scholarly journals The Influence of Environmental Change (Crops and Water) on Population Redistribution in Mexico and Ethiopia

2019 ◽  
Vol 9 (23) ◽  
pp. 5219 ◽  
Author(s):  
Haibin Xia ◽  
Susana B. Adamo ◽  
Alex de Sherbinin ◽  
Bryan Jones
Keyword(s):  
Environmental Change ◽  
Crop Yield ◽  
Crop Production ◽  
River Flow ◽  
Control Variable ◽  
Correlation Coefficients ◽  
Short Term ◽  
Population Redistribution ◽  
Environmental Shocks

This paper discusses the effects of long-term environmental change (represented by the abundance or scarcity relative to the long-term average level of crop yield/river flow) and short-term environmental shock (represented by the maximum number of consecutive years below the median crop yield/river flow per decade) on population redistribution in Mexico and Ethiopia. Crop production and water resources, which are affected by climate change and influence human survival and activities, were selected as research variables. Two developing countries, namely, Mexico and Ethiopia, were selected as comparison cases. The results showed that short-term environmental shocks had no correlation with population redistribution. Short-term environmental shocks might fail to influence migration decisions or cause only temporary displacements that cannot be detected by demographic statistics. Among the long-term environmental change factors, only crop yield deviation was found to have a significant positive correlation with population redistribution. Based on two different datasets and two different decades, crop yield deviation is positively correlated with population redistribution; the correlation coefficients between crop yield deviation and population redistribution were 0.134 to 0.162 in Mexico and 0.102 to 0.235 in Ethiopia. When urbanization was considered as the control variable, the correlation coefficient between crop yield deviation and population redistribution in Mexico dropped by half, while it was almost the same in Ethiopia. However, Ethiopia’s population redistribution was more clearly influenced by the population itself. Crop yield deviation relative to water flow deviation meant changes in livelihoods. Population redistribution is a possible means of adapting to changes in livelihood. Mexico exhibited high resilience to changes in livelihoods caused by long-term environmental change, especially in its densely populated areas. In contrast, Ethiopia was characterized mainly by high population growth and low population migration. People in some areas of Ethiopia were forced to endure hardship of livelihood deterioration or to stay where they were due to the difficulty of obtaining sufficient resources to afford the cost of migration.

scholarly journals Effects of Short-term Tillage of a Long-term No-Till Land on Crop Yield and Nutrient Uptake in Two Contrasting Soil Types

2016 ◽  
Vol 5 (3) ◽  
pp. 32 ◽  
Author(s):  
Miles Dyck ◽  
Sukhdev S. Malhi ◽  
Marvin Nyborg ◽  
Dyck Puurveen
Keyword(s):  
Nutrient Uptake ◽  
Crop Yield ◽  
Crop Production ◽  
N Uptake ◽  
P Uptake ◽  
N Fertilization ◽  
Short Term ◽  
Plant Yield ◽  
No Till

<p>Pre-seeding tillage of long-term no-till (NT) land may alter crop production by changing the availability of some nutrients in soil. Effects of short-term (4 years) tillage (hereafter called reverse tillage [RT]) of land previously under long-term (29 or 30 years) NT, with straw management (straw removed [SRem] and straw retained [SRet]) and N fertilizer rate (0, 50 and 100 kg N ha<sup>-1</sup> in SRet, and 0 kg N ha<sup>-1</sup> in SRem plots), were determined on plant yield (seed + straw, or harvested as forage/silage at soft dough stage), and N and P uptake in growing seasons from 2010 to 2013 at Breton (Gray Luvisol [Typic Cryoboralf] loam) and from 2009 to 2012 at Ellerslie (Black Chernozem [Albic Argicryoll] loam), Alberta, Canada. Plant yield, N uptake and P uptake tended to be greater with RT compared to NT in most cases at both sites, although significant in a few cases only at Ellerslie. On average over both sites, RT produced greater plant yield by 560 kg ha<sup>-1</sup> yr<sup>-1</sup>, N uptake by 5.8 kg N ha<sup>-1</sup> yr<sup>-1</sup>, and P uptake by 1.8 kg P ha<sup>-1</sup> yr<sup>-1</sup> than NT. There was no consistent beneficial effect of straw retention on plant yield, N uptake and P uptake in different years. Plant yield, N uptake and P uptake increased with N fertilization at both sites, with up to the maximum rate of applied N at 100 kg N ha<sup>-1</sup> in 3 of 4 years at Breton and in 2 of 4 years at Ellerslie. In conclusion, our findings suggested some beneficial impact of occasional tillage of long-term NT soil on crop yield and nutrient uptake.</p>

scholarly journals Capital Structure and Firm Performance: Evidence from Malaysian Public Listed Plantation Companies

