annual life cycle, and how these have changed during 2004–2020. Results Black-faced Spoonbills mainly breed on the west coast of the Korean peninsula, while immature birds show a wider summer distribution throughout Yellow Sea coastal areas, when a few remain on wintering sites in the south. Combined tracking results and mid-winter counts confirmed known wintering sites on the east and south coasts of China, but showed that the species also winters on wetlands in the Yangtze River floodplain and in Southeast Asia. During 2004–2020, counts of wintering birds in coastal habitats increased from 1198 to 4864, with numbers wintering on the island of Taiwan contributing most to the overall increase. Latest counts found 5222 in 2021. We also identify key wintering and stopover sites as well as their current conservation status. Conclusions This study revised the known summering and wintering ranges of the Black-faced Spoonbill and assessed the conservation status of key sites based on a combination of field survey and satellite tracking data. We recommend prioritisation of further field research to identify and survey inland wintering areas in the Yangtze River floodplain and summering areas of immature birds. More tracking of adult individuals and birds during spring migration is necessary to fill these information gaps. We also suggest establishing a Black-faced Spoonbill monitoring platform to store, share and show real-time distribution range and population abundance data.

Spatial and Temporal Modelling of Hoki Distribution using Gaussian Markov Random Fields

<p>In order to carry out assessment of marine stock levels, an accurate estimate of the current year's population abundance must be formulated. Standardized catch per unit of effort (CPUE) values are, in theory, proportional to population abundance. However, this only holds if the species catchability is constant over time. In almost all cases it is not, due to the existence of spatial and temporal variation. In this thesis, we fit various models to test different combinations and structures of spatial and temporal autocorrelation within hoki (Macruronus novaezelandiae) CPUE. A Bayesian approach was taken, and the spatial and temporal components were modelled using Gaussian Markov random fields. The data was collected from summer research trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA) and the Ministry for Primary Industries (MPI). It allowed us to model spatial distribution using both areal and point reference approaches. To fit the models, we used the software Stan (Gelman et al., 2015) which implements Hamiltonian Monte Carlo. Model comparison was carried out using the Watanabe-Akaike information criterion (WAIC, (Watanabe, 2010)). We found that trawl year was the most important factor to explain variation in research survey hoki CPUE. Furthermore, the areal approach provided better indices of abundance than the point reference approach.</p>

Spatial and Temporal Modelling of Hoki Distribution using Gaussian Markov Random Fields

<p>In order to carry out assessment of marine stock levels, an accurate estimate of the current year's population abundance must be formulated. Standardized catch per unit of effort (CPUE) values are, in theory, proportional to population abundance. However, this only holds if the species catchability is constant over time. In almost all cases it is not, due to the existence of spatial and temporal variation. In this thesis, we fit various models to test different combinations and structures of spatial and temporal autocorrelation within hoki (Macruronus novaezelandiae) CPUE. A Bayesian approach was taken, and the spatial and temporal components were modelled using Gaussian Markov random fields. The data was collected from summer research trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA) and the Ministry for Primary Industries (MPI). It allowed us to model spatial distribution using both areal and point reference approaches. To fit the models, we used the software Stan (Gelman et al., 2015) which implements Hamiltonian Monte Carlo. Model comparison was carried out using the Watanabe-Akaike information criterion (WAIC, (Watanabe, 2010)). We found that trawl year was the most important factor to explain variation in research survey hoki CPUE. Furthermore, the areal approach provided better indices of abundance than the point reference approach.</p>

Diversity Analysis of Soil Microbial Population Abundance Before and After Planting JunCao "Oasis No. 1" in Saline-Alkali Soil

In order to explore the difference of soil microbial population structure and abundance before and after planting JunCao"Oasis No. 1" in saline-alkali soil, verify the improvement effect of JunCao"Oasis No. 1" on microbial population structure and abundance in saline-alkali soil. Samples were collected from the blank saline area with and without JunCao"Oasis NO.1" and no plant growth on the surface, respectively, as Experimental group soil samples (S.Y.1-S.Y.8) and Blank group soil samples (K.B.1-K.B.8).16sDNA high-throughput sequencing technology was used for sequencing analysis respectively, and the diversity of microbial population abundance between them was compared and analyzed.The results showed that the diversity of microbial population abundance in the experimental group was significantly higher than that in the blank group, and the diversity of microbial population abundance in the experimental group was significantly different from that in the blank group, indicating that the composition of microbial population in the experimental group was significantly different from that in the blank group. In the OTU cluster analysis, the number of OTU clusters in the Experimental group soil samples (S.Y.1-S.Y.8) was significantly higher than that in the Blank group soil samples (K.B.1-K.B.8). In the sample complexity analysis of α-diversity analysis, the richness and diversity of microbial population in soil samples of Experimental group (S.Y.1-S.Y.8) were significantly higher than that in soil samples of Blank group (K.B.1-K.B.8), which was clearly reflected in the Species accumulation boxplot and Graph of species diversity. In the β-diversity analysis, PcoA, PCA and NMDS analysis methods were used to analyze the difference of microbial population diversity between Experimental soil samples (S.Y.1-S.Y.8) and Blank soil samples (K.B.1-K.B.8). The results showed that the diversity of microbial population in Experimental soil sample (S.Y.1-S.Y.8) was significantly different from that in Blank soil sample (K.B.1-K.B.8). In this paper, 16sDNA high-throughput sequencing technology was used to analyze the diversity of microbial population abundance between Blank soil samples and Experimental soil samples, and it was proved that JunCao"Oasis No. 1" had good saline-alkali soil improvement characteristics. It can effectively increase the abundance of microbial population in saline-alkali soil, so as to restore the microbial population ecosystem in saline-alkali soil, which has important application value in soil saline-alkali control.

