Changes in fine-scale movement and foraging patterns of common wombats along a snow-depth gradient

2010 ◽  
Vol 37 (3) ◽  
pp. 175 ◽  
Author(s):  
Alison Matthews

Context. Feeding strategies of large herbivores in snow-covered environments can be influenced by snow depth and snow quality. Common wombats, Vombatus ursinus, are large marsupial herbivores that occur in subalpine areas of Australia where they must dig through the snow to reach low vegetation. Deeper snow at higher elevations is considered to limit foraging and constrain their range, although there have been no quantitative studies investigating the influence of snow on their foraging behaviour. Aims. The present study examined how snow influenced the foraging behaviour of common wombats along a snow-depth gradient. Methods. During the 2008 winter season, snow tracks of 17 wombats were located within the subalpine zone, in a study area ranging from 1520 to 1850 m asl, and followed to record attributes of the snow cover and environment in relation to wombat activity. Key results. Wombats selected sites to feed where the snow was shallower, and deeper snow at feeding sites caused changes in foraging behaviour. Foraging occurred along fairly direct routes between burrows; however, as snow depth increased, wombats deviated more from their path to seek out suitable foraging sites. Most foraging occurred in shallow snow in open areas or where the snow had melted around the bases of trees, shrubs or boulders. About half (52%) of the feeding sites necessitated the wombats digging through the snow to reach low vegetation, predominantly the grasses of Poa spp. Digging craters for feeding occurred in snow depths up to 100 cm, although depths less than 35 cm were preferred. Some shrub species, such as dusty daisy bush, Olearia phlogopappa, that protruded from the snow, were also eaten where the snow was deeper. Dietary analysis confirmed that monocots made up the majority of the diet (93.3%), although some individuals consumed up to 26% dicots. Conclusions. The present study demonstrated that wombats can adjust to a snow-covered environment by altering both their foraging patterns and diet as snow depth increases. However, they will be limited where snow depths are consistently greater than 100 cm. Implications. Under future climate-change scenarios of declining snow cover, wombats may be able to forage and inhabit higher altitudes than where they currently occur, and this has implications for the grazing-sensitive alpine ecosystem. Predicting shifts in the range of other herbivores to higher altitudes will require knowledge of their species-specific foraging thresholds in snow, such as presented in this study.

2021 ◽  
Vol 28 ◽  
pp. 138-152
Author(s):  
Pawel Jan Kolano ◽  
Malin Røyset Aarønes ◽  
Katrine Borgå ◽  
Anders Nielsen

Pollinating insects are an inherent part of most terrestrial ecosystems as they provide a crucial service for most angiosperms, including numerous important crops. A decrease in pollinator populations can therefore have severe consequences for both natural ecosystems and agricultural yields. Pesticide usage has been pointed out as one of the drivers behind pollinator declines. Globally, neonicotinoids are one of the most commonly used insecticides and studies have shown that exposure at sub-lethal levels can alter foraging behaviour, ultimately negatively affecting survival.Using a custom-made bumblebee colony monitoring system, we examined how the number and duration of foraging bouts of bumblebees (Bombus terrestris) on an individual level, and hive growth rate, was affected by exposure to low (6.5 µg/L) and high (10.6 µg/L) sub-lethal concentrations of the neonicotinoid clothianidin via nectar. We also examined possible interaction between clothianidin exposure and abiotic factors (temperature and precipitation), and its impact on foraging bout number and duration.Exposure to sublethal concentrations of clothianidin increased foraging bout duration in bumblebees. Furthermore, the foraging bout duration decreased with increasing temperature at both exposure concentrations, whereas the unexposed control group was not affected by temperature. Neither number of foraging bouts nor the daily rhythm of foraging bout duration was affected by clothianidin exposure or temperature. The foraging bout duration decreased with increasing precipitation in both exposed and non-exposed groups. However, we did not find any interaction between precipitation and exposure, suggesting that precipitation does not affect toxicity.Our study shows the importance of semi-natural experiments and accounting for ambient factors when assessing the risk that pesticide exposure may present to pollinators. We conclude that the effect of clothianidin exposure on bumblebee foraging behaviour is temperature sensitive and that local climatic conditions and future climate change scenarios should be considered in risk assessments of clothianidin and other insecticides. 


