scholarly journals Main environmental variables influencing the abundance of plant species under risk category

2021 ◽  
Author(s):  
Pablo Antúnez
Keyword(s):  
Plant Species ◽  
National Level ◽  
Principal Component ◽  
Summer Precipitation ◽  
Growing Season ◽  
Maximum Temperature ◽  
Tropical Species ◽  
Risk Category ◽  
Spring Precipitation ◽  
Different Seasons

AbstractDetermining climatic and physiographic variables in Mexico's major ecoregions that are limiting to biodiversity and species of high conservation concern is essential for their conservation. Yet, at the national level to date, few studies have been performed with large data sets and cross-confirmation using multiple statistical analyses. Here, we used 25 endemic, rare and endangered species from 3610 sampling points throughout Mexico and 25 environmental attributes, including average precipitation for different seasons of the year, annual dryness index, slope of the terrain; and maximum, minimum and average temperatures to test our hypothesis that these species could be assessed with the same weight among all variables, showing similar indices of importance. Our results using principal component analysis, covariation analysis by permutations, and random forest regression showed that summer precipitation, length of the frost-free period, spring precipitation, winter precipitation and growing season precipitation all strongly influence the abundance of tropical species. In contrast, annual precipitation and the balance at different seasons (summer and growing season) were the most relevant variables on the temperate region species. For dry areas, the minimum temperature of the coldest month and the maximum temperature of the warmest month were the most significant variables. Using these different associations in different climatic regions could support a more precise management and conservation plan for the preservation of plant species diversity in forests under different global warming scenarios.

scholarly journals Scots Pine (pinus sylvestris L.) on Shingle Fields: A Dendrochronologic Reconstruction of Early Summer Precipitation in Mideast Sweden

2009 ◽  
Vol 22 (17) ◽  
pp. 4710-4722 ◽  
Author(s):  
Karin Jönsson ◽  
Christer Nilsson
Keyword(s):  
Pinus Sylvestris ◽  
Tree Ring ◽  
Scots Pine ◽  
Principal Component ◽  
Summer Precipitation ◽  
Early Summer ◽  
Climate Data ◽  
Spring Precipitation ◽  
Dead Trees ◽  
Pine Trees

Abstract Scots pine (Pinus sylvestris L.) trees growing on shingle fields offer a unique possibility to reconstruct precipitation and study climate variability in the fairly humid eastern part of central Sweden. Tree-ring characteristics were compared with monthly (1890–2001) and daily (1961–2001) climate data from an adjacent meteorological station. Chronologies for latewood (LW), earlywood (EW), and tree-ring widths (RW) were constructed from 73 living and dead trees. Correlation analyses show that tree growth is most sensitive to early summer precipitation. EW shows the strongest correlation with precipitation in May and June while LW is best correlated with June and July precipitation. A reconstruction model for May–June precipitation was calculated using principal component analysis (PCA) regression (regular regression) including EW, LW, and RW for present and previous years. The model explained 46% of the variation in May–June precipitation and allowed a reconstruction back to 1560. Information about wet and dry years was collected from historical documents and was used to validate the result. Periods with precipitation above and below the mean show agreement with previous reconstructions of spring precipitation from tree rings in Finland and of spring floods from estuary sediments in the region. Analyses of correlations between meteorological stations and reconstructed precipitation show that the model is valid for the coastal part of central Sweden. The authors conclude that Scots pine trees on shingle fields are well suited for precipitation reconstruction, and the separate analyses of LW and EW improve the reconstruction.

scholarly journals Seed Set Patterns in East African Highland Cooking Bananas Are Dependent on Weather before, during and after Pollination

Horticulturae ◽  
2021 ◽  
Vol 7 (7) ◽  
pp. 165
Author(s):  
Allan Waniale ◽  
Rony Swennen ◽  
Settumba B. Mukasa ◽  
Arthur K. Tugume ◽  
Jerome Kubiriba ◽  
...  
Keyword(s):  
Critical Period ◽  
Floral Development ◽  
Seed Set ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Maximum Temperature ◽  
Fruit Pulp ◽  
East African ◽  
Average Temperature ◽  
Wild Banana

