Water inputs across a tropical montane landscape in Veracruz,Mexico: synergistic effects of land cover,rain and fog seasonality,and interannual precipitation variability

Land‐cover change can alter the spatiotemporal distribution of water inputs to mountain ecosystems, an important control on land‐surface and land‐atmosphere hydrologic fluxes. In eastern Mexico, we examined the influence of three widespread land‐cover types, montane cloud forest, coffee agroforestry, and cleared areas, on total and net water inputs to soil. Stand structural characteristics, as well as rain, fog, stemflow, and throughfall (water that falls through the canopy) water fluxes were measured across 11 sites during wet and dry seasons from 2005 to 2008. Land‐cover type had a significant effect on annual and seasonal net throughfall (NTF <0=canopy water retention plus canopy evaporation; NTF >0=fog water deposition). Forest canopies retained and/or lost to evaporation (i.e. NTF<0) five‐ to 11‐fold more water than coffee agroforests. Moreover, stemflow was fourfold higher under coffee shade than forest trees. Precipitation seasonality and phenological patterns determined the magnitude of these land‐cover differences, as well as their implications for the hydrologic cycle. Significant negative relationships were found between NTF and tree leaf area index (R²=0.38, P<0.002), NTF and stand basal area (R²=0.664, P<0.002), and stemflow and epiphyte loading (R²=0.414, P<0.001). These findings indicate that leaf and epiphyte surface area reductions associated with forest conversion decrease canopy water retention/evaporation, thereby increasing throughfall and stemflow inputs to soil. Interannual precipitation variability also altered patterns of water redistribution across this landscape. Storms and hurricanes resulted in little difference in forest‐coffee wet season NTF, while El Niño Southern Oscillation was associated with a twofold increase in dry season rain and fog throughfall water deposition. In montane headwater regions, changes in water delivery to canopies and soils may affect infiltration, runoff, and evapotranspiration, with implications for provisioning (e.g. water supply) and regulating (e.g. flood mitigation) ecosystem services.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

A new species of Galearis (Orchidinae: Orchidaceae) from Sichuan,China

A new species, Galearis huanglongensis Q.W.Meng & Y.B.Luo, is described and illustrated. It is similar to Galearis cyclochila (Franch. & Sav.) Soó and Galearis diantha (Schltr.) P.F.Hunt, but differs in having a short spur, two elliptical lateral stigma lobes and distinctly separated bursicles. This new species is known only from the type locality, the Huanglong Valley, Songpan County, western Sichuan, China, growing amongst mosses under alpine shrubs at an elevation of about 3000 m. Based on two years of observations of its population size, the species was categorized as critically endangered CR (B1a, B2a) according to the World Conservation Union (IUCN) Red List Categories and Criteria, Version 3.1. The micromorphology of pollinia and seeds was observed by scanning electron microscopy and compared with that of G. cyclochila and G. diantha. The results supported G. huanglongensis Q.W.Meng & Y.B.Luo as a new species. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 158 , 689–695.     

Spatial and temporal factors associated with nest survival of Gray Flycatchers in managed ponderosa pine forests

Gray Flycatchers (Empidonax wrightii) breed in a variety of habitats in the arid and semi‐arid regions of the western United States, but little is known about their breeding biology, especially in the northern portion of their range where they nest in ponderosa pine (Pinus ponderosa) forests. From May to July 2014 and 2015, we conducted surveys for singing male Gray Flycatchers along the eastern slope of the Cascade Range in Washington, U.S.A, monitored flycatcher nests, and quantified nest‐site vegetation. We used a logistic‐exposure model fit within a Bayesian framework to model the daily survival probability of flycatcher nests. During the 2 yr of our study, we monitored 141 nests, with 93% in ponderosa pines. Mean clutch size was 3.6 eggs and the mean number of young fledged per nest was 3.2. Predation accounted for 90% of failed nests. We found a positive association between daily nest survival and both nest height and distance of nest substrates from the nearest tree. Flycatchers that locate their nests higher above the ground and further from adjacent trees may be choosing the safest alternative because higher nests may be less exposed to terrestrial predators and nests in trees that are farther from other trees may be less exposed to arboreal predators such as jays (Corvidae) that may forage in patches with connected canopies. Nests in trees farther from other trees may also allow earlier detection of approaching predators and thus aid in nest defense.