2020 ◽  
Author(s):  
David Pulido-Velazquez ◽  
Antonio-Juan Collados-Lara ◽  
Eulogio Pardo-Igúzquiza

<p>Climate change will modify the availability of snow resources in the future. Thus developing methodologies to assess impacts of potential future climate change scenarios on snow variables is a key subject. In this work we combine several previous developed methodologies (downscaling climate change scenarios to local scale, cellular automata models, and stochastic weather generators) to assess impacts of future climate change scenarios and its uncertainty on snow cover area through a Montecarlo simulation. The cellular automata model uses climatic indices (precipitation and temperature) as driving variables to estimate snow cover area. Future scenarios of these variables can be generated using bias correction and delta change approaches and different regional climate models. The stochastic weather generators allow us to produce multiple series of precipitation and temperature based on the statistical characteristics of the future local scenarios generated. These multiple series can be used as inputs of the cellular automata model in order to assess the future snow cover area and its uncertainty. The main advantages of the proposed methodology are its applicability in cases with limited information and in mountain ranges scales. The methodology has been applied to the Sierra Nevada mountain range in southern Spain. This area has a Mediterranean climate very sensitive to climate change. Using the future precipitation and temperature scenarios generated considering the Representative Concentration Pathways 8.5 (RCP8.5) for the period 2071–2100, we obtain a significant reduction in snow cover area, with mean values of 59.0% for the local scenarios generated with a delta change approach, and 61.7% for those one generated with the bias correction approach.</p><p>This research has been partially supported by the SIGLO-AN project (RTI2018-101397-B-I00) from the Spanish Ministry of Science, Innovation and Universities (Programa Estatal de I+D+I orientada a los Retos de la Sociedad).</p>


2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.


2021 ◽  
Vol 165 (3-4) ◽  
Author(s):  
Maria Vorkauf ◽  
Christoph Marty ◽  
Ansgar Kahmen ◽  
Erika Hiltbrunner

AbstractThe start of the growing season for alpine plants is primarily determined by the date of snowmelt. We analysed time series of snow depth at 23 manually operated and 15 automatic (IMIS) stations between 1055 and 2555 m asl in the Swiss Central Alps. Between 1958 and 2019, snowmelt dates occurred 2.8 ± 1.3 days earlier in the year per decade, with a strong shift towards earlier snowmelt dates during the late 1980s and early 1990s, but non-significant trends thereafter. Snowmelt dates at high-elevation automatic stations strongly correlated with snowmelt dates at lower-elevation manual stations. At all elevations, snowmelt dates strongly depended on spring air temperatures. More specifically, 44% of the variance in snowmelt dates was explained by the first day when a three-week running mean of daily air temperatures passed a 5 °C threshold. The mean winter snow depth accounted for 30% of the variance. We adopted the effects of air temperature and snowpack height to Swiss climate change scenarios to explore likely snowmelt trends throughout the twenty-first century. Under a high-emission scenario (RCP8.5), we simulated snowmelt dates to advance by 6 days per decade by the end of the century. By then, snowmelt dates could occur one month earlier than during the reference periods (1990–2019 and 2000–2019). Such early snowmelt may extend the alpine growing season by one third of its current duration while exposing alpine plants to shorter daylengths and adding a higher risk of freezing damage.


2021 ◽  
Vol 9 (4) ◽  
pp. 862
Author(s):  
Vittoria Catara ◽  
Jaime Cubero ◽  
Joël F. Pothier ◽  
Eran Bosis ◽  
Claude Bragard ◽  
...  

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.


Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2101
Author(s):  
Christian Charron ◽  
André St-Hilaire ◽  
Taha B.M.J. Ouarda ◽  
Michael R. van den Heuvel

Simulation of surface water flow and temperature under a non-stationary, anthropogenically impacted climate is critical for water resource decision makers, especially in the context of environmental flow determination. Two climate change scenarios were employed to predict streamflow and temperature: RCP 8.5, the most pessimistic with regards to climate change, and RCP 4.5, a more optimistic scenario where greenhouse gas emissions peak in 2040. Two periods, 2018–2050 and 2051–2100, were also evaluated. In Canada, a number of modelling studies have shown that many regions will likely be faced with higher winter flow and lower summer flows. The CEQUEAU hydrological and water temperature model was calibrated and validated for the Wilmot River, Canada, using historic data for flow and temperature. Total annual precipitation in the region was found to remain stable under RCP 4.5 and increase over time under RCP 8.5. Median stream flow was expected to increase over present levels in the low flow months of August and September. However, increased climate variability led to higher numbers of periodic extreme low flow events and little change to the frequency of extreme high flow events. The effective increase in water temperature was four-fold greater in winter with an approximate mean difference of 4 °C, while the change was only 1 °C in summer. Overall implications for native coldwater fishes and water abstraction are not severe, except for the potential for more variability, and hence periodic extreme low flow/high temperature events.


Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.


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