Stephen Aichele, PhD, is a research scientist in Switzerland in University of Geneva's Psychology & Educational Sciences Department. Aichele received his bachelor's degree in biopsychology from University of California, Santa Barbara (1994), followed by a master's degree with highest honors in quantitative psychology (2010) and a PhD in quantitative psychology (2013) from University of California, Davis. As a graduate research assistant, Dr. Aichele worked on both the The Samantha Project and Savannas Forever Tanzania HIV Research Initiative.
Dr. Aichele's academic employment has included laboratory instructor and teaching assistant at University of California, Davis, in advanced statistical inference (graduate level), causal modeling of correlational data (graduate level), statistical analysis of psychological data, and research methods in psychology. He has been published in Psychological Science; Psychology of Consciousness: Theory, Research and Practice; Emotion, Psychology and Aging; Neuroimage; PLoS ONE; Health Psychology; Frontiers in Human Neuroscience; Psychoneuroendocrinology; and Attention, Perception & Psychophysics. Dr. Aichele has presented at numerous conferences, including the Annual Meeting of the Gerontological Society of America; 21st International Conference on Computational Statistics; Annual International Meeting of the Psychometric Society; University of California, Davis' Annual Spring Psychology Departmental Conference; University of California Global Health Day; Computational Neuroscience Society Annual Meeting; and Society for Neuroscience Annual Meeting. Dr. Aichele's research and expertise includes multivariate statistical methods in the behavioral sciences, cognitive aging and epidemiology, and longitudinal data analysis. Most recently, he was awarded the John Templeton Foundation Research Grant ($2.3 million).
When did you first decide to become a psychologist? Why?
My interest in psychology began during high school. I was struggling with the emotional and relational fallout in my family after my mother was diagnosed with a terminal illness (advanced non-Hodgkin lymphoma) when she was 39 years old. At the time I wanted to become a clinical psychologist or perhaps a psychiatrist.
How/why did you choose the graduate school you attended?
I attended two graduate schools. The first was a program in clinical psychology at a private college—within a year I knew it was the wrong decision. Later, after completing additional coursework in computer science and mathematics, I found a job as a research specialist at the university where I ultimately completed my doctorate. There were several reasons I chose to pursue my PhD there: I had already established a direction for my research, they had an excellent graduate program in my area of interest, and I had financial support (through an existing grant).
What surprised you the most about your graduate studies?
Because I had financial support going in, I was able to focus exclusively on coursework and research for the first two years of my education. But when the grant ended, I was worried that needing to TA to support myself financially would slow my progress. As it turned out, I loved teaching the statistics labs.
Why did you decide to specialize in quantitative psychology in particular?
In some ways I feel like quantitative psychology chose me. As a first-year undergraduate student, long before I attended graduate school, I was asked to help as a teaching assistant for a course in quantitative psychology that I had just completed. But shortly afterward I shifted my focus to neuroscience in order to apply to medical school. While I'm glad to have completed the pre-med coursework, my real strengths and interests were in psychology and computing. Following my undergraduate education, I spent a long time looking for a field that would allow me to combine those interests. Later, when I took a position as a research specialist, I discovered that there was a graduate program in quantitative psychology at the university where I was working, and it then dawned on me that what I had been seeking for so long was right there.
If you had to do it all over again, would you still specialize in quantitative psychology? Why or why not?
Yes, absolutely. I've pursued other career paths, but I've yet to find any that suit me so well.
Has being a quantitative psychologist met your expectations? Please explain.
Actually, it's exceeded my expectations. Initially I worried that, as a field, quantitative psychology might be too restrictive and boring, but that's not at all the case. That said, had my research emphasized standardized educational testing, I might feel that way. Also, relative to other areas in behavioral research, there appear to be more job openings for qualified candidates in quantitative psychology.
What do you like most about being a quantitative psychologist?
The flexibility to work on a variety of interesting topics is excellent. As a former mentor put it, "Everyone needs a data analyst." It's quite thrilling to apply both novel and well-known statistical methods to discover new things about human behavior and health outcomes. It's also rewarding to teach others how to use such powerful tools responsibly.
What do you like least about being a quantitative psychologist?
It can be difficult to locate oneself along the working spectrum of technical innovation and practical application. I simply don't have the time both to be an innovator in a specific statistical methodology and to apply those methods in addressing "real world problems." The result is that my career can at times feel like a bridge between worlds (statistics, psychology) when I would prefer to better acquaint myself with one or the other world.
Currently my work is heavily research focused. I have access to a vast amount of data that have been painstakingly collected, over decades, from thousands of individuals. It's my job to use sophisticated statistical methods to clarify what those data have to say about age-related changes in mental health – and then write the story. Because my work is cyclical by nature, I don't so much have a typical day as a typical week or month. When I begin a new project, I will often spend several weeks cleaning and then analyzing the data that I receive in order to answer several key questions that I have formulated ahead of time. Then I shift gears from data analyst to behavioral researcher, diving into the empirical literature to better understand the results of the analyses and to deepen my knowledge of related work. Depending on what I learn, I may or may not need to reconfigure the analyses. Rinse, repeat. Then I combine the information from the literature review and data analyses into a manuscript to be submitted for publication. Throughout this process, there are also meetings to attend, talks and/or seminars to give, and grants to write. At the moment I have no teaching obligations, but that will likely change if I remain in academia.
I typically work a 40-hour week, but it fluctuates. My hours are flexible, which can both be helpful (I have two young daughters and associated responsibilities) and at times aggravating (because my spouse's work hours are not flexible, I often end up shouldering any unanticipated household and/or childcare needs, which means I make up for missed work at night or on weekends). I get about six hours of sleep per night – often less, rarely more. I think sleep will be better once the kids are a little older. I have about 10 weeks of vacation per year (I live and work in Switzerland, after all). Here, people actually use their weekends and vacation days to recuperate and spend time with family – I almost never receive work-related email during a weekend or official holiday as it is generally considered unprofessional.
Do you feel you have enough time to spend with your family? Why or why not?
Yes, I am very fortunate in this respect. I get ample vacation time, and I work in close proximity to my children's school/daycare. By comparison, my wife, who has less vacation time and who commutes to work, is envious of the time I have with the kids.
Despite the generous downtime from work, life has felt insanely busy the past two years, and I have struggled to find balance. As a family, we've been adjusting to a new country, new language, new jobs, and the demands of parenting (two children under the age of five, one of whom was a baby when we first arrived). I travel internationally between Europe and the U.S. twice per year with my family and once or twice per year for work. There are amazing perks to living and working abroad, but there are also certain socio-cultural handicaps one faces as an outsider that place strains on time and energy (and finances). Also, because I'm an American, I have no real long-term job security here, which means that I constantly need to be thinking ahead, which can be stressful. I am only now starting to feel like we are mostly adjusted to this new lifestyle – and that there is a bit more room to breathe.
Do you feel you are adequately compensated in your field? Please explain.
Yes, quite. Academic salaries are good in Switzerland. However, positions in Swiss universities are closely guarded, and it is nearly impossible for an American to secure long-term employment in one of the more lucrative posts.
If you took out educational loans, is/was paying them back a strain? Please explain.
I feel strongly that the system of student loan debt in the U.S. is disgraceful, and I made a point of not going into debt to fund my graduate education. However, I also realize that I was fortunate to not need to take out student loans, and I certainly appreciate the difficulty posed by the decision of whether or not to take out loans in order to attend medical/professional/graduate school.
In your position now, knowing what you do, what would you say to yourself back when you started your quantitative psychology career?
If I could, I would give advice to myself during my undergraduate years, but the undergraduate me would probably not have listened to such trite remarks: Start early and stick with it. Take an internship in a lab as an undergraduate and build connections and experience outside of class. Keep sharpening your practical skills, because that's where the opportunities are. Don't follow the herd, but also recognize the value of working within an established system.
What information/advice do you wish you had known prior to beginning graduate school?
I was older and relatively savvy about academia by the time I started my degree in quantitative psychology. If anything, I wish I hadn't wasted the time and money that I did in my earlier attempt to pursue a doctorate in clinical psychology at a private college.
From your perspective, what is the biggest problem in health care today? Please explain.
Well, that's a huge question. Globally, the main problem seems to be differential access to quality health care. But with respect to my research, I would say that what concerns me most is the increasing need for medical and functional support for older individuals with mental impairment.
Where do you see quantitative psychology in five years?
With the growth of computing, the internet, and data mining technologies, there has been a lot of hype about "big data." But "big data" are not necessarily "smart data." Anyone interested in statistical and computational approaches to studying human behavior (and related health outcomes) would do well to consider lessons learned by quantitative psychologists over the past century. I see increasing need for such individuals, both within and outside of academia.
I currently perform very little outreach/volunteer work due to parenting responsibilities. Previously, I spent several years working for a not-for-profit educational center focused on teaching communication and community-building skills to school-age children in Southern California.
What's your final piece of advice for students interested in pursuing a career in quantitative psychology?
Learning statistics is a non-linear, iterative process that requires time and effort—but also one that quickly starts to pay off. But quantitative psychology is not just about statistics: It is equally important to learn how to approach behavioral and health-related analyses as a theoretically minded scientist. Sometimes technical curiosity will outweigh interest in psychological phenomena, or vice versa, but in the end a quantitative psychologist must be able to skillfully integrate the two.


DeeperStill – Greensboro NC from Rich Kalonick on Vimeo.
Living Proof Live Rio Rancho NM from Rich Kalonick on Vimeo.
Living Proof Live – Pittsburgh PA from Rich Kalonick on Vimeo.
Untitled from Kris Seidenkranz on Vimeo.


text:
Jan 11, 2021 | INDUSTRY NEWS
African Petchem Firms Sign Hamriyah Free Zone Leasing Deal
Despite Covid-19's global economic fallout, the Hamriyah Free Zone Authority (HFZA) has reinforced its reputation and position as a prominent destination regionally and globally after two giant African petrochemicals companies – Global Vision Specialty Chemicals & Proud Lubricants and Grease IND – announced investments in the free zone by leasing over 1,076,391 sq ft plots of land.
