scholarly journals Contributions of precipitation and temperature to the large scale geographic distribution of fleshy-fruited plant species: Growth form matters

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Yuan Zhao ◽  
Honglin Cao ◽  
Wubing Xu ◽  
Guoke Chen ◽  
Juyu Lian ◽  
...  
Keyword(s):  
Plant Species ◽  
Geographic Distribution ◽  
Large Scale ◽  
Growth Form ◽  
Precipitation And Temperature

scholarly journals A Digital Framework to Predict the Sunshine Requirements of Landscape Plants

2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang
Keyword(s):  
Solar Radiation ◽  
Plant Species ◽  
Large Scale ◽  
Normal Growth ◽  
Adaptive Selection ◽  
Landscape Plant ◽  
Landscape Plants ◽  
The Stability ◽  
Stability And Accuracy ◽  
The City

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.

scholarly journals Ecological Impacts of Megaprojects: Species Succession and Functional Composition

Plants ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2411
Author(s):  
Hamada E. Ali ◽  
Solveig Franziska Bucher
Keyword(s):  
Plant Species ◽  
Large Scale ◽  
Invasive Plant ◽  
Species Traits ◽  
Natural Vegetation ◽  
Ecological Impacts ◽  
Imperata Cylindrica ◽  
Dry Matter Content ◽  
Large Scale Disturbance ◽  
The Impact

Land-use changes have huge impacts on natural vegetation, especially megaprojects, as the vegetation layer is destroyed in the course of construction works affecting the plant community composition and functionality. This large-scale disturbance might be a gateway for the establishment of invasive plant species, which can outcompete the natural flora. In contrast, species occurring in the area before the construction are not able to re-establish. In this study, we analyzed the impact of a pipeline construction on a wetland nature reserve located in northern Egypt. Therefore, we analyzed the plant species occurrence and abundance and measured each plant species’ traits before the construction in 2017 as well as on multiple occasions up to 2 years after the construction had finished on altogether five sampling events. We found that the construction activity led to the establishment of an invasive species which previously did not occur in the area, namely, Imperata cylindrica, whereas five species (Ipomoea carnea, Pluchea dioscoridis, Polygonum equisetiforme, Tamarix nilotica, and Typha domingensis) could not re-establish after the disturbance. The functionality of ecosystems assessed via the analysis of plant functional traits (plant height, specific leaf area, and leaf dry matter content) changed within species over all sampling events and within the community showing a tendency to approximate pre-construction values. Functional dispersion and Rao’s quadratic diversity were higher after the megaproject than before. These findings are important to capture possible re-establishment and recovery of natural vegetation after construction and raise awareness to the impact of megaprojects, especially in areas which are high priority for conservation.

scholarly journals Effects of climate model radiation, humidity and wind estimates on hydrological simulations

2012 ◽  
Vol 16 (2) ◽  
pp. 305-318 ◽  
Author(s):  
I. Haddeland ◽  
J. Heinke ◽  
F. Voß ◽  
S. Eisner ◽  
C. Chen ◽  
...  
Keyword(s):  
Bias Correction ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Correction Method ◽  
Hydrological Models ◽  
Temperature And Precipitation ◽  
Effects Of Radiation ◽  
Precipitation And Temperature

Abstract. Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.

The effects of growth form on the impact of companion planting of nectar-producing plant species with Sedum album for extensive green roofs

2020 ◽  
Vol 56 ◽  
pp. 126875
Author(s):  
Tatsuya Matsuoka ◽  
Kazuaki Tsuchiya ◽  
Susumu Yamada ◽  
Jeremy Lundholm ◽  
Toshiya Okuro
Keyword(s):  
Plant Species ◽  
Growth Form ◽  
Green Roofs ◽  
The Impact ◽  
Extensive Green Roofs

Geographic Ranges of Plant Species in Relation to Dispersal Morphology, Growth Form and Diaspore Weight

1993 ◽  
Vol 20 (5) ◽  
pp. 563 ◽  
Author(s):  
Meri O Akwood ◽  
Enrique Jurado ◽  
Michelle Leishman ◽  
Mark Westoby
Keyword(s):  
Plant Species ◽  
Growth Form ◽  
Geographic Ranges

Linguistic levelling in Spanish: The analogical strong preterites

2010 ◽  
Vol 55 (2) ◽  
pp. 209-225
Author(s):  
Enrique Pato
Keyword(s):  
Geographic Distribution ◽  
Large Scale ◽  
Data Sources ◽  
Person Plural ◽  
Third Person ◽  
Corpus Data ◽  
Peninsular Spanish

AbstractCertain Peninsular Spanish varieties have two third-person plural forms in the simple past indicative of verbs with ‘strong’ (stem-stressed) preterites. While this phenomenon is documented in large-scale linguistic atlas surveys, its current geographic distribution and diachronic origins remain under-studied. This paper sets out to: 1) establish the geographic distribution of these variants; the differing methodologies and epochs of the data sources make them particularly interesting to compare, showing that these analogical strong preterites have suffered a drastic decline over the last century; 2) use historical corpus data to show that the vernacular variant is by no means a recent phenomenon; 3) examine external history as a source of explanation in linguistic reconstruction, showing that this process of analogical levelling took place after the reconquest and resettlement of these regions. These findings support the hypothesis of a feature which spread over the centuries by linguistic diffusion.

scholarly journals Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

2016 ◽  
Vol 12 (3) ◽  
pp. 635-662 ◽  
Author(s):  
Laurie Caillouet ◽  
Jean-Philippe Vidal ◽  
Eric Sauquet ◽  
Benjamin Graff
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
High Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Precipitation Forecast ◽  
Seasonal Temperature ◽  
Downscaling Method ◽  
Quantitative Precipitation Forecast ◽  
Precipitation And Temperature

Abstract. This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. The probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.

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