2021 ◽  
Vol 5 (1) ◽  
pp. 123-142
Author(s):  
Kim Foong Jee ◽  
Jia En Joanne Ngui ◽  
Pei Pei Jessica Poh ◽  
Wai Loon Chan ◽  
Yet Siang Wong
Keyword(s):  
Firm Performance ◽  
Capital Structure ◽  
Significant Relationship ◽  
Firm Growth ◽  
Control Variable ◽  
Short Term ◽  
Total Debt ◽  
And Performance ◽  
The Impact

This paper examines the relationship between capital structure and performance of firms. The study is confined to plantation sector companies in Malaysia and is based on a sample of 39 firms which listed in Bursa Malaysia for the period from 2009 to 2019. This study uses two performance measures which are ROA and ROE as the dependent variable. Besides, the capital structure measures are the short-term debt, long-term debt, total debt and firm growth, which as the independent variables. Size will be the control variable in this study. Moreover, a fixed-effect panel regression analysis has been used to analyse the impact of capital structure on firm performance. The results indicate that firm performance, which is in term of ROA, have an insignificant relationship with short-term debt (STD) and long-term debt (LTD). For the total debt (TD) and growth, there is a significant relationship with ROA. However, for the performance measured by ROE, it has an insignificant relationship with short-term debt (STD), long-term debt (LTD) and total debt (TD). Furthermore, there is a significant relationship between the growth and the performance firms from plantation sector in Malaysia.

Techniques to Predict Agricultural Droughts

2005 ◽  
Author(s):  
Zekai Şen
Keyword(s):  
Crop Yield ◽  
Satellite Data ◽  
Wheat Yield ◽  
Weather Variables ◽  
Short Term ◽  
Yield Model ◽  
Regression Techniques ◽  
The Difference ◽  
Effects Of Drought

In general, the techniques to predict drought include statistical regression, time series, stochastic (or probabilistic), and, lately, pattern recognition techniques. All of these techniques require that a quantitative variable be identified to define drought, with which to begin the process of prediction. In the case of agricultural drought, such a variable can be the yield (production per unit area) of the major crop in a region (Kumar, 1998; Boken, 2000). The crop yield in a year can be compared with its long-term average, and drought intensity can be classified as nil, mild, moderate, severe, or disastrous, based on the difference between the current yield and the average yield. Regression techniques estimate crop yields using yield-affecting variables. A comprehensive list of possible variables that affect yield is provided in chapter 1. Usually, the weather variables routinely available for a historical period that significantly affect the yield are included in a regression analysis. Regression techniques using weather data during a growing season produce short-term estimates (e.g., Sakamoto, 1978; Idso et al., 1979; Slabbers and Dunin, 1981; Diaz et al., 1983; Cordery and Graham, 1989; Walker, 1989; Toure et al., 1995; Kumar, 1998). Various researchers in different parts of the world (see other chapters) have developed drought indices that can also be included along with the weather variables to estimate crop yield. For example, Boken and Shaykewich (2002) modifed the Western Canada Wheat Yield Model (Walker, 1989) drought index using daily temperature and precipitation data and advanced very high resolution radiometer (AVHRR) satellite data. The modified model improved the predictive power of the wheat yield model significantly. Some satellite data-based variables that can be used to predict crop yield are described in chapters 5, 6, 9, 13, 19, and 28. The short-term estimates are available just before or around harvest time. But many times long-term estimates are required to predict drought for next year, so that long-term planning for dealing with the effects of drought can be initiated in time.

Reliability and reproducibility of a clinical application of a simple technique for repeated circumferential leg measurements

2010 ◽  
Vol 26 (1) ◽  
pp. 14-19 ◽  
Author(s):  
A te Slaa ◽  
P Mulder ◽  
D Dolmans ◽  
P Castenmiller ◽  
G Ho ◽  
...  
Keyword(s):  
Simple Technique ◽  
Correlation Coefficients ◽  
Repeated Measurements ◽  
Medium Term ◽  
Short Term ◽  
Intra Class Correlation ◽  
Long Period ◽  
Simple Instrument ◽  
Reproducible Method