The deal was signed at HFZA headquarters by Saud Salim Al Mazrouei, Director of Hamriyah Free Zone Authority, and Antonio Joao Pinto, the Founder, and CEO of the two firms, in the presence of senior officials from both sides.
Global Vision Specialty Chemicals is specialized in Blending, Packaging & Drumming of Drilling Upstream & Downstream Petrochemicals and Chemical Additives, while the activity of Proud Lubricants and Grease is the manufacturing of Lubricants, Grease, Plastic Products & Tins.
As per the MoU, the two companies are expected to inaugurate world-class petrochemicals factories and warehouses for export to local, regional, and global markets.
Al Mazrouei pointed out that this new investment was a testament to Sharjah's pioneering position as a business destination for innovation and future companies and a main gateway to regional and global markets, affirming that the petrochemicals industry is one of the key factors of the emirate's economic diversification strategy and development plans, stressing the importance of attracting such specialized companies to bolster the knowledge economy.
"HFZA has successfully managed to turn the current global challenges into opportunities for further enhancing innovation and distinction in the services provided," he added.
Al Mazrouei also lauded the economic stimulus packages adopted earlier by the Sharjah Government to strengthen the presence of foreign investments and ensure business sustainability.
For his part, Antonio Joao Pinto hailed the cooperation and facilities provided by HFZA to launch the new investment, thanking the HFZA team for the professionalism they have shown to expedite the roll out of the operations of the two companies.
"After a deliberate study, we've chosen Sharjah to be the centre of our operations and expansion activities, thanks to the various investment advantages and the premium services provided to the companies operating in Sharjah's free zones," he added.
Pinto pointed out that the petchem firms' primary focus was to boost its presence in the European and Asian markets, thus benefiting from the zone's sophisticated infrastructure, as well as the facilities and services, and the vast business networking HFZA provides to its investors.
In addition to offering industrial and commercial plots of land, HFZA, the second-largest industrial free zone in the UAE, provides advanced infrastructure and modern facilities that strengthen external expansion plans for investors, especially in import and re-export to the world's markets, he added.
Iran Registers 7% Increase in Petchem Production – NPC
Oman LNG Signs Agreements with Japanese Firms
Oman to Export 2.35mn tonnes of LNG Annually to Japan Firms

redpajama_set_name: RedPajamaCommonCrawl


text:
Predicting suitable habitat of the Chinese monal (Lophophorus lhuysii) using ecological niche modeling in the Qionglai Mountains, China
PeerJ
Bin Wang1, Yu Xu2,3, Jianghong Ran1
1Sichuan University, Key Laboratory of Bio-Resources and Eco-Environment of Ministry Education, College of Life Sciences, Chengdu, China
2Guizhou Normal University, College of Life Sciences, Guiyang, China
3Pingdingshan University, School of Resources and Environmental Sciences, Pingdingshan, China
10.7717/peerj.3477
Patricia Gandini
Biodiversity, Conservation Biology, Natural Resource Management
Conservation gap, Habitat fragmentation, Local disturbances, Nature reserve, MaxEnt
© 2017 Wang et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
Wang B, Xu Y, Ran J. 2017. Predicting suitable habitat of the Chinese monal (Lophophorus lhuysii) using ecological niche modeling in the Qionglai Mountains, China. PeerJ 5:e3477 https://doi.org/10.7717/peerj.3477
The authors have chosen to make the review history of this article public.
Understanding the distribution and the extent of suitable habitats is crucial for wildlife conservation and management. Knowledge is limited regarding the natural habitats of the Chinese monal (Lophophorus lhuysii), which is a vulnerable Galliform species endemic to the high-montane areas of southwest China and a good candidate for being an umbrella species in the Qionglai Mountains. Using ecological niche modeling, we predicted current potential suitable habitats for the Chinese monal in the Qionglai Mountains with 64 presence points collected between 2005 and 2015. Suitable habitats of the Chinese monal were associated with about 31 mm precipitation of the driest quarter, about 15 °C of maximum temperature of the warmest month, and far from the nearest human residential locations (>5,000 m). The predicted suitable habitats of the Chinese monal covered an area of 2,490 km2, approximately 9.48% of the Qionglai Mountains, and was highly fragmented. 54.78% of the suitable habitats were under the protection of existing nature reserves and two conservation gaps were found. Based on these results, we provide four suggestions for the conservation management of the Chinese monal: (1) ad hoc surveys targeting potential suitable habitats to determine species occurrence, (2) more ecological studies regarding its dispersal capacity, (3) establishment of more corridors and green bridges across roads for facilitating species movement or dispersal, and (4) minimization of local disturbances.
Understanding the distribution of suitable habitats and its influencing factors are crucial for wildlife conservation and management (Austin, 2002). Ecological niche models have developed as excellent tools for predicting habitat distribution of species that are difficult to investigate (Peterson, Ball & Cohoon, 2002; Mota-Vargas et al., 2013), because they can predict the distribution of species' habitats at a large spatial scale based on species presence data and environmental variables, without the need for extensive surveys and detailed descriptions of physiological and behavioral characteristics (Morrison, Marcot & Mannan, 2012). In particular, MaxEnt, a presence-only modeling approach based on the maximum entropy principle (Phillips, Anderson & Schapire, 2006), outperforms other models in prediction accuracy (Elith et al., 2006; Phillips, Anderson & Schapire, 2006), transferability (Tuanmu et al., 2011), and performance with small sample sizes (Pearson et al., 2007; Costa et al., 2010). It offers great potential for addressing endangered and poorly known bird species with scarce occurrence data (e.g., Botero-Delgadillo, Páez & Bayly, 2012; Marcondes et al., 2014; Tobón-Sampedro & Rojas-Soto, 2015).
The Chinese monal (Lophophorus lhuysii) is the largest Galliform species (with a mean length of 76 cm and a mean weight of 3.18 kg) distributed in high-montane regions, mainly inhabiting subalpine scrubs, as well as subalpine and alpine meadows at an elevation of 3,000–4,900 m (MacKinnon, Phillipps & He, 2000; Madge, McGowan & Kirwan, 2002). This species is endemic to southwest China, and is found primarily in southeast Gansu, southeast Qinghai, western Sichuan, and northwest Yunnan (Lei & Lu, 2006; Lu, 2015). It has been listed on appendix I of CITES since 1975 (CITES, 2016) and classified as a vulnerable species on the IUCN red list since 1994 (IUCN, 2015). In 1989, the Chinese government started to legally protect the species as a first-class, nationally-protected wildlife species (Ministry of Forestry of People's Republic of China, Ministry of Agriculture of People's Republic of China, 1989). Recently, the Chinese monal was identified as one of the endemic bird species in China with the highest conservation values in terms of phylogenetic diversity (Chen, 2013). Its population size, however, remains small (10,000–25,000 individuals in total, BirdLife International, 2015) and is inferred to be in a state of continuous decline because of illegal hunting and on-going habitat degradation and fragmentation (BirdLife International, 2015). It is therefore necessary to establish effective conservation programs targeting the Chinese monal.
However, knowledge of the natural habitats of the Chinese monal is limited, as cryptic behavior and inaccessible habitats of the species make it difficult to survey the natural populations. Most of the previous studies were conducted in the late twentieth century and only provided simple descriptions of habitat use (Ma, 1989; Zhang, 1995), population density and structure (He & Lu, 1985; Long et al., 1998), breeding ecology (He et al., 1986), activity pattern (Ma, 1988), and feeding habits (Lu et al., 1986). There has not been a quantitative analysis of the natural habitats of the Chinese monal at a large spatial scale in any part of its geographical range and this limited knowledge has constrained conservation development for the Chinese monal.
Figure 1: Topographic map of the Qionglai Mountains, showing the location of the 64 presence points of the Chinese monal used in modeling.
The black triangle shows the location of Huayan tunnel at which we observed monals crossing the road daily (detailed in 'Discussion'). The geographic range of Chinese monal was delineated based on Lu (2015).
DOI: 10.7717/peerj.3477/fig-1
The Qionglai Mountains are a part of the biodiversity hotspot of the Mountains of Southwest China (Mittermeier et al., 2011) that supports many endangered and endemic wildlife species. As the geographical center of the distribution of the Chinese monal (Lei & Lu, 2006; Lu, 2015; Fig. 1), this region is critical for the conservation of the species. In this study, we used the ecological niche modeling approach, with species records and predictors selected from a large set of environmental variables, to predict the current potential suitable habitats for the Chinese monal in the Qionglai Mountains. Our objectives were to (1) delineate the distribution of suitable habitats of the Chinese monal, (2) identifycritical environmental factors influencing the species' habitat suitability, (3) compare the prediction with existing nature reserve network and provide conservation suggestions based on the results.
Materials & Methods
The Qionglai Mountains are the easternmost portion of the Hengduan Mountains, extending approximately 250 km from north to south at the center of Sichuan Province, China (E: 102°01′–103°46′, N: 29°27′–31°55′; Fig. 1). The area covers 26,258 km2 and incorporates 12 counties, including Lixian, Xiaojin, Baoxing, Dayi, Lushan, Qionglai, and Tianquan; the areas west of the Min River in Wenchuan, Dujiangyan and Chongzhou counties are also included in the Qionglai Mountains (the east side of the River belongs to the Minshan Mountains); the areas east of the Dadu River in Luding and Kangding counties are also included in the Qionglai Mountains (the west sides of the River belong to the Daxueshan Mountains). Elevation ranges from 450 m in the Sichuan Basin to 6,250 m at the Siguniang Mountain peak. The subtropical monsoon climate predominates the region. There are diverse ecosystems and vegetation types, with many rare and endangered wildlife species, such as the giant panda (Ailuropoda melanoleuca), golden snub-nosed monkey (Rhinopithecus roxellanae), snow leopard (Panthera unica), takin (Budorcas taxicolor), and dove tree (Davidia involucrate) (Hu, 2001).
