A.G. Toxopeus

Tracing glacial refugia of Triturus newts based on mitochondrial DNA phylogeography and species distribution modeling

IntroductionThe major climatic oscillations during the Quaternary Ice Age heavily influenced the distribution of species and left their mark on intraspecific genetic diversity. Past range shifts can be reconstructed with the aid of species distribution modeling and phylogeographical analyses. We test the responses of the different members of the genus Triturus (i.e. the marbled and crested newts) as the climate shifted from the previous glacial period (the Last Glacial Maximum, ~21 Ka) to the current interglacial.ResultsWe present the results of a dense mitochondrial DNA phylogeography (visualizing genetic diversity within and divergence among populations) and species distribution modeling (using two different climate simulations) for the nine Triturus species on composite maps.ConclusionsThe combined use of species distribution modeling and mitochondrial phylogeography provides insight in the glacial contraction and postglacial expansion of Triturus. The combined use of the two independent techniques yields a more complete understanding of the historical biogeography of Triturus than both approaches would on their own. Triturus newts generally conform to the ‘southern richness and northern purity’ paradigm, but we also find more intricate patterns, such as the absence of genetic variation and suitable area at the Last Glacial Maximum (T. dobrogicus), an ‘extra-Mediterranean’ refugium in the Carpathian Basin (T. cristatus), and areas where species displaced one another postglacially (e.g. T. macedonicus and western T. karelinii). We provide a biogeographical scenario for Triturus, showing the positions of glacial refugia, the regions that were postglacially colonized and the areas where species displaced one another as they shifted their ranges.

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area.

GIANT PANDA HABITAT SELECTION IN FOPING NATURE RESERVE, CHINA

Abstract Little is known about habitat selection of the giant panda (Ailuropoda melanoleuca), especially about the relationship between giant panda presence and bamboo and tree structures. We presented data on giant panda habitat use and selection in Foping Nature Reserve (NR), China. We used 1,066 radiotracking locations for 6 collared individuals to analyze giant panda habitat selection, and we used 110 plots to reveal the structure of giant panda habitat and its relationship with giant panda presence. We found that (1) giant pandas in Foping NR selected mostly 3 habitats: conifer forest, deciduous broadleaf forest, and Fargesia bamboo groves. (2) In winter, giant pandas selected deciduous broadleaf forest within elevations of 1,600 to 1,800 m with a south-facing slope of 10 to 20 degrees. In summer, giant pandas selected conifer forest within elevations of 2,400 to 2,600 m and a slope of 20 to 30 degrees. (3) Giant pandas selected the Bashaina fargesii bamboo area with short and dense culms in winter, while they selected the Fargesia qinlingensis bamboo area with a high coverage of tall and thick culms in summer. We concluded that giant pandas in Foping NR do select their preferred habitats. These findings may be used to guide the human activities in the reserve with consideration of giant panda habitat conditions.

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p < 0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p < 0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.

Migratory herbivorous waterfowl track satellite-derived green wave index

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008–2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40–60%), while the Greenland geese followed an earlier stage (GWI 20–40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

Understory bamboo discrimination using a winter image

In this study, a new approach is presented that combines forest phenology and Landsat vegetation indices to estimate evergreen understory bamboo coverage in a mixed temperate forest. It was found that vegetation indices, especially the normalized difference vegetation index (NDVI) derived from leaf-off (winter) images were significantly correlated with percent understory bamboo cover for both deciduous and mixed coniferous/deciduous forests. Winter NDVI was used to map bamboo coverage using a binary decision tree classifier. A high mapping accuracy for understory bamboo presence/absence was achieved with an overall accuracy of 89 percent ( k5 0.59). In addition, for the first time, we successfully classified three density classes of bamboo with an overall accuracy of 68 percent ( k5 0.48). These results were compared to three traditional multispectral bandsbased methods (Mahalanobis distance, maximum likelihood, and artificial neural networks). The highest mapping accuracy was again obtained from winter images. However, the kappa z-test showed that there was no statistical difference in accuracy between the methods. The results suggest that winter is the optimal season for quantifying the coverage of evergreen understory bamboos in a mixed forest area, regardless of the classification methods use.

