Soil Chemical Properties Barely Perturb the Abundance of Entomopathogenic Fusarium oxysporum: A Case Study Using a Generalized Linear Mixed Model for Microbial Pathogen Occurrence Count Data

Fusarium oxysporum exhibits insect pathogenicity—however, generalized concerns of releasing phytopathogens within agroecosystems marred its entomopathogenicity-related investigations. In a previous study, soils were sampled from Douro vineyards and adjacent hedgerows. In this study, 80 of those soils were analyzed for their chemical properties and were subsequently co-related with the abundance of entomopathogenic F. oxysporum, after insect baiting of soils with Galleria mellonella and Tenebrio molitor larvae. The soil chemical properties studied were organic matter content; total organic carbon; total nitrogen; available potassium; available phosphorus; exchangeable cations, such as K+, Na+, Ca2+, and Mg2+; pH; total acidity; degree of base saturation; and effective cation exchange capacity. Entomopathogenic F. oxysporum was found in 48 soils, i.e., 60% ± 5.47%, of the total soil samples. Out of the 1280 insect larvae used, 93, i.e., 7.26% ± 0.72%, were found dead by entomopathogenic F. oxysporum. Stepwise deletion of non-significant variables using a generalized linear model was followed by a generalized linear mixed model (GLMM). A higher C:N (logarithmized) (p < 0.001) and lower exchangeable K+ (logarithmized) (p = 0.008) were found significant for higher fungal abundance. Overall, this study suggests that entomopathogenic F. oxysporum is robust with regard to agricultural changes, and GLMM is a useful statistical tool for count data in ecology.


Introduction
Entomopathogenic fungi are the natural biological control agents of insect pests [1]. The fungi belonging to Fusarium Link ex Grey (Hypocreales: Nectriaceae) are widely known as plant pathogens and saprophytes. Among animals, Fusarium spp. are quite abundantly associated with insects from different orders, i.e., Coleoptera, Diptera, Hemiptera, Isoptera, Lepidoptera, and Orthoptera [2,3]. A previous study emphasized the use of different Fusarium spp. as biological control agents for the agricultural insect pests, and aroused concern towards the limited research in this direction, pertaining to a generalized apprehension of releasing phytopathogens and related toxins in the environment [4]. Note: herbicide applied (1) and no herbicide applied (0). Other representations are organic matter % (OM), available phosphorous mg/kg (P), available potassium mg/kg (K), exchangeable calcium ions cmol/kg (Ca 2+ ), exchangeable magnesium ions cmol/kg (Mg 2+ ), exchangeable potassium ions cmol/kg (K + ), exchangeable sodium ions cmol/kg (Na + ), effective cation exchange capacity cmol/kg (ECEC), total nitrogen g/kg (N), total acidity (TA), and degree of base saturation % (DBS).

Effect of Soil Chemical Properties on Fungal Abundance
Previously, a generalized linear model (GLM) was used to relate the count data of F. oxysporum abundance with soil chemical properties, followed by the stepwise procedure for the deletion of non-significant variables. The only significant soil properties observed were the two log-transformed variables (i.e., log C:N and log K + ). This analysis was followed by a GLMM with only log C:N and log K + as the relevant soil properties, and the farm type as a random effect. For GLMM, the global significance of the model was p < 0.001 (Wald χ 2 = 17.516, d.f. = 2), and the AIC value was 228.7. Higher log C:N significantly promoted while higher exchangeable log K + significantly inhibited the abundance of F. oxysporum mycoses in insect larvae, respectively (Figure 1). The statistical values of the significance for the log-transformed variables were Wald χ 2 = 15.468, d.f. = 1, and p < 0.001 for log C:N, and Wald χ 2 = 6.976, d.f. = 1, and p = 0.008 for log K + . Other relevant values for these significant variables were estimate = 3.8238, standard error = 0.9722, and Z value = 3.933 for log C:N; and estimate = −0.7271, standard error = 0.2753, and Z-value = −2.641 for log K + .

