Exclosure fences around nests of imperiled Florida Grasshopper Sparrows reduce rates of predation by mammals

Increasing nest survival by excluding predators is a goal of many bird conservation programs. However, new exclosure projects should be carefully evaluated to assess the potential risks of disturbance. We tested the effectiveness of predator exclosure fences (hereafter, fences) for nests of critically endangered Florida Grasshopper Sparrows (Ammodramus savannarum floridanus) at a dry prairie site (Three Lakes; 2015–2018) and a pasture site (the Ranch; 2015–2016) in Osceola County, Florida, USA. We installed fences at nests an average of 8 days after the start of incubation, and nest abandonment after fence installation was rare (2 of 149 installations). Predation was the leading cause of failure for unfenced nests at both sites (48–73%). At Three Lakes, nest cameras revealed that mammals and snakes were responsible for 61.5% and 38.5% of predation events, respectively, at unfenced nests. Fences reduced the daily probability of predation (0.016 for fenced nests vs. 0.074 for unfenced nests). The probability that a fenced nest would survive from discovery to fledging was more than double that of unfenced nests (60.4% vs. 27.7%). However, we found no difference in daily nest survival at the Ranch between the year before nests were fenced (2015; 0.874) and the year when all but one nest were fenced (2016; 0.867) because red imported fire ants (Solenopsis invicta) were responsible for 86% of predation events at fenced nests at the Ranch. The use of cameras at fenced nests revealed that site‐specific differences in nest predators explained variation in fence efficiency between sites. Our fence design may be useful for other species of grassland birds, but site‐specific predator communities and species‐specific response of target bird species to fences should be assessed before installing fences at other sites.     

Distribution and multiplication of Ralstonia solanacearum strain race 1 biovar 4 in vegetable sweet potato cuttings

Ralstonia solanacearum (RS) race 1 biovar 4 (R1bv4), causal agent of bacterial wilt in vegetable sweet potato (VSP), is often latent in VSP vines and is important in introduction of the pathogen to newly planted fields. In this study, the effects of biological and environmental factors on the distribution and multiplication of R1bv4 in VSP tissues were examined. Based on stem-injection inoculation, the R1bv4strain of NC01 could cause 49.0% and 33.0% wilting on VSP cultivars TN71 and WS, respectively. The populations of NC01 in diseased TN71 and WS were 10⁸–10⁹ cfu/g tissue at 28th day after inoculation. On the other hand, the R1bv4 could not cause symptom in cultivars of TN57 and VSPSL-1 vine and the NC01 was confined to near the injection sites. Temperature tests indicated that NC01 could cause 28.0% and 14.0% wilting on cultivar TN71 at 28 and 20°C, respectively. Moreover, the populations of NC01in diseased plants were 1.6 × 10⁹ and 7.9 × 10⁸ cfu/g tissue at 28 and 20°C, respectively. The distribution of NC01 in VSP stem indicated that the isolation frequency of NC01 was lower than 31.0% in terminal shoots or erect stems and 45.0 to 100.0% in creeping stem after 8 wks planted in infested soil (10⁶ cfu/g soil). The results demonstrated that terminal shoots or erect stems were not common carrier for transmitting R1bv4. Furthermore, two R1bv4 strains, NC01 and HsinT01, were examined the ability for latent infection on cv. TN71. The results revealed that NC01 and HsinT01 showed different ability of latent infection on cultivar TN71. NC01 had lower percentage (46.8% and 45.1%) than HsinT01 (93.4% and 75.3%) at 20 and 28°C.     

Identification and partial characterization of a latent ATP,Mg-dependent protein phosphatase in rabbit skeletal muscle cytosol

Summary Fractionation of rabbit skeletal muscle cytosol on Aminohexyl-Sepharose has resulted in the identification of a latent ATP, Mg-dependent protein phosphatase whose catalytic subunit is in the active conformation, but is inhibited by the presence of more than one modulator unit. The partially purified enzyme is converted to an inactive, kinase F_A-dependent form upon incubation at 30°C unless modulator-specific polyclonal antibodies are added to the preparation. The immunoglobulins also relieve the inhibition which is responsible for the low basal phosphatase activity of the enzyme, and they counteract all of the heat-stable inhibitor activity present in the preparation. Addition of free catalytic subunit abolishes the inhibition of the latent enzyme in a dose-dependent way, but cannot prevent the inactivation process. The inactivated phosphatase and the original latent enzyme exhibit the same apparent M _r in sucrose density-gradient centrifugation (70 000) and in gel filtration (110 000).Abbreviations PMSF Phenylmethanesulphonyl Fluoride - TLCK L-l-chloro-3-(4-tosylamido)-7-amino2-heptanone-hydrochloride - TPCK L-l-chloro-3-(4-tosvlamido)-4-phenyl-2-butanone     