Presence data
In total, we gathered 103 current (2005–2015) presence records of the Chinese monal (Table S1), including sightings, callings, feces, and feathers. The majority (86.4%) of the records was from field surveys in recent years, including the authors' filed survey records, sympatric animal database of the fourth national survey on giant panda, and biodiversity monitoring data from nature reserves; the remaining data was from published literatures and network databases (for details, see Table 1). To insure spatial accuracy, we only kept presence points with accuracies to three decimal places of the coordinates. To avoid overfitting the model, we generated a 1 km2 buffer around each presence point and randomly selected one if the buffers overlap, as this area approximates the minimum home range size maintained by the Chinese monal (He & Lu, 1985). Finally, 64 remained presence points with geographic coordinates were used to build the ecological niche model (Fig. 1).
Sources of Chinese monal presence data in the Qionglai Mountains used in the suitable habitat modeling.
Elevational range and area of survey site
Survey technique and effort
Survey time
Used/total presence points
Global Biodiversity Information Facility (http://www.gbif.org/) Network database Bird-watching records 2005–2015 2/7
Shen, Li & Xiang (2010) 3,300–4,170 m; 35 km2 Published literature Apr–Nov, 2007–2010 7/7
Comprehensive scientific survey on Anzihe Nature Reserve 1,638–3,868 m; 110 km2 Line transect; 29 3–4.9 km transects Apr–Oct, 2010 3/3
Comprehensive scientific survey on Fengtongzhai National Nature Reserve 1,000–4,896 m; 403 km2 Line transect; 38 2–5 km transects May–Oct, 2010–2011 15/28
Sympatric animal database of the fourth national survey on giant panda 1,000–4,400 m; 8,740 km2 Grid square; 4,370 2 km2 squares Mar–Dec, 2012–2013 22/24
Infrared-triggered camera monitoring in Heishuihe Nature Reserve 1,520–4,234 m; 234 km2 Infrared-triggered camera; 70 cameras All year round, 2013–2014 5/15
Infrared-triggered camera monitoring in Labahe Nature Reserve 1,500–4,500 m; 170 km2 Infrared-triggered camera; 30 cameras All year round, 2014–2015 4/5
Montane bird survey in Wolong National Nature Reserve 3,600–4,400 m; 17 km2 Line transect; 7 2–6 km transects Jun–Jul, 2015 6/14
DOI: 10.7717/peerj.3477/table-1
A total of 42 environmental variables (Table S2) summarizing five groups (bioclimatic data, vegetation, phenological metrics, topographical attributes, and human impacts) potentially related to habitat suitability of the Chinese monal were selected as candidate variables. We included 19 bioclimatic variables from WorldClim 1.4 (http://www.worldclim.org/), which were interpolated based on a large number of weather stations all over the world, integrating the effects of latitude, longitude, and elevation (Hijmans et al., 2005). Bioclimatic data were frequently used in habitat modeling due to direct effects on species distribution (Guisan & Zimmermann, 2000). Vegetation and phenology-related variables were derived from moderate resolution imaging spectroradiometer (MODIS) remotely sensed data from LP DAAC (https://lpdaac.usgs.gov/). The International Geosphere-Biosphere Programme (IGBP) classification of land cover within MCD12Q1 2014 product was used as a categorical variable of vegetation type (Loveland & Belward, 1997). This classification was derived from yearly MODIS data and 1860 training sites observations distributed across the Earth's land areas (Friedl et al., 2010). We downloaded a time series of MOD13Q1 16-day enhanced vegetation index (EVI) product over a three year period from 2013 to 2015 (23 layers per year). To reduce the potential noise caused by cloud remnants, we reconstructed a clean and smooth EVI time series employing an adaptive Savitzky-Golay filter and then generated 15 phenological metrics using TIMESAT 3.2 (Jönsson & Eklundh, 2002; Jönsson & Eklundh, 2004). These EVI derived metrics strongly correlate with vegetation primary productivity and its seasonality (Jönsson & Eklundh, 2002; Rahman et al., 2005; Alcaraz-Segura et al., 2013), and could improve the performance of species habitat modeling (Requena-Mullor et al., 2014). The topographical attributes included elevation, slope, aspect, and distance to rivers. Slope and aspect were extracted from an ASTER GDEM V2 30 m resolution digital elevation model (DEM; http://www.gscloud.cn/), using the Surface Analyst Tool of ArcGIS 10.2 (ESRI, Redlands, CA, USA). Aspect was recalculated as the absolute value of actual degree minus 180°, representing how close the slope was to the adret facing the sun (Kalkhan, 2011). We produced a layer of distance to the nearest perennial river using the Euclidean Distance Tool of ArcGIS. Variables regarding human impacts included Euclidean distance to residential locations (villages and rural settlements) and to roads, and human influence index (HII). HII layer was downloaded from Last of the Wild (Data Version 2, 2005) (http://sedac.ciesin.columbia.edu/), representing anthropogenic impacts spanning 1995–2004 that were calculated by integrating the data including human population pressure (population density), human land use (built-up areas, nighttime lights, land use, and land cover), and human accessibility (coastlines, roads, railroads, and navigable rivers). The basic vector layers of rivers, roads, and residential locations were provided by National Geomatics Center of China (NGCC). Each variable was projected to the UTM zone 48N coordinate system, and resampled to the same pixel size as the EVI layers (about 250 m) using bilinear interpolation, except for the categorical land cover that was resampled using nearest neighbor assignment.
Model procedure
We used MaxEnt to generate the habitat suitability model of the Chinese monal (MaxEnt 3.3.3k, http://biodiversityinformatics.amnh.org/open_source/maxent/). Ecological niche models with inappropriately complex variables might be oversized, overfitted or redundant (Parolo, Rossi & Ferrarini, 2008; Swanepoel et al., 2013). To increase abilities in building high accuracy predictions and in identifying the critical predictors constraining the species' distribution, we implemented an optimized selection of 42 environmental variables based on sample-size-corrected Akaike information criteria (AICc) (Akaike, 1974; Warren & Seifert, 2011; Warren et al., 2014). Firstly, we built a MaxEnt model with the full set of 42 variables and removed variables with contribution <1% or had Pearson's correlation coefficients >|0.7| with the highest contributed variable; then the retained variables were used to build a new model, and the variables with low contribution (<1%) or high correlation coefficients (absolute values > 0.7) with the second highest contributed variable were removed again; finally, a set of models with different set of variables were produced after repeating this process, and AICc value was calculated for each model based on codes proposed by Warren, Glor & Turelli (2010). The model with the lowest AICc was considered to have the most appropriate complexity (Warren & Seifert, 2011; Jueterbock et al., 2016), thus the variables included in this model were selected to build the final model for Chinese monal habitat. The optimized variable selection was processed in R 3.2.2 (R Development Core Team, 2015) with package "MaxentVariableSelection" (Jueterbock, 2015; Jueterbock et al., 2016).
The regularization multiplier, maximum number of background points, maximum iterations, and convergence threshold were set as default values, since these settings have been found to achieve good performances (Phillips & Dudík, 2008). To produce stable results, we ran 20 replicate bootstrap procedures for the final model. Each replicate used a randomly selected dataset of 75% training data and 25% test data. The built-in functions: contribution of variables, response curves, and jackknife tests were used to analyze the relative importance of each variable in modeling, and their relation with the habitat suitability. We used an average output grid of 20 replicates as the final model prediction, with a logistic habitat suitability index ranging from the lowest "0" to the highest "1."
Model performance was evaluated using three different measures, including area under the receiver operating characteristic curve (AUC), Cohen's maximized Kappa, and the true skill statistic (TSS). All three measures are calculated based on specificity and sensitivity of the predictive model. Specificity and sensitivity represent the success rate for classifying absences and presences, respectively. AUC is a threshold-independent evaluation measure obtained by plotting sensitivity against 1-specificity (Fielding & Bell, 1997). We used the built-in function of MaxEnt program to produce the mean AUC values of the 20 replicates. The model accuracy can be judged as excellent if AUC > 0.9, good if 0.9 > AUC > 0.8, fair if 0.8 > AUC > 0.7, poor if 0.7 > AUC > 0.6, and failed if 0.6 > AUC > 0.5 (Swets, 1988).
Kappa and TSS are threshold-dependent indices that measure the agreement between predictions and known occurrences (presences and absences) at different binary thresholds. Kappa index is obtained by plotting sensitivity and specificity against different thresholds (Cohen, 1960), while TSS equals sensitivity + specificity − 1 (Allouche, Tsoar & Kadmon, 2006). Another difference is that Kappa index responds to species prevalence whereas TSS does not (Allouche, Tsoar & Kadmon, 2006). In this study, we used maximized values of Kappa and TSS at their own optimal thresholds to evaluate model performance. The standards for judging model performance are: excellent if Kappa > 0.75, good if 0.75 > Kappa > 0.4, and poor if Kappa < 0.4 (Araújo et al., 2005); while good to excellent if TSS > 0.8, useful if 0.8 > TSS > 0.5, and poor if 0.5 > TSS > 0.2 (Coetzee et al., 2009). Since these two indices require the use of absence data, 200 additional pseudo-absence points were generated within the study region. These pseudo-absence points were randomly located outside the 1 km buffers of observed presence points for Chinese monals. The threshold-dependent statistics were analyzed in R 3.2.2 (R Development Core Team, 2015) with package "PresenceAbsence" (Freeman & Moisen, 2008).
Habitat analysis
For further analysis, we applied a threshold that maximizes the TSS for transforming the model prediction with a continuous habitat suitability index to a binary suitable/unsuitable map. Maximum TSS is a promising threshold criterion when only species presence data are available, outperforming many other criterions in most cases (Liu et al., 2005; Jiménez-Valverde & Lobo, 2007; Liu, White & Newell, 2013). We estimated total suitable habitat area of the Chinese monal in the Qionglai Mountains and areas harboured in counties and nature reserves, respectively.