Effect of Soil Chemical Properties on Fungal Abundance
Previously, a generalized linear model (GLM) was used to relate the count data of F. oxysporum abundance with soil chemical properties, followed by the stepwise procedure for the deletion of nonsignificant variables. The only significant soil properties observed were the two log-transformed variables (i.e., log C:N and log K + ). This analysis was followed by a GLMM with only log C:N and log K + as the relevant soil properties, and the farm type as a random effect. For GLMM, the global significance of the model was p < 0.001 (Wald χ 2 = 17.516, d.f. = 2), and the AIC value was 228.7. Higher log C:N significantly promoted while higher exchangeable log K + significantly inhibited the abundance of F. oxysporum mycoses in insect larvae, respectively (Figure 1)

Discussion
Biological communities in soils are likely to be the most complex. Microorganisms in the soils are extremely diverse, and they contribute to numerous ecosystem services that are critical to the sustainable functioning of both natural as well as managed ecosystems [17]. Agroecosystems, for example, constantly lose nutrients through leaching, run-off, denitrification, removal of crop harvest, and residues, and hence are dependent on continuous external inputs of nutrients. Such losses are likely to affect lower trophic levels, and ultimately influence different ecosystems services, such as pest suppression [18]. Soil microbes can affect crop yield, either (a) directly, e.g., as crop pathogens; or (b) indirectly, by participating in soil structure modification, carbon and nutrient cycles, and food web interactions. In either of these cases, soil microbes ultimately influence crop productivity [17,19,20]. To bridge the gaps between these phenomena, the current study focuses on the soil chemical properties with respect to the abundance of IPF F. oxysporum.
The most significant soil variable was the C:N (p < 0.001), which promoted the abundance of mycoses in insect larvae. Nitrogen is essential to plant growth and added as fertilizers in soils, if necessary. However, it was noticed that addition of the NPK fertilizers eventually reduces the density of entomopathogens-for example, nematodes [21]. Moreover, fertilizing soils tend to reduce the internal biological control within agroecosystems [18]. Higher organic matter, and hence, the higher organic carbon, increases the cation exchange capacity of the soils, which ultimately increases fungal conidia attachment [8]. Therefore, an increase in C and a decrease in N, which lead to a higher C:N, eventually facilitated the abundance of IPF F. oxysporum in our study.
Modeling has been an integral part in predicting phenomena in entomology. For example, it has been used previously to estimate flight phenology of world-famous insect pests, such as the European grapevine moth, or Lobesia botrana (Denis and Schiffermüller) (Lepidoptera: Tortricidae), in the Douro vineyards [13]. A generalized linear mixed model, with a previous GLM stepwise deletion of nonsignificant variables, provides a better outlook towards finding the variables that are significantly affecting the data. The stepwise GLM procedures allow the discarding of effects that do not differ significantly from zero. Further usage of a less complex model, such as GLMM, which is widely used in ecology [15], allowed improving the model and generalizing conclusions.

Discussion
Biological communities in soils are likely to be the most complex. Microorganisms in the soils are extremely diverse, and they contribute to numerous ecosystem services that are critical to the sustainable functioning of both natural as well as managed ecosystems [17]. Agroecosystems, for example, constantly lose nutrients through leaching, run-off, denitrification, removal of crop harvest, and residues, and hence are dependent on continuous external inputs of nutrients. Such losses are likely to affect lower trophic levels, and ultimately influence different ecosystems services, such as pest suppression [18]. Soil microbes can affect crop yield, either (a) directly, e.g., as crop pathogens; or (b) indirectly, by participating in soil structure modification, carbon and nutrient cycles, and food web interactions. In either of these cases, soil microbes ultimately influence crop productivity [17,19,20]. To bridge the gaps between these phenomena, the current study focuses on the soil chemical properties with respect to the abundance of IPF F. oxysporum.
The most significant soil variable was the C:N (p < 0.001), which promoted the abundance of mycoses in insect larvae. Nitrogen is essential to plant growth and added as fertilizers in soils, if necessary. However, it was noticed that addition of the NPK fertilizers eventually reduces the density of entomopathogens-for example, nematodes [21]. Moreover, fertilizing soils tend to reduce the internal biological control within agroecosystems [18]. Higher organic matter, and hence, the higher organic carbon, increases the cation exchange capacity of the soils, which ultimately increases fungal conidia attachment [8]. Therefore, an increase in C and a decrease in N, which lead to a higher C:N, eventually facilitated the abundance of IPF F. oxysporum in our study.
Modeling has been an integral part in predicting phenomena in entomology. For example, it has been used previously to estimate flight phenology of world-famous insect pests, such as the European grapevine moth, or Lobesia botrana (Denis and Schiffermüller) (Lepidoptera: Tortricidae), in the Douro vineyards [13]. A generalized linear mixed model, with a previous GLM stepwise deletion of non-significant variables, provides a better outlook towards finding the variables that are significantly affecting the data. The stepwise GLM procedures allow the discarding of effects that do not differ significantly from zero. Further usage of a less complex model, such as GLMM, which is widely used in ecology [15], allowed improving the model and generalizing conclusions.