Seed set in banana is influenced by weather, yet the key weather attributes and the critical period of influence are unknown. We therefore investigated the influence of weather during floral development for a better perspective of seed set increase. Three East African highland cooking bananas (EAHBs) were pollinated with pollen fertile wild banana ‘Calcutta 4′. At full maturity, bunches were harvested, ripened, and seeds extracted from fruit pulp. Pearson’s correlation analysis was then conducted between seed set per 100 fruits per bunch and weather attributes at 15-day intervals from 105 days before pollination (DBP) to 120 days after pollination (DAP). Seed set was positively correlated with average temperature (P < 0.05–P < 0.001, r = 0.196–0.487) and negatively correlated with relative humidity (RH) (P < 0.05–P < 0.001, r = −0.158–−0.438) between 75 DBP and the time of pollination. After pollination, average temperature was negatively correlated with seed set in ‘Mshale’ and ‘Nshonowa’ from 45 to 120 DAP (P < 0.05–P < 0.001, r = −0.213–−0.340). Correlation coefficients were highest at 15 DBP for ‘Mshale’ and ‘Nshonowa’, whereas for ‘Enzirabahima’, the highest were at the time of pollination. Maximum temperature as revealed by principal component analysis at the time of pollination should be the main focus for seed set increase.

scholarly journals Sensory Profile of Chihuahua Cheese Manufactured from Raw Milk

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Sarai Villalobos-Chaparro ◽  
Erika Salas-Muñóz ◽  
Néstor Gutiérrez-Méndez ◽  
Guadalupe Virginia Nevárez-Moorillón
Keyword(s):  
Principal Component Analysis ◽  
Geographical Location ◽  
Principal Component ◽  
Raw Milk ◽  
Component Analysis ◽  
Sensory Profile ◽  
Different Seasons ◽  
Quantitative Descriptive ◽  
Traditional Manufacturing ◽  
Chihuahua Cheese

Chihuahua cheese is a local artisanal cheese traditionally produced from raw milk. When this cheese is produced with pasteurized milk, cheesemakers complain that there are differences in taste and aroma as compared with traditional manufacturing. This work aimed to obtain a descriptive sensory analysis of Chihuahua cheese manufactured with raw milk under traditional conditions. Samples were collected in five cheese dairies at two different seasons (summer and autumn), and a Quantitative Descriptive Sensorial Analysis was done by a panel of trained judges. For aroma descriptors, cooked descriptor showed differences between dairies, and whey was different among dairies and sampling seasons (P<0.01); diacetyl, fruity (P<0.01), as well as free fatty acids, nutty and sulphur (P<0.05) descriptors varied between seasons. For flavour descriptors, bitter perception was different between dairies and seasons (P<0.01). Salty and creamy cheese was also different among dairies (P<0.01). A Principal Component Analysis for differences among dairies and sampling season demonstrated that the first three components accounted for 90% of the variance; variables were more affected by the sampling seasons than by the geographical location or if the dairy was operated by Mennonites. Chihuahua cheese sensorial profile can be described as a semi-matured cheese with a bitter flavour, slightly salted, and with a cream flavour, with aroma notes associated with whey and sour milk. Principal Component Analysis demonstrated season influence on flavour and aroma characteristics.

scholarly journals Relationships between Southeast Australian Temperature Anomalies and Large-Scale Climate Drivers

2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Warm Season ◽  
Principal Component ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Past Century ◽  
Tasman Sea ◽  
Australian Continent

Abstract Over the past century, particularly after the 1960s, observations of mean maximum temperatures reveal an increasing trend over the southeastern quadrant of the Australian continent. Correlation analysis of seasonally averaged mean maximum temperature anomaly data for the period 1958–2012 is carried out for a representative group of 10 stations in southeast Australia (SEAUS). For the warm season (November–April) there is a positive relationship with the El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) and an inverse relationship with the Antarctic Oscillation (AAO) for most stations. For the cool season (May–October), most stations exhibit similar relationships with the AAO, positive correlations with the dipole mode index (DMI), and marginal inverse relationships with the Southern Oscillation index (SOI) and the PDO. However, for both seasons, the blocking index (BI, as defined by M. Pook and T. Gibson) in the Tasman Sea (160°E) clearly is the dominant climate mode affecting maximum temperature variability in SEAUS with negative correlations in the range from r = −0.30 to −0.65. These strong negative correlations arise from the usual definition of BI, which is positive when blocking high pressure systems occur over the Tasman Sea (near 45°S, 160°E), favoring the advection of modified cooler, higher-latitude maritime air over SEAUS. A point-by-point correlation with global sea surface temperatures (SSTs), principal component analysis, and wavelet power spectra support the relationships with ENSO and DMI. Notably, the analysis reveals that the maximum temperature variability of one group of stations is explained primarily by local factors (warmer near-coastal SSTs), rather than teleconnections with large-scale drivers.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