Objective The aim of this study is to determine the reliability and reproducibility of repeated tape measurements to assess the leg circumference during a long period. Methods A tape measure is a simple instrument that is applicable in the presence of oedema. Measurements were performed by four observers on 11 volunteers. Four measurements were done in the first week (short term), a fifth measurement at two weeks (medium term) and a sixth measurement was done at 12 weeks (long term). Results The short-, medium- and long-term intra-class correlation coefficients for repeated measurements were 0.90, 0.89 and 0.78, respectively. The short-term and long-term reproducibility indices equalled 4.4% and 6.5%. If only a single observer would be involved, the short-term intra-class correlation coefficients would improve to 0.94 (reproducibility index 3.3%). Conclusion Tape measurements have been proved to be a reliable and reproducible method to asses the lower limb circumference.

scholarly journals The influence of decadal-scale variability on trends in long European streamflow records

2013 ◽  
Vol 10 (2) ◽  
pp. 1859-1896 ◽  
Author(s):  
J. Hannaford ◽  
G. Buys ◽  
K. Stahl ◽  
L. M. Tallaksen
Keyword(s):  
Eastern Europe ◽  
River Flow ◽  
Interdecadal Variability ◽  
Trend Detection ◽  
Quality Data ◽  
Mean Flow ◽  
Short Term ◽  
Decadal Scale ◽  
Multi Temporal

Abstract. This study seeks to provide a long-term context for the growing number of trend analyses which have been applied to river flows in Europe. Most studies apply trend tests to fixed periods, in relatively short (generally 1960s–present) records. This study adopts an alternative "multi-temporal" approach, whereby trends are fitted to every possible combination of start and end years in a record. The method is applied to 132 catchments with long (1932–2004) hydrometric records from northern and central Europe, which were chosen as they are minimally anthropogenically influenced and have good quality data. The catchments are first clustered into five regions, which are broadly homogenous in terms of interdecadal variability of annual mean flow. The multi-temporal trend approach was then applied to regional time series of different hydrological indicators (annual, monthly and high and low flows). The results reveal that the magnitude and even direction of short-term trends are heavily influenced by interdecadal variability. Some short-term trends revealed in previous studies are shown to be unrepresentative of long-term change. For example, previous studies have identified post-1960 river flow decreases in southern and eastern Europe: in parts of eastern Europe, these trends are resilient to study period, extending back to the 1930s; in southern France, longer records show evidence of positive trends which reverse from the 1960s. Recent (post-1960) positive trends in northern Europe are also not present in longer records, due to decadal variations influenced by the North Atlantic Oscillation. The results provide a long-term reference for comparison with published and future studies. The multi-temporal approach advocated here is recommended for use in future trend assessments, to help contextualise short-term trends. Future work should also attempt to explain the decadal-scale variations that drive short-term trends, and thus develop more sophisticated methods for trend detection that take account of interdecadal variability and its drivers.

scholarly journals Misleading Aggregate Considerations in Sector-Specific Causalities: Long-term Bank Credit Usage in Fishing vs. Agriculture in Turkey

2019 ◽  
pp. 1-14
Author(s):  
Celal Demirkol ◽  
Ali Faruk Acikgoz
Keyword(s):  
Financial Analysis ◽  
Control Variable ◽  
Point Of View ◽  
Policy Implications ◽  
Bank Credit ◽  
Short Term ◽  
Alternative Source ◽  
Agriculture Sector ◽  
Fishing Sector

As an alternative source of financing the assets, bank credits have ever been on the spot of business finance and financial analysis. Those sources of financing have mostly compared with the short-term appearance of either liabilities or liquidity. The relevant finance literature ensures that the long-term appearance of bank credits in the balance sheets of businesses is not only affected by the composition of short-term liabilities but also the liquidity. Nevertheless, bank credit usage, especially in the long-term, may have different characteristics amongst sectors. Some sectors may even deserve a thorough analysis in their challenge of bank credit finance. The fishing sector and the businesses which it contains may have been neglected in terms of revealing the causalities which might have been hidden by considering its aspects as a supplement in the aggregate figures of the agriculture sector in Turkey. Thus, this study aims at the core debt and liability variables along with a liquidity control variable, cash and cash equivalents or cash, to reveal the causality and cointegration aspects on the long-term bank credit potential in the nexus of these two inter-related sectors. We hereby compare the results of the model designed for the study in between fishing and agriculture sectors in Turkey for the time span of available and comparable data which has been represented by the Central Bank of Turkey as a part of nonfinancial or real sector data from 1996 up to 2009. The findings depict that fishing sector, unlikely to agriculture sector in which it is generally added and forced to share the same investment atmosphere of incentives, policy implications, and attitudes of the creditors, does have different features in terms of long-term bank credit usage. Cash and cash equivalents are not significant regressors for the agriculture sector, however, fishing sector has evidence in the long-run that cash and cash equivalents have noteworthy impact in the long-term bank credits. The results of the study will therefore help both the decisions on the creditors’ and fishing sector sides enriching the profound details and sector specific reasoning for which an aggregate point of view where fishing sector is seen as a part of agriculture sector could not reflect the sector’s characteristics on the path to develop the fishing sector and the businesses therein. We also believe that this study will present evidence for any policies and incentives in promoting new investments in the fishing sector of Turkey.

