Using eDNA to detect the distribution and density of invasive crayfish in the Honghe-Hani rice terrace World Heritage site

The Honghe-Hani landscape in China is a UNESCO World Natural Heritage site due to the beauty of its thousands of rice terraces, but these structures are in danger from the invasive crayfish Procambarus clarkii. Crayfish dig nest holes, which collapse terrace walls and destroy rice production. Under the current control strategy, farmers self-report crayfish and are issued pesticide, but this strategy is not expected to eradicate the crayfish nor to prevent their spread since farmers are not able to detect small numbers of crayfish. Thus, we tested whether environmental DNA (eDNA) from paddy-water samples could provide a sensitive detection method. In an aquarium experiment, Real-time Quantitative polymerase chain reaction (qPCR) successfully detected crayfish, even at a simulated density of one crayfish per average-sized paddy (with one false negative). In a field test, we tested eDNA and bottle traps against direct counts of crayfish. eDNA successfully detected crayfish in all 25 paddies where crayfish were observed and in none of the 7 paddies where crayfish were absent. Bottle-trapping was successful in only 68% of the crayfish-present paddies. eDNA concentrations also correlated positively with crayfish counts. In sum, these results suggest that single samples of eDNA are able to detect small crayfish populations, but not perfectly. Thus, we conclude that a program of repeated eDNA sampling is now feasible and likely reliable for measuring crayfish geographic range and for detecting new invasion fronts in the Honghe Hani landscape, which would inform regional control efforts and help to prevent the further spread of this invasive crayfish

Identifying Forest Fire Driving Factors and Related Impacts in China Using Random Forest Algorithm

Reasonable forest fire management measures can effectively reduce the losses caused by forest fires and forest fire driving factors and their impacts are important aspects that should be considered in forest fire management. We used the random forest model and MODIS Global Fire Atlas dataset (2010~2016) to analyse the impacts of climate, topographic, vegetation and socioeconomic variables on forest fire occurrence in six geographical regions in China. The results show clear regional differences in the forest fire driving factors and their impacts in China. Climate variables are the forest fire driving factors in all regions of China, vegetation variable is the forest fire driving factor in all other regions except the Northwest region and topographic variables and socioeconomic variables are only the driving factors of forest fires in a few regions (Northwest and Southwest regions). The model predictive capability is good: the AUC values are between 0.830 and 0.975, and the prediction accuracy is between 70.0% and 91.4%. High fire hazard areas are concentrated in the Northeast region, Southwest region and East China region. This research will aid in providing a national-scale understanding of forest fire driving factors and fire hazard distribution in China and help policymakers to design fire management strategies to reduce potential fire hazards

Multifunctional Textile Platform for Fiber Optic Wearable Temperature-Monitoring Application

Wearable sensing technologies have been developed rapidly in the last decades for physiological and biomechanical signal monitoring. Much attention has been paid to functions of wearable applications, but comfort parameters have been overlooked. This research presents a developed fabric temperature sensor by adopting fiber Bragg grating (FBG) sensors and processing via a textile platform. This FBG-based quasi-distributed sensing system demonstrated a sensitivity of 10.61 ± 0.08 pm/°C with high stability in various temperature environments. No obvious wavelength shift occurred under the curvatures varying from 0 to 50.48 m−1 and in different integration methods with textiles. The temperature distribution monitored by the developed textile sensor in a complex environment with multiple heat sources was deduced using MATLAB to present a real-time dynamic temperature distribution in the wearing environment. This novel fabric temperature sensor shows high sensitivity, stability, and usability with comfort textile properties that are of great potential in wearable applications

Features and favorable exploration direction of normal faults in Jurassic strata in northern central Sichuan Basin, China

Studies focusing on the fault system in the Jurassic strata of the Sichuan Basin have been limited, restricting the understanding of the hydrocarbon accumulation mode of the Shaximiao Formation and the expansion of exploration. Through interpretation and coherent slice analysis of extensive seismic data, we have newly discovered that normal faults are widely developed in the northern central Sichuan Basin in the Jurassic strata. These faults mainly extend from the Lower to Upper Jurassic strata and are characterized by the continuous arrangement of NEE-trending small faults in the plane, with a few NNE-trending and NNW-trending faults also present. The distribution of Jurassic fault combinations varies within the basin, with normal faults mainly distributed in the low uplift areas of central Sichuan and the north of central Sichuan. Geochemical data comparisons indicate that these normal faults serve as conduits between the Jurassic source rocks and the Shaximiao Formation reservoir in these areas. Furthermore, the newly discovered normal faults are superimposed with the middle and lower Jurassic source rocks in the northern central Sichuan Basin, suggesting the formation of a new hydrocarbon accumulation model involving hydrocarbon generation from the middle and lower Jurassic, facilitated by communication through normal faults. Notably, one of the promising directions for exploration lies in the multi-stage channel superimposed development zone near these normal faults

Honghe Hani Terrace landscape in Yunnan, China, 30 March 2016.

<p>Honghe Hani Terrace landscape in Yunnan, China, 30 March 2016.</p

Environmental DNA detection and quantification in the aquarium experiment.

<p>The simulated density gradient of crayfish was achieved via a dilution series, where the average paddy has 10⁵ L of water. Logarithmic data has a better linear relation. Logarithm of CCT increases significantly with logarithm of crayfish density in all three sample sources. The estimated concentrations range lie between the Limit of Detection and the Limit of Quantification, as determined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177724#pone.0177724.g002" target="_blank">Fig 2</a>.</p

Comparison of eDNA and bottle-trapping with direct counts of crayfish.

<p>Direct counts are normalized to number of crayfish per average paddy (10⁵ L water). (A) the linear regression model for eDNA and direct counts of crayfish, and (B) for bottle-trapping and direct counts of crayfish.</p

Map of sampling locations. Dots from dark red to light red are scaled for estimated crayfish density as in Fig 5.

<p>Map of sampling locations. Dots from dark red to light red are scaled for estimated crayfish density as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177724#pone.0177724.g005" target="_blank">Fig 5</a>.</p

Honghe Hani Terrace landscape in Yunnan, China, 30 March 2016.

<p>Honghe Hani Terrace landscape in Yunnan, China, 30 March 2016.</p

Comparison of farmer reports, eDNA, bottle-trap index, and direct counts.

<p>The 32 paddies are divided into seven that had no crayfish reported, 21 that had crayfish and could be checked with direct counting, and four that had crayfish but could not be checked with direct counting. (a) eDNA, bottle-traps, and direct counts all confirmed that the seven farmer-reported crayfish-free paddies were free of crayfish. (b) eDNA and direct counts confirmed that the 21 farmer-reported crayfish-containing paddies had crayfish, but bottle-traps failed to detect crayfish in 7 of those paddies, including one (paddy 15) that was deemed high density by farmer report, eDNA, and direct counts. (c) Finally, eDNA confirmed that all four uncounted farmer-reported, crayfish-containing paddies had crayfish, but bottle-traps failed to detect crayfish in one of them. The intensity of the red color indicates crayfish density estimates by direct counts, eDNA, and bottle trapping. The latter two were converted using the fitted models in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177724#pone.0177724.g004" target="_blank">Fig 4</a>. N indicates no crayfish reported or detected. X indicates direct count not carried out. H and M indicate farmer reports of “high” and “medium” crayfish densities.</p