Development and validation of a scale to measure the resilience of schools: Perspectives of young people from vulnerable and challenging territories

2021 ◽  
pp. 136548022199174
Author(s):  
Ana Milheiro Silva ◽  
Sofia Marques da Silva
Keyword(s):  
Young People ◽  
National Level ◽  
Principal Component ◽  
Border Regions ◽  
Educational Pathways ◽  
Resilience Scale ◽  
12Th Grade ◽  
Confirmatory Factor ◽  
Territorial Disparities ◽  
Development And Validation

This article presents the development and validation of a scale for young people, which measures the resilience of schools in ensuring the educational pathways of students in vulnerable and challenging territories. This scale was developed within a national-level project, conducted in Portuguese border regions with Spain, which are peripheral contexts with economic, social, cultural, and educational disadvantages, but with locally-situated promising dynamics. Resilient schools, from an ecological perspective, are sensitive and committed to their internal and external settings. These schools act as a whole to face problem solving and risk situations, while also needing to support youth educational pathways and fulfill their role. This is particularly important in contexts with territorial disparities and specificities, as is the case of border regions. The Resilience Scale of Schools – Youth Version (RSS-Y) integrates dimensions related to schools’ focus and priorities, as well as practices and resources. Its development took into consideration that schools in vulnerable territories deal with specific constraints and fewer opportunities. In addition, this scale seeks to study the characteristics of resilience that young people identify in their schools and how they perceive their schools’ support. This quantitative scale was developed following a multi-step approach and was applied to 3,968 young people (9th to 12th grade). It comprises 17 items, rated on a five-point Likert scale to assess agreement. Statistical analysis ensure the internal consistency (Factor 1, α = .846; Factor 2, α = .845; Factor 3, α = .789) and the validity of this scale, indicating adequate psychometric properties to measure students’ perspectives on the resilience characteristics of schools. A Principal Component Analysis (PCA) proposes a three-factor structure that explains 57.393% of the total variance. A Confirmatory Factor Analysis (CFA) indicates that this model is a good fit with the data. The RSS-Y can provide an important contribution to educational research developed in more deprived territories, but also to school contexts, since it recognizes the importance of schools’ differentiated approaches and highlights characteristics that promote the resilience and quality of schools.

scholarly journals Understanding Land-Atmosphere-Climate Coupling from the Canadian Prairie Dataset

2018 ◽  
Author(s):  
Alan K Betts ◽  
Raymond L Desjardins
Keyword(s):  
Snow Cover ◽  
Diurnal Cycle ◽  
Radiative Forcing ◽  
Potential Temperature ◽  
Warm Season ◽  
Growing Season ◽  
Cold Season ◽  
Maximum Temperature ◽  
Canadian Prairie ◽  
Cloud Forcing

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land-atmosphere-cloud coupling. The key reason is that trained observers made hourly estimates of opaque cloud fraction that obscures the sun, moon or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality that they can be calibrated against Baseline Surface Radiation Network data to give the climatology of the daily short-wave, longwave and total cloud forcing (SWCF, LWCF and CF). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing reverses sign from negative in the warm season to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10&deg;C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature and the pressure height of the lifting condensation level are all tightly coupled to opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between cloud forcing and the warm season imbalance of the diurnal cycle; which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forci, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of mixing ratio which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season and its dependence on reflective cloud.

scholarly journals Different Wood Anatomical and Growth Responses in European Beech (Fagus sylvatica L.) at Three Forest Sites in Slovenia

2021 ◽  
Vol 12 ◽  
Author(s):  
Domen Arnič ◽  
Jožica Gričar ◽  
Jernej Jevšenak ◽  
Gregor Božič ◽  
Georg von Arx ◽  
...  
Keyword(s):  
Tree Ring ◽  
Climatic Factors ◽  
Ring Width ◽  
European Beech ◽  
Growing Season ◽  
Climatic Conditions ◽  
Maximum Temperature ◽  
Tree Ring Width ◽  
Vessel Area ◽  
Temperature And Precipitation