Deep Profiling of the Immune Microenvironment throughout Myeloma Disease Stages

Background The immune system is altered in multiple myeloma (MM) and contributes to therapy resistance. The availability of novel immunotherapies necessitates understanding the influence of the immune microenvironment on disease progression which may inform sensitivity to therapy. The objective of this study is to fully characterize the immune microenvironment in MM precursor diseases and MM and identify any immune contribution to progression. To accomplish this we used high-dimensional mass cytometry (CyTOF) to investigate immune alterations associated with progression in pre-malignant and malignant stages of MM. Methods Cryopreserved bone marrow mononuclear cells (BMMCs) from healthy donors (HD, n=13), MGUS (n=21), SMM (n=19), newly diagnosed MM (NDMM, n=17), and ~3 months post- first autologous stem cell transplant (ASCT, n=21) were assessed using a panel of 35 cell surface and 3 intracellular antibodies that includes cell lineage markers for identification of immune populations and functional markers indicative of positive or negative immune regulation. BMMCs were thawed, stained with antibodies, and analyzed on a Helios mass cytometer. Data were normalized using bead normalization, transformed using the inverse hyperbolic sine function with a cofactor of 5 and gated for 45+ live, intact, singlets for global analysis by gating in FCS express and clustering by viSNE for visualization. Differences in population abundance were identified in an unbiased manner by FlowSOM and in marker intensity by CITRUS. Marker intensity analysis was performed using the multiple testing permutation procedure (SAM), with an FDR of 1% and minimum population size of 0.5%. Results To identify changes in the immune microenvironment associated with progression we compared immune population abundance and marker intensity indicative of immune status including activation, exhaustion, or senescence. MGUS was distinguished from HD by increased abundance of CD4 central memory (CM, p&lt;0.001), effector memory (EM, p&lt;0.001) and plasmacytoid and monocyte-derived dendritic cells (DC, p&lt; 0.01). In MGUS, TIM3 and CD57 were elevated on NK cells and NKT cells, respectively, compared to HD suggesting reduced activity. In SMM increased abundance of B regulatory cells (3.0 vs 5.9 %, p&lt;0.01) but reduced inhibitory markers on T cells including PD1, CTLA4 CD55, FOXP3 and TIGIT was observed compared to MGUS. NDMM was distinguished from SMM by reduced abundance of CD4 EM (p&lt;0.01), CD8 early EM (p&lt; 0.001), and B regulatory cells (p&lt;0.01) and increased abundance of active Tregs (CD38+, P&lt;0.01) and total NK cells (p&lt;0.01) which had increased CD55, a complement inhibitory protein. Post-ASCT changes in immune abundance include increased total CD8 and CD8 terminal effectors (CD57 +, p&lt; 0.0001), B regulatory cells (p&lt;0.0001), and reduced total CD4 and CD4 CM (p&lt;0.0001), compared to NDMM. CD4 T cells post-ASCT were characterized by reduced CD127 and CCR7 and increased CD28, CTLA4, FOXP3 and TIGIT and CD8 T cells had reduced CD28, CD127 and CCR7 and increased CD57 and TIGIT compared to NDMM. Interestingly, significant difference in NK cells were not observed but post-ASCT NK cells may be active as suggested by reduced CD59 and TIM3 compared to NDMM. To determine whether the immune microenvironment had normalized by 3 months post-ASCT we compared population abundance to HD, MGUS, and SMM cases. Immune abundance post-ASCT revealed a significantly lower percentage of CD4 CM, 4 -8 - T cells, normal PCs, and post-switch B cells (25+) and elevated CD8 terminal effector (57+) and B regulatory cells than all 3 other groups. Overall major differences in abundance of total T and B cells and their subsets were observed with differences in NK cells between stages primarily reflected in marker expression (e.g. CD161+ subset) rather than abundance. Conclusions Early changes in the immune microenvironment observed in MGUS/SMM lead to immune suppression and eventually immune evasion allowing MM to emerge. In this study the immune ME did not appear to normalize 3 months post-therapy indicated by an increase in B regulatory cells and markers of inactive effector cells. Profiling of the immune microenvironment throughout MM treatment may allow us to identify novel therapeutic targets and optimal timing of administration of novel immunotherapies and patients that would most benefit from these therapies. Disclosures Walker: Sanofi: Speakers Bureau; Bristol Myers Squibb: Research Funding. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees.