## 4 Discussion  
The importance of zoonoses is increasingly recognized, and disease early warning-systems are currently receiving considerable research attention [34; 35]. Previous work has demonstrated that environmental conditions monitored by satellite imagery, including vegetation cover, landscape structure, soil moisture and water bodies [36; 37; 38], could be a potential information source for studying the ecology of zoonotic diseases, such as vector-borne and rodent-borne diseases [16; 39; 40], because the environmental conditions characterized by remote sensing images are considered to be linked to reservoir host habitats or pathogen infection risks.  
In this study, we evaluated the environmental conditions of farmland systems at field sites on the Weihe Plain that may be inhabited by HTNV rodent hosts, using MODIS products. We collected data during field campaigns, which provided strong evidence that the apparent time lag between the end of rodent host breeding [41] and subsequent HFRS peaks in humans was related to a biological process. In farmland with a simple vegetation structure, we found a higher correlation between _A. agrarius_ population density and PsnNet than between _A. agrarius_ population density and NDVI. This was not unexpected, because the impact of interannual fluctuations in crop output, which affects population density, is likely to be reflected by PsnNet.  
HFRS is still a serious disease in mainland China, which accounts for 90% of the cases reported globally [42]. In mainland China, HTNV and Seoul virus (SEOV), the major causative agents of HFRS, are carried by _A. agrarius_ (which thrives in rural areas) and _R. norvegicus_ (which thrives in urban areas), respectively [43; 44]. During the 96 months of trapping in the study area, _A. agrarius_ was the most frequently captured rodent species and the dominant species in the study area [45]. We applied a structure equation model to test the trophic cascade hypothesis in the farmland systems of central China, which supported the finding that primary productivity may affect rodent demography with a time lag. We inferred that the time lags might be due to the time needed for crop growth and rodent breeding activities to be seen in the trappable population. It follows that there would be a further few months after rodent demography was affected until the human-wildlife contact pattern was affected.  
Figure 7: Structural equation model for net photosynthesis (PsnNet), rodent population density and incidence of hemorrhagic fever with renal syndrome (HFRS). (\(\chi^{2}=2.34\), CFI \(=0.97\)). * Parameter is significant at the 0.05 level. ** Parameter is significant at the 0.01 level.  
It was, therefore, seen that the environmental variable, PsnNet, which represented the food availability for small rodents [46; 47] would be a useful indicator for natural HTNV infection warnings in this focal area of China.  
As climate variability plays an important role in shaping _A. agrarius_ population dynamics (and also those of other rodent species), as has been suggested by several previous studies [48; 49; 50; 51], the complex linkages between farmland conditions, _A. agrarius_ abundance, and climatic conditions should be studied in the future. Also, due to the various types of climate and habitat, further analyses and validation are needed for other endemic areas of China. Finally, we must acknowledge the limitations of this study. As the virus prevalence in rodent hosts affects disease dynamics, the epidemiology of HTNV should also be considered.