European beech (Fagus sylvatica L.) adapts to local growing conditions to enhance its performance. In response to variations in climatic conditions, beech trees adjust leaf phenology, cambial phenology, and wood formation patterns, which result in different tree-ring widths (TRWs) and wood anatomy. Chronologies of tree ring width and vessel features [i.e., mean vessel area (MVA), vessel density (VD), and relative conductive area (RCTA)] were produced for the 1960–2016 period for three sites that differ in climatic regimes and spring leaf phenology (two early- and one late-flushing populations). These data were used to investigate long-term relationships between climatic conditions and anatomical features of four quarters of tree-rings at annual and intra-annual scales. In addition, we investigated how TRW and vessel features adjust in response to extreme weather events (i.e., summer drought). We found significant differences in TRW, VD, and RCTA among the selected sites. Precipitation and maximum temperature before and during the growing season were the most important climatic factors affecting TRW and vessel characteristics. We confirmed differences in climate-growth relationships between the selected sites, late flushing beech population at Idrija showing the least pronounced response to climate. MVA was the only vessel trait that showed no relationship with TRW or other vessel features. The relationship between MVA and climatic factors evaluated at intra-annual scale indicated that vessel area in the first quarter of tree-ring were mainly influenced by climatic conditions in the previous growing season, while vessel area in the second to fourth quarters of tree ring width was mainly influenced by maximum temperature and precipitation in the current growing season. When comparing wet and dry years, beech from all sites showed a similar response, with reduced TRW and changes in intra-annual variation in vessel area. Our findings suggest that changes in temperature and precipitation regimes as predicted by most climate change scenarios will affect tree-ring increments and wood structure in beech, yet the response between sites or populations may differ.

scholarly journals What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages?

2018 ◽  
Vol 35 ◽  
pp. 1-12
Author(s):  
Cynthia Diniz Souza ◽  
Vandick S. Batista ◽  
Nidia Noemi Fabré
Keyword(s):  
Wind Speed ◽  
Rainy Season ◽  
Fish Assemblages ◽  
Principal Component ◽  
Dry Season ◽  
Community Diversity ◽  
Tropical Species ◽  
Coastal Fish ◽  
Wide Range ◽  
Diversity Profiles

Seasonal ecological effects caused by temperature and photoperiod are typically considered minimal in the tropics. Nevertheless, annual climate cycles may still influence the distribution and abundance of tropical species. Here, we investigate whether seasonal patterns of precipitation and wind speed influence the structure of coastal fish assemblages and fishing yields in northeast Brazil. Research trips were conducted during the rainy and dry seasons using commercial boats and gear to sample the fish community. Diversity was analyzed using abundance Whittaker curves, diversity profiles and the Shannon index. Principal Component Analysis (PCA) was used to analyze associations between the abundance of species and various environmental variables related to seasonality. A total of 2,373 fish were collected, representing 73 species from 34 families – 20 of which were classified as both frequent and abundant. Species richness was greater and more equitable during the rainy season than the dry season – driven by changes in the precipitation rather than to wind speed. Species diversity profiles were slightly greater during the rainy season than the dry season, but this difference was not statistically significant. Using PCA was identified three groups of species: the first associated with wind speed, the second with precipitation, and the third with a wide range of sampling environments. This latter group was the largest and most ecologically heterogeneous. We conclude that tropical coastal fish assemblages are largely influenced by local variables, and seasonally mediated by annual changes related to precipitation intensity and wind speed, which in turn influences fishery yields.

Phylogenetic relationships among species of Ganoderma (Ganodermataceae, Basidiomycota) from Cameroon

2012 ◽  
Vol 60 (6) ◽  
pp. 526 ◽  
Author(s):  
T. R. Kinge ◽  
A. M. Mih ◽  
M. P. A. Coetzee
Keyword(s):  
Plant Species ◽  
Phylogenetic Relationships ◽  
Internal Transcribed Spacer ◽  
New Records ◽  
Small Subunit ◽  
Species Level ◽  
Molecular Techniques ◽  
Tropical Species ◽  
The Tropics

Ganoderma is an important genus of the Polyporales in the tropics. Identification of tropical species has mainly been based on morphology, which has led to misidentification. This study aimed to elucidate the diversity and phylogenetic relationships of Ganoderma isolates from different hosts in Cameroon using morphological and molecular techniques. Analyses of basidiocarp morphology and the internal transcribed spacer and mitochondria small subunit were undertaken for 28 isolates from five plant species. The results show that the isolates belong to eight species. Three of the species were identified to species level; of these only G. ryvardense has been previously described from Cameroon while G. cupreum and G. weberianum are new records. The five remaining species did not match with any previously described species and have been designated as Ganoderma with different species affinities.

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