scholarly journals Revisiting the effects of relevant factors on Pakistan's agricultural products export

2020 ◽  
Vol 66 (No. 12) ◽  
pp. 527-541
Author(s):  
Zaid Ashiq Khan ◽  
Mansoor Ahmed Koondhar ◽  
Noshaba Aziz ◽  
Uzair Ali ◽  
Liu Tianjun
Keyword(s):  
Error Correction ◽  
National Economy ◽  
Crop Production ◽  
Error Correction Model ◽  
Agricultural Products ◽  
Short Term ◽  
Correction Model ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

Pakistan is an agriculture-based country, so the agricultural sector is known as the backbone of the national economy. Considering the national economy and the agricultural industry, it is necessary to focus on earnings through agricultural products export to improve the livelihood of local farmers. Therefore, the current study aimed to analyse the short-term and long-term factors affecting agricultural products export. The annual time series of 1976–2016 were collected from World Bank indicators, the Food and Agriculture Organization, and the Statistical Bureau of Pakistan. An autoregressive distributed lag, along with a vector error correction model, was employed. A cointegration test showed long-term associations between the selected variables. While the autoregressive distributed lag model confirmed the short-term correlation between area sown and crop production towards agricultural products export, there is no long-term relationship between the selected variables. In addition, the bidirectional correlation between employment in agriculture and agricultural products export was confirmed by the vector error correction model. Therefore, it is essential to increase agricultural production with the available natural resources to increase foreign earnings.

scholarly journals How adaptive plasticity evolves when selected against

2018 ◽  
Author(s):  
Alfredo Rago ◽  
Kostas Kouvaris ◽  
Tobias Uller ◽  
Richard Watson
Keyword(s):  
Natural Selection ◽  
Environmental Change ◽  
Coarse Grained ◽  
Adaptive Plasticity ◽  
Short Term ◽  
Local Optima ◽  
Term Selection ◽  
Selection For ◽  
The Individual

AbstractAdaptive plasticity allows organisms to cope with environmental change, thereby increasing the population’s long-term fitness. However, individual selection can only compare the fitness of individuals within each generation: if the environment changes more slowly than the generation time (i.e., a coarse-grained environment) a population will not experience selection for plasticity even if it is adaptive in the long-term. How does adaptive plasticity then evolve? One explanation is that, if competing alleles conferring different degrees of plasticity persist across multiple environments, natural selection between lineages carrying those alleles could select for adaptive plasticity (lineage selection).We show that adaptive plasticity can evolve even in the absence of such lineage selection. Instead, we propose that adaptive plasticity in coarse-grained environments evolves as a by-product of inefficient short-term natural selection. In our simulations, populations that can efficiently respond to selective pressures follow short-term, local, optima and have lower long-term fitness. Conversely, populations that accumulate limited genetic change within each environment evolve long-term adaptive plasticity even when plasticity incurs short-term costs. These results remain qualitatively similar regardless of whether we decrease the efficiency of natural selection by increasing the rate of environmental change or decreasing mutation rate, demonstrating that both factors act via the same mechanism. We demonstrate how this mechanism can be understood through the concept of learning rate.Our work shows how plastic responses that are costly in the short term, yet adaptive in the long term, can evolve as a by-product of inefficient short-term selection, without selection for plasticity at either the individual or lineage level.

Behavioral, plastic, and evolutionary responses to a changing world

2018 ◽  
Author(s):  
Wolf U. Blanckenhorn
Keyword(s):  
Climate Change ◽  
Life History ◽  
Environmental Change ◽  
Physiological Responses ◽  
Short Term ◽  
Temporal Scales ◽  
Evolutionary Response ◽  
Physiological Adjustments ◽  
Changing World

Organisms can respond to environmental change by modifying their behavior to obtain an instant response, through short-term phenotypically plastic, often physiological, adjustments, and/or by adapting their life history through a more long-term evolutionary response. Behavioural and physiological responses, in fact, can occur at all these three temporal scales. Examples of behaviors so affected include congregation, dispersal, foraging, migration, or mating. Such responses have consequences at the population and community levels, and ultimately for the evolution of species. This chapter discusses insect examples of these kinds, with an emphasis on human-induced factors, such as (primarily) climate change, pollution, fragmentation, and urbanization.

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