Corresponding Mitochondrial DNA and Niche Divergence for Crested Newt Candidate Species

Genetic divergence of mitochondrial DNA does not necessarily correspond to reproductive isolation. However, if mitochondrial DNA lineages occupy separate segments of environmental space, this supports the notion of their evolutionary independence. We explore niche differentiation among three candidate species of crested newt (characterized by distinct mitochondrial DNA lineages) and interpret the results in the light of differences observed for recognized crested newt species. We quantify niche differences among all crested newt (candidate) species and test hypotheses regarding niche evolution, employing two ordination techniques (PCA-env and ENFA). Niche equivalency is rejected: all (candidate) species are found to occupy significantly different segments of environmental space. Furthermore, niche overlap values for the three candidate species are not significantly higher than those for the recognized species. As the three candidate crested newt species are, not only in terms of mitochondrial DNA genetic divergence, but also ecologically speaking, as diverged as the recognized crested newt species, our findings are in line with the hypothesis that they represent cryptic species. We address potential pitfalls of our methodology.

Using Poaching Levels and Elephant Distribution to Assess the Conservation Efficacy of Private, Communal and Government Land in Northern Kenya

Efforts to curb elephant poaching have focused on reducing demand, confiscating ivory and boosting security patrols in elephant range. Where land is under multiple uses and ownership, determining the local poaching dynamics is important for identifying successful conservation models. Using 2,403 verified elephant, Loxodonta africana, mortality records collected from 2002 to 2012 and the results of aerial total counts of elephants conducted in 2002, 2008 and 2012 for the Laikipia-Samburu ecosystem of northern Kenya, we sought to determine the influence of land ownership and use on diurnal elephant distribution and on poaching levels. We show that the annual proportions of illegally killed (i.e., poached) elephants increased over the 11 years of the study, peaking at 70% of all recorded deaths in 2012. The type of land use was more strongly related to levels of poaching than was the type of ownership. Private ranches, comprising only 13% of land area, hosted almost half of the elephant population and had significantly lower levels of poaching than other land use types except for the officially designated national reserves (covering only 1.6% of elephant range in the ecosystem). Communal grazing lands hosted significantly fewer elephants than expected, but community areas set aside for wildlife demonstrated significantly higher numbers of elephants and lower illegal killing levels relative to non-designated community lands. While private lands had lower illegal killing levels than community conservancies, the success of the latter relative to other community-held lands shows the importance of this model of land use for conservation. This work highlights the relationship between illegal killing and various land ownership and use models, which can help focus anti-poaching activities.

Change detection in animal movement using discrete wavelet analysis

Abstract Animals moving through a complex environment change their movement patterns frequently. Such transitions from one movement behavior to another are a result of multiple factors such as weather, habitat and inter-specific interactions occurring either individually or in tandem. Understanding where and when these changes occur is the first step towards understanding the limiting or key factors acting at different scales. We applied discrete wavelet analysis to find change points in the movement behavior of a Lesser Black-backed gull ( Larus fuscus ). We compared our results with results from the residence method proposed by Barraquand and Benhamou (2008) and the statistical method proposed by Lavielle (1999, 2005). Discrete wavelet analysis allows the identification and localization of change points by decomposing the frequency content of two time series consisting of step length and residence time data, while omitting the problem of redundancy of coefficients consistent with continuous wavelet transformation of movement data. We show that the novel use of discrete wavelet analysis in animal movement studies is widely applicable on different focus variables, allowing changes in the movement behavior and precise change points to be detected.

Environmental parameters linked to the last migratory stage of barnacle geese en route to their breeding sites

The migration timing of birds can be controlled by endogenous parameters. However, little is known about how environmental parameters influence the timing of migration and which have the greatest influence at different stages of migration. In this study we identified the main environmental parameters that correlate with the timing of the last stage of spring migration for the barnacle goose, Branta leucopsis. GPS tracking data were registered for 12 barnacle geese (in 2008–2010) on the Russian flyway and 17 (2006–2010) on the Svalbard flyway. A linear mixed-effect model and principal component analysis were used to retrieve statistically significant parameters. Departure date from the last staging site on the Russian flyway was related to daylength, temperature, cloud cover and barometric pressure, and on the Svalbard flyway to a food availability index and daylength. Arrival date at the Russian breeding site was related to cloud cover and barometric pressure en route and the food availability index and temperature at the breeding site. For the Svalbard flyway, temperature and cloud cover en route and the food availability index, wind, temperature and cloud cover at the breeding site were significantly related to arrival date at the breeding site. Our study highlights the importance of environmental parameters including food, weather and daylength for the last stage of goose spring migration. We found different priorities in selecting the environmental parameters in migration timing decisions between Svalbard and Russian barnacle geese which fly over sea and over land, respectively. Identifying the key factors that act as cues during the final stages of spring migration is important when assessing the possible effects of climate change on the timing of migration for a highly selective herbivore such as the barnacle goose.