Optimized variable selection showed that the model with the lowest AICc was built with: maximum temperature of the warmest month (bioclim5), precipitation of the driest quarter (bioclim17), annual maximum of EVI (evi maximum), base level values of EVI (evi base level), slope, and distances to residential locations (d_resident) and to roads (d_road) (Tables S3 and S4). The seven predictors were therefore selected for the final MaxEnt modeling. We obtained average values of model evaluation indices after 20 replicates: training AUC = 0.966, test AUC = 0.953, maximum Kappa = 0.813, and maximum TSS = 0.882. High scores of model evaluation indices, both the threshold-independent and threshold-dependent, indicated that the habitat suitability model produced by MaxEnt performed excellently (Manel, Williams & Ormerod, 2001; Araújo et al., 2005).
Relevant variables
Evaluation of percent contribution of each variable to the model illustrated that three predictors had over 10% relative contribution to the habitat suitability model of the Chinese monal, contributing 78% collectively (Table 2). Precipitation of the driest quarter (bioclim17) made the largest contribution, followed by maximum temperature of the warmest month (bioclim5) and distance to the nearest residential locations. Similarly, these three predictors received the highest AUC values when used in isolation in the jackknife test (Table 2), indicating they are better at discriminating suitable from non-suitable habitat as compared with the other variables. The response of logistic probability of monal occurrence on the two critical climatic predictors were both unimodal, that the probabilities were at the peak at 31 mm for precipitation of the driest quarter and at 15 °C for maximum temperature of the warmest month (Figs. 2A and 2B). The response curve also showed that monals were more likely to occur at sites further away (>5,000 m) from the nearest human residential locations (Fig. 2C).
Relative importance of environmental variables in the habitat suitability model of the Chinese monal.
Percent contributiona
Jackknife of AUCb
bioclim17 36.2 0.856
bioclim5 31.0 0.840
d_resident 10.5 0.771
evi base level 8.8 0.689
evi maximum 6.0 0.683
slope 4.8 0.631
d_road 2.7 0.642
aThe relative contribution of each variable to predictive model, shown as mean value of 20 replicates.
bJackknife test of variable importance, expressed as AUC (area under the receiver operating characteristic curve) for models using each variable alone. A higher gain indicates a variable with more information for modelling when used in isolation, shown as mean value of 20 replicates.
bioclim17
precipitation of the driest quarter
bioclim5
maximum temperature of the warmest month
d_resident
distance to residential location
evi base value
annual base level value of EVI
evi maximum
annual maximum EVI
d_road
distance to roads
Figure 2: Response curves of habitat suitability for the Chinese monal (vertical axis) to the precipitation of the driest quarter (A), maximum temperature of the warmest month (B), distance to residential locations (C), and distance to roads (D).
The red lines illustrate the mean responses of 20 replicates and the blue shades showed the ± standard deviation.
Habitat status
We created a binary suitable/unsuitable habitat map after applying the maximum TSS threshold (where habitat suitable index = 0.208). The suitable habitats for the Chinese monal covered an area of 2,490 km2, corresponding to 9.48% of the entire Qionglai Mountains region. The majority of suitable habitats for the Chinese monal distributed in the central mountain regions, mainly stretching along the boundaries of Lixian-Wenchuan, Wenchuan-Baoxing, Xiaojin-Baoxing, and Baoxing-Tianquan (Fig. 3, Table 3). Ten existing nature reserves are located in the Qionglai Mountains, covering over a quarter of the entire region. Over 50% of the suitable monal habitats were situated within nature reserves. Wolong Nature Reserve provided the largest area of suitable habitats for the Chinese monal, while Heishuihe, Labahe, and Fengtongzhai Nature Reserve also had high proportions of suitable habitat (Table 4). Two general regions with large areas of potential suitable habitat were outside of any nature reserves: one in the northern region of Lixian County, and the other in northwest Baoxing County (Fig. 3).
Figure 3: Predicted suitable habitat for the Chinese monal and existing nature reserves in the Qionglai Mountains.
The geographic range of Chinese monal was delineated based on Lu (2015).
Our study represents the first attempt at predicting the suitable habitat of the Chinese monal. Variable analysis revealed that bioclimatic variables were the most influential predictors on the habitat suitability of the Chinese monal. Higher habitat suitability was constrained in narrow ranges of both precipitation of the driest quarter and maximum temperature of the warmest month, suggesting that Chinese monal was highly sensitive to climate under extreme periods. The monals appeared to prefer habitats far away from residential locations, suggesting human disturbance as a crucial pressure for the species. Although roads represent remarkable sources of disturbance to wildlife that could lead to road-kill (Mumme et al., 2000) and barrier effect (Shepard et al., 2008), the impact of roads was relatively weak in our niche model (Table 2). It is likely that a greater part of occurrence records were sampled in more easily accessible sites in proximity to roads (Fig. 1), and such a sampling bias had decreased the importance of roads disturbance in the model. Despite the sampling bias towards roads, we found an relation that habitat suitability increased with increasing distance from roads in the niche model predictions (Fig. 2D). As an explanation, we suggest that our predictive habitat suitability was more sensitive to bioclimatic conditions than to human disturbance; sites with bioclimatic conditions preferred by the Chinese monal might be infrequently crossed by roads.
Estimates of suitable habitat areas of the Chinese monal distributed in counties within the Qionglai Mountains.
County area (km2)
Suitable habitat area (km2)
Proportion of suitable habitat (%)
Wenchuana 3,589 852 23.74
Baoxing 3,124 544 17.41
Lixian 4,325 401 9.27
Xiaojin 5,568 235 4.22
Lushan 1,259 159 12.60
Tianquan 2,390 150 6.28
Dayi 1,207 80 6.63
Kangdingb 1,666 37 2.22
Chongzhoua 803 19 2.37
Ludingb 647 13 2.00
Qionglai 1,377 0 0
Dujiangyana 303 0 0
Total 26,258 2,490 9.48
aWenchuan, Dujiangyan and Chongzhou described here are only their west parts of the Min River.
bKangding and Luding described here are only their east parts of the Dadu River.
The predicted suitable habitats for the Chinese monal were highly fragmented. Specialized niche requirements (i.e., narrow climate preferences) constrained their suitable habitats to subalpine and alpine regions. High mountain ridges and deep valleys throughout the Qionglai Mountains separated the suitable haibtats into small and isolated patches, especially for those distributed in the north of Lixian County, south of Baoxing County, and the boundary area of Lixian-Xiaojin-Wenchuan County (Fig. 3). As a strong disturbance, human residential areas further restricted and separated the suitable habitats. The fragmentation might have negative effects on the Chinese monal, which has low dispersal ability (With & Crist, 1995), reducing the probability of genetic exchange (Höglund et al., 2011) and colonizing suitable empty patches (Stamps, Buechner & Krishnan, 1987) by increasing the resistance to individual movement between isolated habitat patches.
Estimates of suitable habitat areas of the Chinese monal in nature reserves.
Reserve area (km2)
Wolong 2,124 585 27.54
Miyaluo 1,951 181 9.28
Heishuihe 325 146 44.92
Siguniangshan 583 131 22.47
Caopo 517 128 24.76
Fengtongzhai 403 111 27.54
Labahe 239 69 28.87
Anzihe 110 18 16.36
Jintangkongyu 242 0 0
Zhailong 204 0 0
Total 6,698 1,364 20.36
Many subalpine meadows within the Qionglai Mountains are summer pasture for the grazing yaks. Grazing could lead to direct disturbance, accelerating habitat degradation and fragmentation, and increasing the probability of poaching (Lu et al., 1986; Ma, 1988; Long et al., 1998). Additionally, gathering of herbs for use in traditional Chinese medicine in spring and summer, especially the collection of Fritillaria spp., an important food source of the Chinese monal, could result in a reduction of food abundance and thus a indirect disturbance to the Chinese monal (Fuller & Garson, 2000; Lu, 2015). Our study, however, failed to incorporate these remarkable local threats into modeling due to the lack of data. If grazing and herb gathering are considered, the actual suitable monal habitat might be even smaller, more fragmented, and more variable than our prediction.
Our results raise concerns for the status of the Chinese monal in the Qionglai Mountains, and the species may be at greater risk than has previously been considered. As a typical high-montane species with large home range, the Chinese monal has the potential to serve as an umbrella or flagship species for high-montane ecosystems. Conservation of these ecosystems will likely contribute to the maintenance of regional biodiversity, at least for the montane Galliformes (Roberge & Angelstam, 2004; Rowland et al., 2006; McGowan, Zhang & Zhang, 2009). Based on our results, we have several conservation suggestions targeting the Chinese monal. Our prediction could guide future field surveys for locating new populations in the areas that were predicted to be suitable habitat but lack investigation (Raxworthy et al., 2003; Menon et al., 2010). The large and well-connected habitat patches distributed in the boundary area of Wenchuan, Baoxing, Lushan, and Dayi County appear to provide ideal and important habitats for the Chinese monal and should be treated as a priority area for conservation. However, a large portion stretching along the northern boundary of Baoxing County is unprotected by any nature reserves and lacks systematic survey (Fig. 3). Similarly, large ribbon-like patches of suitable habitats in northeast of Lixian County and north of Wenchuan County was also lacking protection and survey (Fig. 3). Our first suggestion, therefore, is to conduct ad hoc surveys for determining the actual occurrence of Chinese monal in these two areas. If there are indeed some populations in these two regions, we suggest that new nature reserves should be designated in order to fill these two obvious conservation gaps. The second suggestion is to study the dispersal capacity of the Chinese monal for further assessing habitat quality and fragmentation. Such ecological knowledge could be helpful for determining the actual distribution of animals in relation to the distribution of suitable environmental habitats (Pulliam, 2000; Lu et al., 2012). For instance, it will be useful to determine whether the Zagunao river valley is a geographic barrier that Chinese monals cannot cross through, and whether gene flow can occur between the monal populations isolated in the south and north of Baoxing County (Fig. 3).
