limiting factors simulation

Then, students will identify limiting factors and (2). The limiting factors mapping (Fig 8) shows that high rainfall is the limiting factor determining the southern boundary of the species, as shown in the response curves of PDM and AP. For more information about PLOS Subject Areas, click how limiting factors can affect plant growth. 06 Dec. 2015. lesson and guiding students in creating a graphic organizer on Data Availability: All relevant data are within the paper and its Supporting Information files. The potential distribution of Chinese sea buckthorn is mainly located in semi-humid and semi-arid regions (Fig 2D), and begins from southwest of the Hengduanshan Mountains and extends to the southern boundary of the Daxinganling Mountains (extending southwest to northeast at 45°). Therefore, air mass of Eastern Asian monsoon arrives in Loess Plateau later and continues for shorter period, while that of Siberian cold winter monsoon reaches this area earlier and lasts for longer time within a year [62,63]. Although there is high consistency between models, many studies have shown that maximum entropy modeling (MaxEnt) is widely used and usually produces accurate predictions of species distributions [20,21,38]. The meanings of abbreviations of PDM, AP, CI, ART, PWM, WI, PSD, MTCM, MTWM, HI, PER, AMT, and ABT can be found in Table 1. https://doi.org/10.1371/journal.pone.0131659.g004. It has been widely planted for preventing soil erosion. limiting factors for populations. Such modeling techniques are recommended when absence data of a species is not available or reliable [30,37]. The width of the range is about 560 km with an area of approximately 1.12 million km2, occupying 11.7% of the land area of China, spanning 12 provinces including Xizang, Yunnan, Sichuan, Gansu, Qinghai, Ningxia, Shaanxi, Shanxi, Hebei, Inner Mongolia, Henan, and Liaoning with the core areas mainly located in Xizang, Sichuan, Gansu, Qinghai, Ningxia and Shaanxi provinces (Fig 2A). Therefore, Chinese sea buckthorn has been arousing international attention as a promising new crop, and it is predicted by some as the next major health food fad [3]. A serious soil erosion problem exists within the range of potential distribution region of Chinese sea buckthorn. These studies greatly improve our understanding of the influence of climatic factors on geographic distribution of Chinese sea buckthorn. organisms. . Have student groups complete the activity, recording their data The exotic species black locust (Robinia pseudoacacia) could survive in the same region as Chinese sea buckthorn, but the distribution of black locust does not show the southwest-northeast direction [47] because black locust is mainly limited by low temperatures unlike those of the Eastern Asia monsoon climate. I) Humid region with non-distinct dry season; II) Humid region with distinct dry season; III) Semi-humid region; IV) Semi-arid region; V) Arid region; VI) Extremely arid region. The results show that the climatic thresholds for the core areas of Chinese sea buckthorn are as follows: PDM of 1.0–7.0 mm, AP of 344.0–1089.0 mm, CI of -47.7–0.0°C, ART of 26.1–45.0°C, PWM of 81.0–230.0 mm, WI of 42.0–170.4°C, PSD of 72.0–106.0 mm, and MTCM of -19.8– -1.3°C. various limiting factors can influence population size over time. It has a range of 0–1, with a value greater than 0.5 indicating a better-than-random performance event. Evaluation of climatic factors revealed that the distribution of Chinese sea buckthorn is mainly affected by PDM, AP, CI and ART. Ask students to consider the Predator-Prey The assumption is that information on which variable is driving the MESS value at any given point can be extracted and mapped by finding the most dissimilar variable. Students will be hooked into this lesson with a hands-on Students must identify at least 4 density Our study could provide theoretical support for top-level design of the cultivation and planting of Chinese sea buckthorn for policy-makers and planners. represent mice (prey) (S-B-2-2_ Predator-Prey Cards.docx), one set for each group of three to four students, 25 large squares cut from index cards or card stock, to Examine the effects of limiting factors on population dynamics. Moodle, n.d. The 10-fold cross-validation method and areas under the receiver operating characteristic curve method were used to assess the accuracy of the MaxEnt model. Small-Group Activity: Predator-Prey group. If we let mini be the minimum value of variable Vi over the reference point set and the similarly for maxi, pi be the value of variable vi at point P, fi be the percent of reference points whose value of variable Vi is smaller than pi, then the similarity of P with respect to variable Vi is calculated by Eq 2: Finally, the multivariate similarity of P is the minimum of its similarity with respect to each variable. double-line graph students created. The study was conducted in China, which is located in the eastern part of Asia, on the western coast of the Pacific Ocean (3°52′–53°33′N, 73°40′–135°2′E), and spans are over 5,000 km from east to west and over 5,500 km from north to south. population size. Describe different food webs including a food web containing humans. Moodle Share. Ask, “What stops the mouse population from growing The BIOCLIM variables have been widely used in SDMs studies, as the data can be easily downloaded from the WorldClim database with no further calculation requirement. In this lesson, students will conduct a Chinese sea buckthorn (Hippophae rhamnoides subsp. drought, forest fires, and human disturbances. carrying capacity from population data. 06 Dec. 2015. plant competition affects seedling growth. Analyze possible causes of population fluctuations. Funding: The project was supported financially by the National Nature Science Foundation of China (No. Have students copy the The altitude decreases from the southwest (about 3500–4100 m) in the Hengduanshan Mountain region to northeast (1000–1500 m) in the Loess Plateau region. Divide students into groups of three to four Thus, the predicted suitable area might partly be unsuitable for cultivation of the species (e.g. In this study, the potential distribution of Chinese sea buckthorn was found to be similar to its occurrence records (Fig 2B), which demonstrates that the distribution pattern of Chinese sea buckthorn is in equilibrium with climatic conditions. However, it is worth mentioning that the south boundary of liaotung oak is not able to extend to the northern slope of the Qinling Mountains, which represent a dividing line between the warm temperate and northern subtropical zone in China. If possible, allow students to conduct the prior knowledge. have. (See The coefficient of variation in test AUC values was only 2.2% among 10 model simulations, which showed that the 10-fold cross-validation method didn't influence the predicted performance of the MaxEnt model. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. We could also use local weather station data to indicate when this species could be planted and cultivated. and density-independent limiting factors. The limiting factors mapping shows that high rainfall is the limiting factor determining the southern boundary of the species, as shown in the response curves of PDM and AP. According to map of limiting factors, we could easily deduce which factors are limiting physiological and ecological processes. density-dependent and density-independent limiting factors. as density-dependent or density-independent. Because of its large area and extent, as well as its high population, China has a wide variety of climates, topography, soil and vegetation types [40]. Performed the experiments: GL SD KG. Web. . These variables have been widely used in research on the relationship between species/vegetation and climate at a regional or global scale. MESS analysis assists in revealing whether there is possible model-predicted novel habitat (extrapolation), which informs the credibility of model output. The authors acknowledge three anonymous reviewers for their constructive comments, which significantly improved the manuscript. The first part of the lesson is a hands-on, exploratory Describe how energy is converted from one form to another as it moves through a food web (photosynthetic, geothermal).

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