Ammoniacal silver staining of proteins: mechanism of glutaraldehyde enhancement

When the conditions for detecting proteins by ammoniacal silver staining (B. R. Oakley, D. R. Kirsch, and N. R. Morris (1980) Anal. Biochem. 105, 361-363.) following gel electrophoresis were varied, it was noted that glutaraldehyde pretreatment was necessary for maximal staining, which could not be explained simply as the result of "fixation." Further studies indicated that glutaraldehyde enhancement of protein staining with this silver reagent was probably due to oxidation of the aldehyde groups by silver ions, resulting in metallic silver depositions within the gel which act as nucleation sites for additional metallic silver localization in the protein bands upon the addition of formaldehyde developer. This proposed mechanism is consistent with the Tollen's reaction, as well as some aspects of the photographic process. Consistent with this notion, silver-staining intensities are directly related to mole percentage lysine of various standard proteins.     

Latent group detection in functional partially linear regression models

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. We develop an algorithm in the spirit of the K-means clustering to identify latent groups of the subjects under study. We establish the consistency of the proposed estimator, derive the convergence rate and the asymptotic distribution, and develop inference procedures. We show by simulation studies that the proposed method has higher accuracy for recovering latent groups and for estimating the functional coefficients than existing methods. The analysis of the barley data shows that the proposed method can help identify groups of barley families with different salinity tolerant abilities.     

Integrating sample similarities into latent class analysis: a tree-structured shrinkage approach

This paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree-structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data-driven leaf groups with distinct vectors of class probabilities, and (3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.     

A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching

Analysts often estimate treatment effects in observational studies using propensity score matching techniques. When there are missing covariate values, analysts can multiply impute the missing data to create m completed data sets. Analysts can then estimate propensity scores on each of the completed data sets, and use these to estimate treatment effects. However, there has been relatively little attention on developing imputation models to deal with the additional problem of missing treatment indicators, perhaps due to the consequences of generating implausible imputations. However, simply ignoring the missing treatment values, akin to a complete case analysis, could also lead to problems when estimating treatment effects. We propose a latent class model to multiply impute missing treatment indicators. We illustrate its performance through simulations and with data taken from a study on determinants of children's cognitive development. This approach is seen to obtain treatment effect estimates closer to the true treatment effect than when employing conventional imputation procedures as well as compared to a complete case analysis.     

Complex structural effects of two hemispheric climatic oscillators on the regional spatio-temporal expansion of a threatened bird

Links between climatic conditions in the eastern equatorial Pacific and extratropical ecological processes remain unexplored. The analysis of a 20‐year time series of spatial and numeric dynamics of a threatened Mediterranean bird suggests, however, that such couplings can be remarkably complex. By providing a new ecological time‐series modelling approach, we were able to dissect the joint effects of the El Niño/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), regional weather, population density and stochastic variability on the expansion dynamics of the White‐headed duck (Oxyura leococephala) in Spain. Our results suggest that the spatial and numeric dynamics of ducks between peak brood emergence and wintering were simultaneously affected by different climatic phenomena during different phases of their global cycles, involving time lags in the numeric dynamics. Strikingly, our results point to both the NAO and the ENSO as potentially major factors simultaneously forcing ecological processes in the Northern Hemisphere, and suggest a new pathway for non‐additive effects of climate in ecology.     

Development of Meloidogyne arenaria on Peanut and Soybean under Two Temperature Cycles

Florunner peanut and three soybean cultivars, Centennial, Gasoy 17, and Wright, were inoculated with 48-hour age cohorts of Meloidogyne arenari race 1 second-stage juveniles and placed in a growth chamber set to simulate early season (low temperature) and midseason (high temperature) conditions. Percentages of the initial inoculum penetrating roots 4 and 8 days after inoculation were 2-3 times higher in soybean cultivars than in peanut; 25% on susceptible soybean and 9% on peanut. Penetration and early development of M. arenaria were greater in the higher temperature environment. Penetration percentages were expressed as a function of cumulative degree-days by regression models. Development of M. arenaria 10, 20, and 30 days after inoculation was more rapid on peanut than on soybean. The resistant soybean cultivar Wright had slower development rates than did the other two soybean cultivars. Nematode growth and development were dependent on temperature. In greenhouse experiments, production of eggs by M. arenaria was more than 10 times greater on peanut than on susceptible soybean. The reproductive factor for Wright soybean was less than one, but plant growth parameters indicated that this cultivar was intolerant of M. arenavia.