Although human disturbance appeared to be a crucial pressure for Chinese monals (He et al., 1986), we found that Chinese monals did not respond avoiding roads. For instance, during our survey at Wenchuan in 2015, we observed that two Chinese monal pairs, almost at a daily bases, crossed provincial road 303 through the top of the Huayan tunnel (E102°58′, N30°51′; Fig. 1), a well-known location for shooting Chinese monal among wildlife photographers. Huayan tunnel has a length of 570 m, and the large area of natural shrub and meadow preserved on its top serves as a corridor for the monals. However, this does not mean that roads are not a significant threat for the species, as road-kill of Galliformes are not uncommon (Clevenger, Chruszcz & Gunson, 2003; D'Amico et al., 2015). Our third suggestion, therefore, is to build more corridors and green bridges across roads to facilitate road-crossing or dispersal by Chinese monals.
For the purpose of 'game food', Chinese monals had been often poached by local people before 1980s, which was considered as the main cause of a substantial decline of the species (He et al., 1986; Lu et al., 1986; Long et al., 1998; Lei & Lu, 2006). Unfortunately, we found self-made traps for capturing monals and other Galliformes during our surveys, both inside and outside nature reserves, suggesting that poaching is still continuing nowadays. Even though we found little evidence of human impact on monal habitat distribution, our field observation suggested that illegal hunting potentially threaten survival of the Chinese monals and their sympatric Galliform species. Moreover, other short-term and seasonal local disturbance such as yak grazing and herb collection could increase the probability of poaching (Lu et al., 1986; Ma, 1988; Long et al., 1998). Therefore, our fourth suggestion is to limit local disturbances, such as poaching, yak grazing, and herb collection, for maintaining existing populations and habitats of the Chinese monal as well as other montane Galliformes.
This study used the ecological niche modeling approach to predict current suitable habitat of the Chinese monal in Qionglai Mountains. Their suitable habitat was associated with about 31 mm precipitation of the driest quarter, about 15 °C of maximum temperature of the warmest month, and far from the nearest human residential locations (>5,000 m). The predicted suitable habitats of the Chinese monal was highly fragmented covering an area of 2,490 km2. A total of 54.78% of suitable habitat was under the protection of existing nature reserve network, but there were obvious conservation gaps as two regions with large area of well-connected suitable habitats were out of any nature reserve. Finally, this study provide conservation management suggestions in terms of ad hoc surveys targeting potential suitable habitats to determine occurrence of Chinese monals, more ecological studies regarding its dispersal capacity, establishment of more corridors and green bridges across roads in suitable habitats and limitation of local disturbances such as poaching, yak grazing, and herb collection.
All presence records of the Chinese monal in Qionglai Mountains from 2005 to 2015 (Raw data)
Source: GBIF, Global Biodiversity Information Facility; SHEN, Shen, Li & Xiang, 2010; AZH, Comprehensive scientific survey on Anzihe Nature Reserve; FTZ, Comprehensive scientific survey on Fengtongzhai National Nature Reserve; SAD,Sympatric animal database of the fourth national survey on giant panda; HSH, Infrared-triggered camera monitoring in Heishuihe Nature Reserve; LBH, Infrared-triggered camera monitoring in Labahe Nature Reserve; WL, Montane bird survey in Wolong National Nature Reserve.
DOI: 10.7717/peerj.3477/supp-1
Full set of environmental variables potentially related to habitat suitability of the Chinese monal
Performance of models with different sets of environmental variables
The optimized selection of environmental variables started with all 42 variables and stepwise removed the variables with high correlation with others (Pearson's correlation coefficients >0.7) and low contribution (<1%). Performance of each model was estimated by the sample-size-corrected Akaike information criterion (AICc). Model 7 had the lowest AICc value, indicating that the seven variables included in this model represents the most appropriate model complexity.
Process of the optimized environmental variable selection
The optimized selection of environmental variables simplified variables in a stepwise fashion: model 1 was built with all set of 42 variables, and 27 variables were removed in model 2 as they had low contribution (<1%) or high correlation (>0.7 or <0.7) with the highest contribution variable (bioclim17), and 6 variables were removed in model 3 as their low contribution or high correlation with the second high contribution variable (bioclim5), finally seven models were produced after repeating this process. Model 7 had the lowest AICc value (Table S3), indicating this model included the variables represent the most appreciate complexity. Therefore, these seven variables were selected as predictors for building the final MaxEnt model for Chinese monal habitat. Note: con, percent contribution; cor, Pearson's correlation coefficient. Check Table S3 for meaning and information of each environmental variable.
We thank Heishuihe Nature Reserve and Labahe Nature Reserve for providing monitoring data, and Fengtongzhai National Nature Reserve, Wolong National Nature Reserve, Anzihe Nature Reserve for the supports provided during the fieldworks. We are grateful to Qiang Dai and Tingting Yan for their recommendations on methodology, and Liang Dou, Nan Yang, Xiang Yu, Bo Zhang for their assistance in the fieldworks. Zhengyang Wang from Harvard University helped to correct the English writing of the manuscript.
Additional Information and Declarations
The authors declare there are no competing interests.
Bin Wang performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables.
Yu Xu conceived and designed the experiments, performed the experiments, reviewed drafts of the paper.
Jianghong Ran conceived and designed the experiments.
The following information was supplied regarding data availability:
The raw data of this research is uploaded as Table S1.
Funding for this research was provided by the National Natural Science Foundation of China (No. 31301896); the New Teacher Fund for Doctor Station of Ministry of Education of China (No. 20120181120087). There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Akaike H. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19:716-723
Alcaraz-Segura D, Paruelo JM, Epstein HE, Cabello J. 2013. Environmental and human controls of ecosystem functional diversity in temperate South America. Remote Sensing 5:127-154
Allouche O, Tsoar A, Kadmon R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) Journal of Applied Ecology 43:1223-1232
Araújo MB, Pearson RG, Thuiller W, Erhard M. 2005. Validation of species–climate impact models under climate change. Global Change Biology 11:1504-1513
Austin MP. 2002. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling 157:101-118
BirdLife International. 2015. Species factsheet: Chinese monal Lophophorus lhuysii. (accessed November 2015 )
Botero-Delgadillo E, Páez CA, Bayly N. 2012. Biogeography and conservation of Andean and Trans-Andean populations of Pyrrhura parakeets in Colombia: modelling geographic distributions to identify independent conservation units. Bird Conservation International 22:445-461
Chen YH. 2013. Conservation priority for endemic birds of mainland China based on a phylogenetic framework. Chinese Birds 4:248-253
CITES. 2016. Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) Appendices I, II and III.
Clevenger AP, Chruszcz B, Gunson KE. 2003. Spatial patterns and factors influencing small vertebrate fauna road-kill aggregations. Biological Conservation 109:15-26
Coetzee BWT, Robertson MP, Erasmus BFN, Van Rensburg BJ, Thuiller W. 2009. Ensemble models predict Important Bird Areas in southern Africa will become less effective for conserving endemic birds under climate change. Global Ecology and Biogeography 18:701-710
Cohen J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20:37-46
Costa GC, Nogueira C, Machado RB, Colli GR. 2010. Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot. Biodiversity and Conservation 19:883-899
D'Amico M, Román J, Reyes LDL, Revilla E. 2015. Vertebrate road-kill patterns in Mediterranean habitats: who, when and where. Biological Conservation 191:234-242
Elith J, Graham CH, Anderson RP, Dudík M, Ferrier S, Guisan AJ, Hijmans R, Huettmann FR, Leathwick J, Lehmann A, Li JG, Lohmann L. 2006. Novel methods improve prediction of species' distributions from occurrence data. Ecography 29:129-151
Fielding AH, Bell JF. 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24:38-49
Freeman EA, Moisen G. 2008. PresenceAbsence: an R package for presence-absence model analysis. Journal of Statistical Software 23:1-31
Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X. 2010. MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114:168-182
Fuller RA, Garson PJ. 2000. Pheasants: status survey and conservation action plan 2000–2004. Gland: IUCN.
Guisan A, Zimmermann NE. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135:147-186
He FQ, Lu TC. 1985. Ecology of the Chinese monal in winter. Zoological Research 4:345-352 (in Chinese)
He FQ, Lu TC, Lu CL, Cui XZ. 1986. Study on the breeding ecology of the Chinese monal. Acta Ecologica Sinica 2:186-192 (in Chinese)
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965-1978
Höglund J, Larsson JK, Corrales C, Santafé G, Baines D, Segelbacher G. 2011. Genetic structure among black grouse in Britain: implications for designing conservation units. Animal Conservation 14:400-408
Hu JC. 2001. Research on the giant panda. Shanghai: Shanghai Publishing House of Science and Technology. (in Chinese)
IUCN. 2015. IUCN Red List of Threatened Species. (accessed November 2015 )
Jiménez-Valverde A, Lobo JM. 2007. Threshold criteria for conversion of probability of species presence to either–or presence–absence. Acta Oecologica 31:361-369
Jönsson P, Eklundh L. 2002. Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing 40:1824-1832
Jönsson P, Eklundh L. 2004. Timesat—a program for analyzing time-series of satellite sensor data. Computers and Geosciences 30:833-845
Jueterbock A. 2015. 20 R package MaxentVariableSelection: selecting the best set of relevant environmental variables along with the optimal regularization multiplier for Maxent niche modeling. https://cran.rproject.org/web/packages/MaxentVariableSelection/index.html
Jueterbock A, Smolina I, Coyer JA, Hoarau G. 2016. The fate of the Arctic seaweed Fucus distichus under climate change: an ecological niche modeling approach. Ecology and Evolution 6:1712-1724
Kalkhan MA. 2011. Spatial statistics: geospatial information modeling and thematic mapping. New York: CRC Press.