Fungal Isolation, Identification, and Screening
Soils were brought within the campus, and approximately one kg of those soils was air-dried and preserved for physicochemical analyses. For isolation of the entomopathogenic F. oxysporum, the remaining soil portions were equilibrated for moisture overnight, and then baited with eight late-instar larvae of G. mellonella and eight late-instar larvae of Tenebrio molitor Linnaeus (Coleoptera: Tenebrionidae) within 24 h, as described in a previous study [1]. In brief, two sets of four insect larvae of each bait insect were used. To reduce the tendency of silk web formation, the larvae of G. mellonella were given a heat shock in the water bath at 56 • C prior to baiting. Soils were kept at a temperature of 22 • C and a relative humidity of 85%, in the dark inside an environmental chamber (Panasonic MLR-352H-PE). Bowls were frequently agitated and inverted to maximize larval reach for fungal spores in soils. The total incubation period was three weeks. Insect cadavers were monitored every second day to retrieve any mycosed larvae, and to discard cadavers that were infected by entomopathogenic nematodes. Cadavers with a foul smell were also regularly discarded. These schedules were monitored rigorously. Insect cadavers that were suspected to be mycosed by the fungus were then washed for three minutes with 1% NaOCl, followed by three distinct washes with 100 mL of sterilized water. Subsequent culturing on potato dextrose agar was conducted until pure cultures were obtained. Insects were procured as described in another study [2]. Fusarium oxysporum have diverse ecological roles, and therefore, insect baiting seemed a better approach than soil suspension culture or a DNA-based approach for the accurate functional annotation of the obtained F. oxysporum isolate. Fungus was identified using morphological and molecular techniques, as described previously [1]. Infectivity of the isolated fungi were further confirmed by Koch's postulates, as previously described [1,22,23]. Only the fungi that were found to be pathogenic after confirming Koch's postulates were further considered in the study. A total of 80 samples were tested for the presence and abundance of entomopathogenic F. oxysporum.

Soil Analyses and Calculations
Soil pH was determined one hour after preparing a soil-water suspension. Organic matter content was determined using a total organic carbon analyzer (Primacs SNC-100 , Skalar Analytical, Breda, The Netherlands). Total nitrogen was assessed by the Kjeldahl method, and the quantification was done using molecular absorption spectrophotometry [24]. The Egnér-Riehm method was used to extract P and K, and a spectrophotometer and a flame emission photometer (iCE™ 3300 AAS, Thermo Scientific TM , Breda, North Brabant, The Netherlands) was used for their respective determination. Exchangeable cations, or exchangeable bases, were measured by atomic absorption spectrophotometry, following the ammonium acetate extraction at a pH of 7.0 [25]. Titration method described in Thomas was used to determine exchangeable acidity [26]. Effective cation exchange capacity was calculated by summing exchangeable bases and exchangeable acidity. The degree of base saturation was measured by summing the exchangeable bases, dividing it by the ECEC, and then multiplying by 100.

Data Analyses
The abundance of the infected insects was analyzed using a generalized liner mixed model (GLMM), assuming a Poisson distribution for count data with a log link function. Model assumptions were inspected by visualizing residual plots. Soil properties were used as independent variables, herbicide application was considered as the fixed effect, and the farm type was considered as a random effect. The analysis started fitting the full model, which included all independent variables, followed by the stepwise procedure to remove non-significant variables [27]. The significance of the model was obtained using a Wald test, generated by the likelihood ratio tests of the full model with and without the explanatory variable. The analyses were performed in R (version 3.2.2) using the "MASS" package [28] and the "lme4" package [29].

Conclusions
Interactions between plants and microbes are quite complex, and it is necessary to move forward from a simplistic view of an individual plant-microbe interaction to all factors influencing agroecosystems. Soil, its microbes, and plants all work in coherence, and influence various exchanges contributing to plant health and productivity [30]. Soil provides fundamental ecosystem services, which include control of pests and diseases, nutrient cycling, and transformation of toxic materials and organic compounds. Microbes play a critical role in most of the soil processes. In this study, soil chemical properties affecting the presences of IPF F. oxysporum were investigated, and few significant findings could be made. Overall, it was noticed that entomopathogenic F. oxysporum is robust to most of the agricultural disturbances, although higher C:N and less exchangeable K + might facilitate its natural abundance. This study suggests that IPF F. oxysporum can survive effectively in different soils, which further highlights its capabilities as an excellent soil saprophyte in the absence of host insects, as hinted previously [5]. This kind of approach can be extended to other beneficial soil microbes.
Predicting soil microbial quality based on soil chemical properties could be a promising approach in the development of the methods for sustainable agriculture. Authors also suggest the use of GLMM in similar studies focusing on count data profiles, while accessing the factors affecting the abundance of the microbes of interest.