“Caracterización de los sistemas de producción de ovinos de pelo en el suroeste del departamento de Matagalpa 2010”

Con el objetivo de caracterizar los sistemas de producción de ovinos de pelo en el territorio suroeste del departamento de Matagalpa 2010. (Sébaco, Ciudad Darío, San Isidro y Matagalpa). Se aplicó una encuesta a 103 productores que poseen ovinos de pelo, la muestra se definió aleatoriamente utilizando la ecuación planteada por Scheaffer (1987), se utilizó la técnica de muestreo de bola de nieve, planteada por Frey et al (2000). Esta investigación permitió conocer las debilidades y oportunidades en los sistemas de explotación de esta especie promisoria para la zona seca del país. Con los resultados obtenidos de las encuestas se procedió ha elaborar una base de datos en el programa SPSS versión 11.5 en español. Encontrando un predominio del sexo femenino como titulares de las explotaciones ovinas, 58.3% cursó educación primaria, el 98% de las explotaciones cuentan con raza pelibuey, el 100% de las explotaciones realizan destete y monta de forma natural, una media de mortalidad de corderos de 1, alimentan a las ovejas con potrero sin división (81.6%), se suministra pasto de corte, pastoreo, leguminosas y se suplementa sal común 49.5%, aplican vacunas contra ántrax y pierna negra (63.1%), desparasitaciones internas y externas (66%), ambos con una frecuencia de 2 veces al año, en el manejo productivo no se lleva control en la actividad ovina (100%), los equipo e instalaciones son rústicas, los corrales ovinos el son elaborados con alambre y/o madera, techado con plástico y/o zinc (49.51%), en cuanto a asistencia técnica el 58.3% ha recibid

Linear relationships between observed changes in location request across rural grid cells during the Chinese New Year period and the corresponding amount of regional out-migrants at three different levels.

<p>Linear relationships between observed changes in location request across rural grid cells during the Chinese New Year period and the corresponding amount of regional out-migrants at three different levels.</p

An estimate of rural exodus in China using location-aware data - Fig 5

<p>(A) The spatial distribution of relative increase rate in <i>N</i> for all rural grid cells with increased <i>N</i>. (B) The spatial distribution of the net increase in <i>N</i> for rural grid cells. (C) The map of the amount of rural hamlets and villages covered by rural grid cells. All maps are based upon the medium estimate. Latitudinal and longitudinal profiles with an interval of 0.5 arc degree are represented, correspondingly.</p

The relationship between the regional sum of observed <i>N</i> and the number of visitors (both are normalized using the standard score) to Pearl Spring Park (located in Nanjing, Jiangsu province) over the 62 days period in 2017.

<p>The relationship between the regional sum of observed <i>N</i> and the number of visitors (both are normalized using the standard score) to Pearl Spring Park (located in Nanjing, Jiangsu province) over the 62 days period in 2017.</p

Log-linear relationships between the regional net increase in sum of average <i>N</i> (based on the medium estimate) from rural grid cells and the size of source population at three different administrative levels.

<p>Log-linear relationships between the regional net increase in sum of average <i>N</i> (based on the medium estimate) from rural grid cells and the size of source population at three different administrative levels.</p

Two representative time series of <i>N</i> derived from an urban grid cell (red, located in Shanghai City) and a rural grid cell (black, located in a Henan’s rural village).

<p>Two turning points (<i>TP</i>s, both red and black solid circles) were detected using Zivot and Andrews’s unit root testing. <i>NU</i>_b (<i>NR</i>_b) and <i>NU</i>_a (<i>NR</i>_a) stand for average <i>N</i> before and after <i>TP</i> for urban (rural) grid cell, respectively. Statistical difference between <i>NU</i>_b and <i>NU</i>_a (as well as between <i>NR</i>_b and <i>NR</i>_a) can be connected to declined population in urban area (increased in rural area) around the time of the Chinese New Year.</p

Bivariate plots of the regional net increase in average daily location request and the proportion of grid cells with increased <i>N</i> (based on the medium estimate) at three different administrative levels.

<p>The quantitative relationships between two variables are fitted by a logarithmic regression model (red curves).</p

An estimate of rural exodus in China using location-aware data - Fig 4

<p>(A) Country-level time series of location request in social media uses for different areas. Right inset shows the corresponding number of grid cells. (B) Temporal changes in proportion of location request relative to the total country-level sum of <i>N</i> for different areas as shown in (A) except TS1.</p

Multi-level quantitative comparisons between proportions of regional sum of declined and increased location request accounting for the nationwide sum for urban and rural domains, respectively, demonstrate regional imbalances in rural migrations into urban areas.

<p>The deviation from the balanced diagonal is measured using multiples of statistical error. Here, the upper and the lower deviation line represent and , respectively.</p

Summary of determinative criteria for the estimate of grid cell-level rural depopulation and its lower and upper bound.

<p><i>NR</i>_<i>b</i> and <i>NR</i>_<i>a</i> stand for average <i>N</i> before and after <i>TP</i> for rural grid cells, respectively.</p