Last of the Wild Data Version 2. 2005. Global Human Influence Index (HII). Wildlife Conservation (WCS) and Center for International Earth Science Information Network (CIESIN) (accessed 13 July 2016 )
Lei FM, Lu TC. 2006. China endemic birds. Beijing: Science Press. (in Chinese)
Liu C, Berry PM, Dawson TP, Pearson RG. 2005. Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28:385-393
Liu C, White M, Newell G. 2013. Selecting thresholds for the prediction of species occurrence with presence-only data. Journal of Biogeography 40:778-789
Long TL, Shao KQ, Guo G, Cheng CY, Zou XY, Landel H, Rimlinger D, Zhou FL. 1998. Field tracking and ecological observation of the Chinese monal in winter. Sichuan Journal of Zoology 17:104-105 (in Chinese)
Loveland TR, Belward AS. 1997. The IGBP-DIS global 1 km land cover data set, DISCover: first results. International Journal of Remote Sensing 18:3289-3295
Lu TC. 2015. Lophophorus lhuysii Chinese monal. In: Zheng GM, ed. Pheasants in China. Beijing: Higher Education Press. 337-351 (in Chinese)
Lu N, Jia CX, Lloyd H, Sun YH. 2012. Species-specific habitat fragmentation assessment, considering the ecological niche requirements and dispersal capability. Biological Conservation 152:102-109
Lu TC, Liu RS, He FQ, Lu CL. 1986. Ecological studies on Chinese monal. Acta Zoologica Sinica 3:273-279 (in Chinese)
Ma GY. 1988. Observation on the Chinese monal in Gansu Province. Sichuan Journal of Zoology 7:41-42 (in Chinese)
Ma GY. 1989. Distribution and ecological observation of the Chinese monal in Gansu Province. Journal of Tianshui Normal University 1:101-104 (in Chinese)
MacKinnon JR, Phillipps K, He FQ. 2000. A field guide to the birds of China. Oxford: Oxford University Press.
Madge S, McGowan PJ, Kirwan GM. 2002. Pheasants, partridges and grouse: a guide to the pheasants, partridges, quails, grouse, guineafowl, buttonquails and sandgrouse of the world. London: Christopher Helm.
Manel S, Williams HC, Ormerod SJ. 2001. Evaluating presence-absence models in ecology: the need to account for prevalence. Journal of Applied Ecology 38:921-931
Marcondes RS, Del-Rio G, Rego MA, Silveira LF. 2014. Geographic and seasonal distribution of a little-known Brazilian endemic rail (Aramides mangle) inferred from ocurrence records and ecological niche modeling. The Wilson Journal of Ornithology 126:663-672
McGowan PJ, Zhang YY, Zhang ZW. 2009. Galliformes–barometers of the state of applied ecology and wildlife conservation in China. Journal of Applied Ecology 46:524-526
Menon S, Choudhury BI, Khan ML, Peterson AT. 2010. Ecological niche modeling and local knowledge predict new populations of Gymnocladus assamicus, a critically endangered tree species. Endangered Species Research 11:175-181
1989. Checklist of Wild Animals of National Priority Protection
Mittermeier RA, Turner WR, Larsen FW, Brooks TM, Gascon C. 2011. Global biodiversity conservation: the critical role of hotspots. In: Zachos FE, Habel JC, eds. Biodiversity hotspots: distribution and protection of priority conservation areas. Berlin: Springer-Verlag. 3-22
Morrison ML, Marcot B, Mannan W. 2012. Wildlife-habitat relationships: concepts and applications. Washington, D.C.: Island Press.
Mota-Vargas C, Rojas-Soto OR, Lara C, Castillo-Guevara C, Ballesteros-Barrera C. 2013. Geographic and ecological analysis of the bearded wood partridge Dendrortyx barbatus: some insights on its conservation status. Bird Conservation International 23:371-385
Mumme RL, Schoech SJ, Woolfenden GE, Fitzpatrick JW. 2000. Life and death in the fast lane: demographic consequences of road mortality in the florida scrub-jay. Conservation Biology 14:501-512
Parolo G, Rossi G, Ferrarini A. 2008. Toward improved species niche modelling: Arnica montana in the Alps as a case study. Journal of Applied Ecology 45:1410-1418
Pearson RG, Raxworthy CJ, Nakamura M, Townsend PA. 2007. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography 34:102-117
Peterson AT, Ball LG, Cohoon KP. 2002. Predicting distributions of Mexican birds using ecological niche modelling methods. Ibis 144:E27-E32
Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190:231-259
Phillips SJ, Dudík M. 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161-175
Pulliam HR. 2000. On the relationship between niche and distribution. Ecology Letters 3:349-361
2015. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. software
Rahman AF, Sims DA, Cordova VD, El-Masri BZ. 2005. Potential of MODIS EVI and surface temperature for directly estimating per-pixel ecosystem C fluxes. Geophysical Research Letters 32:156-171
Raxworthy C, Martínez-Meyer E, Horning N, Nussbaum R, Schneider G, Ortega-Huerta M, Peterson AT. 2003. Predicting distributions of known and unknown reptile species in Madagascar. Nature 426:837-841
Requena-Mullor JM, López E, Castro AJ, Cabello J, Virgós E, González-Miras E, Castro H. 2014. Modeling spatial distribution of European badger in arid landscapes: an ecosystem functioning approach. Landscape Ecology 29:843-855
Roberge JM, Angelstam P. 2004. Usefulness of the umbrella species concept as a conservation tool. Conservation Biology 18:76-85
Rowland MM, Wisdom MJ, Suring LH, Meinke CW. 2006. Greater sage-grouse as an umbrella species for sagebrush-associated vertebrates. Biological Conservation 129:323-335
Shen Y, Li B, Xiang Y. 2010. Searching the Chinese monal after the earthquake. The Nature 6:7-9 (in Chinese)
Shepard DB, Kuhns AR, Dreslik MJ, Phillips CA. 2008. Roads as barriers to animal movement in fragmented landscapes. Animal Conservation 11:288-296
Stamps JA, Buechner M, Krishnan V. 1987. The effects of edge permeability and habitat geometry on emigration from patches of habitat. American Naturalis 192:533-552
Swanepoel LH, Lindsey P, Somers MJ, Hoven WV, Dalerum F. 2013. Extent and fragmentation of suitable leopard habitat in South Africa. Animal Conservation 16:41-50
Swets JA. 1988. Measuring the accuracy of diagnostic systems. Science 240:1285-1293
Tobón-Sampedro A, Rojas-Soto OR. 2015. The geographic and seasonal potential distribution of the little known Fuertes's Oriole Icterus fuertesi. Bird Conservation International 25:489-502
Tuanmu MN, Vina A, Roloff GJ, Liu W, Ouyang ZY, Zhang HM, Liu JG. 2011. Temporal transferability of wildlife habitat models: implications for habitat monitoring. Journal of Biogeography 38:1510-1523
Warren DL, Glor RE, Turelli M. 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33:607-611
Warren DL, Seifert SN. 2011. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecological Applications 21:335-342
Warren DL, Wright AN, Seifert SN, Shaffer HB. 2014. Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern. Diversity and Distributions 20:334-343
With KA, Crist TO. 1995. Critical thresholds in species' responses to landscape structure. Ecology 76:2446-2459
Zhang T. 1995. Distribution and ecology of Chinese monals in Baishuijiang nature reserve Gansu. Chinese Journal of Zoology 30:25-28 (in Chinese)
Learn more about Q&A
Add a link
Just enter your email
Peer Review history
See citing articles 21
Visitors click for details
PDF Save to Mendeley Read in ReadCube RIS XML BibTeX
Your download will start in a moment...
Typos, corrections needed, missing information, abuse, etc
PeerJ promises to address all issues as quickly and professionally as possible. We thank you in advance for your patience and understanding.
TypoMissing or incorrect metadataQuality: PDF, figure, table, or data qualityDownload issuesAbusive behaviorResearch misconductOther issue not listed above
Follow this publication for updates
"Following" is like subscribing to any updates related to a publication. These updates will appear in your home dashboard each time you visit PeerJ.
You can also choose to receive updates via daily or weekly email digests. If you are following multiple publications then we will send you no more than one email per day or week based on your preferences.
Note: You are now also subscribed to the subject areas of this publication and will receive updates in the daily or weekly email digests if turned on. You can add specific subject areas through your profile settings.
Change notification settings or unfollow
Usage since published - updated daily
Top referrals unique visitors
From bookmark or typed URL
From PeerJ Content Alert Emails
Articles citing this paper
Loading citing articles…
21 Citations Views Downloads


text:
Louisville's Sports Station
790 KRD - Louisville's Sports Station
The Red Zone with Nick Coffey The Herd with Colin Cowherd Ramsey & Rutherford Soccer City presented by LouCity
iHeart Live
Listen on iHeartRadio Join us on Facebook Advertise Events Calendar Community
Advertise on 790 KRD, Get Results
New York Man Files Lawsuit After Getting Hit In The Groin At Batting Cage
posted by Bill Galluccio - Oct 2, 2019
A New York City lawyer has filed a lawsuit against Chelsea Piers after he suffered a severe injury when he was hit in the groin by a baseball while taking some swings in the batting cage. 52-year-old Ethan Brecher says that the pitching machine started firing off 75-mile-per-hour fastballs seconds after he stepped into the cage and the first one struck him in the thigh and then hit his testicles.
"I pick up the bat, I take a step, I'm feeling really good and all of a sudden I was blindsided by a 75-mph ball that hit the interior of my right thigh and ricocheted to my testicle and I fell down in agony," Brecher told the New York Post.
While he was writhing around in pain on the ground, the machine continued to fire nine more baseballs in his direction.
"It was the worst pain. On a scale of 1 to 10, it was like a billion. It was unimaginable," he said.
Brecher was rushed to the hospital where an ultrasound found evidence of bruising and internal bleeding. He was prescribed Oxycontin for the pain and was told that the damage could result in infertility.
He blames Chelsea Piers for programming the machine to start firing baseball seconds after a person steps into the cage.
"What they should have done is given me longer before the pitch was launched. I don't think I was ambling or doing anything, particularly slowly. I had been hitting the balls hundreds of times [over the summer], so I knew how long it would take," Brecher explained.
He is seeking $100,000 in damages and wants Chelsea Piers to alter their machines to give people more time to get ready to take swings in the cage.
"This should be taken as a warning that there is a flaw in the mechanism here. If a little kid was hit in the head and wasn't wearing a helmet, they could have died," he said.
WKRD Public Inspection File
WKRD Political File
Advertise with 790 KRD, Get Results


High School Experience: I went to a secondary school in inner-city London. It was mostly Black students. It was a pretty good school where it was. There were seven grades in our school, so for years 7 to 11 there were about 125 people, then in year twelve there were about 100 people and then in year 13, there were about 60. I graduated with like 60 people in my class. It's not that there is a drop-off, it's that people go to different schools for the last two years. There are more options for secondary school the last two years.
Extracurricular Activities: I'm a part of the Charleston House of Interfaith Cooperation which is all about getting people of different religions and nonfaith to get together to speak about things going on in the U.S. or in the world. I'm also part of Model UN, so I've been to a couple of conferences with them.
Yeah, Charleston was probably my favorite one to go to. I haven't been able to go this semester because I have a class when they meet. It had a big impact because it really made me think about other peoples' perspectives and religions. They did something really cool for me. Over the summer this a conference called Interfaith Youth Core and it's for people who are part of interfaith groups at colleges from all over the US. Trinity flew me out from London to Chicago which was pretty cool. It was for two days in August and I got to speak to people from all over the US, so that was really impactful.
That really depends on which semester and how many classes I'm taking. I only took one class per semester in my first year, and then I took two last semester and one this semester. They get harder as you progress on. I'm in one of the core 300 level courses this semester, Macroeconomic Theory, and that's a lot even though it's just one class. We meet for 50 minutes Monday, Wednesday and Friday and she gives us homework every class. It can range from a long problem set, a couple of questions, or reading the textbook. I took Stats for Economics last semester and I had loads of problem sets. Econ's been hard, it's been a lot of work.
Is there anything the Economics department does well or poorly?
How would you describe the learning environment? Is it collaborative or competitive?
The professors I've had haven't used curves in any courses, so it's really good for working with other students. I feel comfortable asking people for help and studying in groups. Often, they let you hand in homework with multiple people on one sheet. There's also a lot of support in terms of TA's and going to office hours.
I always knew I wanted to do Economics because in the UK system you have to apply with a major to universities. However, it's been really, really difficult so I wish I came in with more of an open mind because I could have done other studies which might have been less nasty. I would say that people, especially people from the UK, should come with an open mind about what they're going to major in because we have to choose really early in the UK.
Freshman: Freshman year I lived in Elton, which was one of the 6 freshman dorms at Trinity. I think it's one of the best. I lived in a two-room double, so the way that worked is you'd enter through one of the bedrooms and then there was another door that you could go in and that'd be her room. We'd just open the door up to talk to each other and close the door when we were going to bed. I think that was one of the best room setups you can have as a freshman. There were about 20 other freshmen on my floor and we had a communal bathroom.
Sophomore: My lottery number was bad because I had a good room freshman year, so I combined numbers with 3 different people and we ended up in a four-person suite in Summit South. Everybody had their own bedroom and then there's a bathroom and a living room.
My housing has been really good.
It's fine, I haven't had any experiences myself. We get emails whenever there is something has happened, but nothing crazy has happened that has made me feel unsafe. In terms of sexual harassment and sexual assault, I haven't really experienced anything.
I don't go off campus a lot to eat. I think often at Trinity there is a bubble and people will stay on campus. Sophomore year I have gone out more, but I don't know if I've established a favorite restaurant.
Maybe Wal Mart? [laughs]. We have a shuttle that goes to different places, like Wal Mart and a mall and some other places, but I like Wal Mart a lot.
Pros: (1) The Greyhound and Peter Pan can take you to Boston or New York pretty easily. It's like two hours to both.
(2) Broadway shows come through Hartford a lot, so I've seen The Color Purple, Jersey Boys, and The Book of Mormon at the Bushnell.
Cons: It can get boring sometimes. Being from London, this isn't a city to me. There are [about 124,000] people. There aren't a lot of things to do if you don't have a car.
What kind of weekend activities or nightlife do you participate in at Trinity?
I'm not a big fan of the nightlife honestly. Coming from the UK, you can start drinking when you're 18, so, back home I can go to clubs and it's fun, there are big spaces, there's good music and different rooms so it doesn't get old. Whereas at Trinity, the fraternities are pretty small and they can be a bit gross, but I guess that's fraternities everywhere. I just don't really like it that much, and I don't like the music they play personally. There is a lot of nightlife here. People go out Tuesday, Thursday, Friday, and Saturday. Freshman year I went out a lot and even last semester I went out a lot, but this semester I haven't really been interested.
What alternatives to going to a party do you like to do?
There is the Bushnell Theatre and they have shows there. I don't really go to any concerts or try to go clubbing because I'm not 21 yet. Maybe senior year that will change, the age thing is annoying.
I'd go to a hangout in a friend's room, then we'd go walk to Vernon Street where all the nightlife is, and go into a frat. It depends where you go, some were really packed, some were empty, so we'd probably go to a few. Things would start dying down around 1AM. Things end pretty early, I think that's an American thing.
How was blending into the social scene as an international student?
I think I had it better because I was from the UK and I speak English as my first language and people are obsessed with British accents, so that can make people want to talk to me. It can be hard because people are different here, definitely different than they are in England. They're a different type of person. People can be kind of rude here, so that has taken some adjusting. Also realizing that somebody isn't necessarily being rude, that's just how they are. Like they say, "Hey! How are you," but just walk away like they don't want to hear your answer. It's been fine so far. I have a lot of friends and having jobs and being involved in plays has helped me find friends.
I think a lot of students who don't speak English as their first language can be more isolated sometimes, but it depends on how they put themselves out there. Some international students stick with students from the same place and some try to blend in and be friends with Americans. It depends on what you want.
Were there any parts of Trinity or American college overall that surprised you?
Yeah, I didn't realize how badly Americans can handle their drinks [laughs]. I feel like when Americans go to college it's the first time they can drink away from their parents so they go crazy. So that was surprising and took some getting used to, but also entertaining [laughs].
I was also surprised by the workload freshman year. I had to work really hard, whereas my friends in the UK were chilling because in their first and second year their grades don't count towards their GPA, which is ridiculous. Here, I had homework every night. It was very hard, it was a massive jump, while for my friends at home it was a massive jump. I would see their Snapchats of them going out all the time but I would be studying every night.
They all kind of happened randomly. I'm not really close friends with the people I met through orientation. I met them through doing plays, being in class, international orientation. I kind of stumbled across people. I wasn't actively looking for friends when I met my friends, I just kind of clicked with them.
I think I did a lot of investigative work before I came here because Trinity was not my top choice and was actually the only school I got into in the US. I was in a program in the UK for people that wanted to go to US universities and they connected us with people already here. I sent a lot of questions to people here so I kind of knew most things. It wasn't a massive shock, I was just surprised how mean people could be here. In terms of meeting somebody one day and then the next day them pretending that they don't know who you are, or being in a class with somebody one semester and then the next semester it's like you never knew each other. And then I wish I knew how bad the nightlife would be for someone like me from where I'm from. I just like can't engage. I'm going abroad next semester so maybe when I get back I can go somewhere that isn't a frat.
Maybe they can look at the frats more and know what they look like because they're quite small here. If they could go to the south part of campus and see the suites that would be nice. If they could see a dorm that might change their mind a lot because there are some really, really nice dorms on that side, or seeing a townhouse which you can get through the housing lottery. Going to a class might be good for you as well, especially if you're an international student and already know what you want to major in.
What is something that we haven't touched on that would be important for a prospective international student to know?
It's not really like the movies. I've watched a lot of American television and I don't think Trinity is like the movies. I think a lot of the movies are based in California and have pool parties every weekend and Trinity is not like that. The school's also going to be harder than they expect. It's been a hard journey but hopefully will be rewarding at the end.
1) It's a good school academically. There is good support academically, if you are having trouble there is help there. A lot of [Economics majors] end up working on Wall Street.
2) The career department is really, really good for helping people get internships.
3) It depends on what you like, some people really like the nightlife here and going to frats and stuff. And even if you're not into that there are lots of things on the weekends. I personally really love going to bingo, and they do a lot of stuff like karaoke. There are a lot of ways to win money, like last week there was a lip sync battle and the first prize won $500 and the second prize won $250 so that was really cool. So, there are lots of ways to have fun even if you don't like the nightlife.
1) As a freshman, you're not allowed to have a car, but I think it's like that at a lot of places. It does make you feel like you're in a bubble. That was hard for me freshman year not leaving campus much, but sophomore year I could go off campus more. Having friends with cars is really nice.
2) It's not the most diverse school, but that is changing. They just came up with a new strategic plan to help change that.
3) It's not the most fun place if you come from a massive city. It's not really urban, it's a town city. If you want a city life it isn't for you.


text:
1940 Articles Buried Deceased Police Former Police Funeral Gender GPS Location Male No NSW Of Church service Of event Of grave Photos State Wall of Remembrance Year
John Jock McDONALD
( late of Hampton )
New South Wales Police Force
Regd. # ? "POSSIBLY" 6540
Rank: Sergeant – retired
Stations: ?, O.I.C. Central Police Barracks
Service: From ? ? 1903 to ? ? 1924 = ? years Service
Awards: ?
Born: ? ? 1866? in Forfarshire, Scotland
Died on: Friday 24 May 1940
Death location: Lithgow Hospital, NSW
Cause: ?
Funeral date: Saturday 25 May 1940 @ 2.30pm
Funeral location: Messrs. Matthews and Lemon's parlors, Mort-street, Lithgow
Buried at: Presbyterian portion, Lowerther Cemetery, Jenolan Caves Rd, Hartley, NSW
Memorial location:
John Jock McDONALD grave
[alert_yellow]JOHN is NOT mentioned on the Police Wall of Remembrance[/alert_yellow] *NEED MORE INFO
[divider_dotted]
Lithgow Mercury ( NSW ) Friday 24 May 1940 page 2
MR. JOHN McDONALD
Death of Veteran Police Officer
Mr. John McDonald, of Hampton, who died in Lithgow hospital early this morning at the age of 74, was for a long time in charge of the Central police barracks, Central-street, Sydney. Many senior officers of the force passed through his hands, including the Commissioner of Police ( Supt. MacKay ) ; between the two there was always a close friendship.
The late Mr. McDonald, a native of Scotland, retired from the force 15 years ago with the rank of sergeant. All his service took place in the metropolitan district.
He had lived at Hampton since his retirement, spending his time at a number of guest-houses. As in Scotland, he was an enthusiastic mountain-climber, and spent much of his time on walking expeditions. He took a keen interest in the district and its progress, and made many friends. He was unmarried.
Mr. McDonald was taken ill 13 months ago, and spent five months in Dudley Hospital, Orange. Shortly after his return to Hampton he was confined to his bed, and was admitted to the Lithgow institution.
The funeral has been arranged for to-morrow afternoon, and will leave Messrs. Matthews and Lemon's parlors, Mort-street, after a service, commencing at 2.30, for the Presbyterian portion of Lowther cemetery. The Commissioner of Police, owing to the ill-health of Mrs. MacKay, will not, be able to attend, but will be represented by Inspector J.J. Fogarty, of Bathurst. Katoomba, Bathurst and Lithgow police will be present.
http://trove.nla.gov.au/newspaper/rendition/nla.news-article220788432.txt
Mudgee Guardian and North Western Representative ( NSW )
Thursday 30 May 1940 page 2 of 12
Mr. John McDonald, of Hampton, died in Lithgow Hospital last Thursday, at the age of 74.
He was for a long time in charge of the Central Police Barracks. Many old Mudgee police officers passed through his hands.
The deceased was taken ill thirteen months ago, and spent five months in Dudley Hospital, Orange.
http://trove.nla.gov.au/ndp/del/article/162211189
The Sydney Morning Herald Wednesday 5 June 1940 page 2 of 22
Probate Jurisdiction – In the Will of JOHN McDONALD late of Hampton in the State of New South Wales, Retired Sergeant of Police, deceased. – Application will be made after fourteen days from the publication hereof that Probate of the last Will of the abovenamed deceased dated the twenty-fifth day of October one thousand nine hundred and thirty-seven may be granted to the PUBLIC TRUSTEE the Executor named in the said Will and all notices may be served at the under-mentioned Proctors for the Executor, 88 Pitt St, Sydney.
http://trove.nla.gov.au/ndp/del/article/17677931
Scone Advocate (NSW) Friday 29 July 1921 page 2
OBITUARY.
THE LATE MR. PAUL HAMMON.
The remains of the late Mr. Paul Hammon, a universally popular young resident of Scone for a number of years, and whose sad and untimely death was referred to in last Tuesday's issue, were laid to rest in the Randwick Cemetery on Monday last. The chief mourners were Mr.E. Nelson (his pal), and Mrs. Hyort and family, (for his mother), Mr. and Mrs. Larsend. Thirty-eight members of the Police Force headed the cortege to Randwick, Inspector Young representing No. 4 Police Station and Sergt. McDonald attending on behalf of Central Police Barracks. The Rev. Walker conducted the burial service. Wreaths were forwarded from Comrades of No. 4 Police Station and of Central Police Barracks, Executive of the Police Association, Mrs. Hyort and family (on behalf of his mother), Mr. E. Nelson (Scone), Mr. Quist (Scone), Mr and Mrs. Larsend (Danish Club), Mrs; P. H. Head and children, Mr. Dalhroad, Mr. Dalberg, Danish Club " Thor, " Mrs. Hill and family, and Loyal Strangers' Friend Lodge, No. 121, Scone.
On 5 August 2016 I made numerous Google enquiries for Paul HAMMON to see if he was an actual member of NSW Police Force or simply an associate of the Police Force. I was NOT able to locate ANY further information about him.
The Sun ( Sydney, NSW ) Thursday 10 November 1921 page 7
CALF ARRESTED
Bellowing in the Streets Sleepless Men and Prisoners
A calf was arrested about midnight and interned at the central barracks. It bellowed for the rest of the night, and greatly annoyed over 100 men in their quarters, and many prisoners in the cells.
The story of the calf's doings have been told from police station to police station throughout the metropolitan district.
When Superintendent Nolan heard of the "arrest" from sergeant MacKay, who had been furnished with a brief report of the affair, he had to laugh, even if there are men on beat duty in the city to-day who are weary from want of sleep.
The arrest was made by Constables Shirlow and Collard while they were patrolling the Darling Harbor side of the city. As they rode along towards Market-street, they spotted the calf, which commenced to bellow loudly. " We'll arrest her, " said one. ' Of course, we can't put her in the cells at the Central, but will shove her into the coalhouse. ' " Right you are," replied the second policeman. " In goes Cattle, and the charge in creating a disturbance. She makes enough noise, Her voice is certainly a contralto. "
Procuring a piece of rope from a yard close by, Shirlow and Collard secured the calf, and, wheeling their bicycles, they moved it alone to the Central Police Station.
" AN IMPORTANT ARREST "
As the two policemen, bicycles, and calf entered the wide-open gates of the police station a wag called out to Sergeant Iverack, " An important arrest, sergeant. The prisoner is coming through the gates."
" We'll have to put her in the coal-house ", remarked one of the men.
" You can't do that very well," was a reply, " It's nearly 1 a.m. and the men are all asleep. She's started her bellowing again, and she will wake them up."
However, she was placed in the coal-house.
She went on singing her song, which lasted till daybreak.
MEN MUST SLEEP
Sergeant "Jock" McDonald, who has charge of the central barracks, became alarmed. Rushing downstairs from the men's quarters he demanded to know what was going on.
" My men are waking up. They must have their sleep, and if this goes on they will not be fit for duty, " he called out.
Nothing could he done. There was no other place to put her. She finished up about 6 a.m., when she was removed to the police depot in a motor van.
One old woman who had been arrested for drunkenness the previous night thought she would help the calf vocally, and she added a song or two.
The poundkeeper at Botany was asked yesterday to take the calf. He refused. "
She's too bony, " he remarked, " and I could do nothing with her. "
Calfie is at the police depot. The police do not know what to do with her. They want her owner to take her away.
" She had no milk yesterday, and seems to want some, " was the remark of a man at the depot this morning. " I think by the look of her, she would want a thousand gallons a day to make her look well.
The calf is believed to have strayed away from a wharf.
http://trove.nla.gov.au/newspaper/article/223483793
The Sun ( Sydney, NSW ) Tuesday 2 September 1924 page 9
SERGEANT McDONALD, who has had charge of the Central Police barracks for over nine years. He is on leave of absence prior to retirement from the force. He joined the service in 1903.
← Charles Albert DEIN
Duncan J. McDONALD →


Meaning and origin of the Norse baby name Vali. Meaning of Vali. What does Vali mean? Vali origin. Information about Vali.
Meaning of Vali: Son of Odin.
Meaning of Vali, Information about First Name Vali, Norse Origin Names, Choose babynames from thousunds of names data base from various regions and coutries.


>> connect to the server to fetch a lot of data.
> repositories, often accessed internationally via VPN.
>> is saying that FSFS is what makes it so slow.
> Not in any way that a remote user could ever notice! The remark is baseless.
Or, maybe their systems are misconfigured.


text:
Australian first – Perth company harvests medicinal cannabis for commercial use
By Little Green Pharma - May 9, 2018
Australia's first crop of medicinal cannabis for commercial use was harvested last week by Perth based phytopharmaceutical company Little Green Pharma.
Little Green Pharma is a private entity specialising in cultivating and producing high quality, locally grown medicinal cannabis. The company announced in December 2017 it was cultivating its first crop at its secure growing facility south of Perth. The cultivation marked the first time medicinal cannabis had been grown in WA.
Little Green Pharma Managing Director, Fleta Solomon, said the company had reached another great milestone towards its goal of producing clean, southwest grown medicinal cannabis.
"We will now dry the flower and, shortly after, extract a sample of resin to send to an approved certified laboratory," Ms Solomon said. "Testing the resin for purity and quality assurance is mandatory."
Strict controls around the production of medicinal cannabis meant the company could not reveal the location of its secure hydroponic growing facility, although the plants being cultivated generally had lower levels of the psychoactive THC cannabinoid and higher levels of the non-psychoactive CBD cannabinoid compared to recreational marijuana.
Ms Solomon said the Directors of Little Green Pharma had recently returned from a fact-finding mission on the medicinal cannabis industry which took them to Israel, Canada and the USA. They looked at best practice growing and manufacturing facilities on a large scale and would now proceed to raise funds to enable the company to ramp up production in WA.
"Little Green Pharma's long-term aim is to build a world class facility on our doorstep right here in WA," she said.
"With the advantage we have of being the first mover in Australia combined with the Australian Government's vision of our nation being the world's premier exporter of high grade medicinal cannabis and the growing number of countries legalising it, we believe it is the perfect time to expand our operations."
Ms Solomon said Little Green Pharma planned to participate in medical research on medicinal cannabis and was in end stage talks with reputable research institutions in WA and overseas.
Little Green Pharma is the only company in WA with a licence and permit from the Office of Drug Control to grow locally.