Estimating dyad association probability under imperfect and heterogeneous detection

In animal behaviour studies, association indices estimate the proportion of time two individuals (i.e. a dyad) spend in association. In terms of dyads, all association indices can be interpreted as estimators of the probability that a dyad is associated. However, traditional indices rely on the assumptions that the probability to detect a particular individual (p) is either approximately one and/or homogeneous between associated and not associated individuals. Based on marked individuals we develop a likelihood based model to estimate the probability a dyad is associated (ψ) accounting for p < 1 and possibly varying between associated and not associated individuals. The proposed likelihood based model allows for both individual and dyadic missing observations. In addition, the model can easily be extended to incorporate covariate information for modeling p and ψ. A simulation study showed that the likelihood based model approach yield reasonably unbiased estimates, even for low and heterogeneous individual detection probabilities, while, in contrast, traditional indices showed moderate to strong biases. The application of the proposed approach is illustrated using a real data set collected from a population of Commerson's dolphin (Cephalorhynchus commersonii) in Patagonia Argentina. Finally, we discuss possible extensions of the proposed model and its applicability in animal behaviour and ecological studies.     

Estimating influence of stocking regimes on livestock grazing distributions

Livestock often concentrate grazing in particular regions of landscapes while partly or wholly avoiding other regions. Dispersing livestock from the heavily grazed regions is a central challenge in grazing land management. Position data gathered from GPS-collared livestock hold potential for increasing knowledge of factors driving livestock aggregation patterns, but advances in gathering the data have outpaced advancements in analyzing and learning from it. We fit a hierarchical seemingly unrelated regression (SUR) model to explore how season of stocking and the location where cattle entered a pasture influenced grazing distributions. Stocking alternated between summer on one side of the pasture one year and fall on another side of the pasture the next year for 18 years. Waypoints were recorded on cattle for 50 d each year. We focused our analysis on the pasture's 10 most heavily grazed 4-ha units, because these units were the most prone to negative grazing impacts. Though grazing of the study units was always disproportionately heavy, it was much heavier with the summer than fall stocking regime: Bayesian confidence intervals indicate summer grazing of study units was approximately double the average fall grazing value. This is our core result, and it illustrates the strong effect stocking season or date or both can have on grazing distributions. We fit three additional models to explore the relative importance of stocking season versus location. According to this analysis, stocking season played a role, but stocking location was the main driver. Ostensibly minor factors (e.g. stocking location) can greatly influence livestock distributions.     

Is bird song a reliable signal of aggressive intent?

In this commentary, we discuss recent experiments on the reliability of bird song as a signal of aggressive intent during territorial conflicts. We outline relevant theoretical views on honest signaling, highlighting the vulnerability handicap hypothesis as a possible explanation for soft song’s reliability in predicting attack. We also sketch possible methods of testing whether soft song agrees with key predictions of the vulnerability handicap hypothesis. Finally, we suggest possible empirical refinements that may be useful in future studies of signals of intent, both in birds and in animals broadly. In particular, we argue that future studies of intent should strive to incorporate the following elements into their experimental design: (1) multi-modal signal components, (2) interaction dynamics, and (3) minimal time intervals. Simulated exchanges using dynamically interactive models may provide a powerful means of incorporating all three of these design features simultaneously.

畜禽养殖污染是不容忽视的新的环境问题

本文论述了畜禽养殖业对环境带来的污染已成为新的环境问题,并提出了改进的措施。     

工业纤维废渣利用的生物技术研究

用平板分离法从树皮中选育出“５０８８号菌种”，使麻纺厂的废弃下脚料转化成可替代饲料中玉米成份的“媲谷菌饲”。并利用造纸厂白泥，粘胶纤维厂废水处理产生的污泥作饲料钙，锌元素添加剂获成功。     

抗生素抗性基因(ARGs)——一种新型环境污染物

抗生素的环境污染与生态毒性近年来引起了日益广泛的关注.水产养殖和畜牧业抗生素长期滥用的直接后果,很可能诱导动物体内抗生素抗性基因,经排泄后将对养殖区域及其周边环境造成潜在基因污染.抗性基因还极有可能在环境中传播、扩散.对公共健康和食品、饮用水安全构成威胁.为此,提出了将抗生素抗性基因作为一类新型环境污染物,对该类污染物在环境中的来源、潜在的传播途径以及国内外相关研究进展进行综述,指出了当前形势下我国开展环境中抗生素抗性基因污染研究的必要性,建议尽快从国家层面上系统进行抗生素抗性基因的环境污染机理与控制对策研究.     

深入认识生态承载力的空间构成发展节约化畜牧业的初探

内蒙古自治区位于祖国北部边疆，地域辽阔，是我国北疆的绿色屏障，由于自然条件的制约，草场保护与草地资源利用间的矛盾比较突出。近几年我区的过度放牧和养殖，使草地面积退化，而且草地建设严重滞后。我区有得天独厚的风能和水资源，但资源分布不均，东部地区水资源和草地资源丰富，而中西部地区风能资源丰富，如何充分认识与利用资源空间有机组成，充分利用生态承载力，实现生存与生态良性发展，则显得十分重要。本文要结合我区的风、水、土、草等资源的分布条件，探讨我区走协调发展的道路。     

兰州市农牧业源氨排放清单及其时空分布特征

通过实地调研等方式获取农牧业源的活动水平,采用NARSES模型确定氮肥施用排放因子,其它排放因子通过文献调研确定,建立了2016年兰州市农牧业源氨排放清单,并进一步分析了农牧业源氨排放的时空分布特征. 2016年兰州市农牧业源大气氨排放量为9 356. 90 t;其中畜禽养殖源氨排放量7 584. 03 t,分担率81. 05%;永登县是氨排放量最大的区县,氨排放量为2 820. 59 t,分担率为30. 14%.在兰州市各区县氨排放量分担率中,畜牧业源氨排放的分担率在65. 83%～97. 38%之间;氮肥施用源的分担率在2. 27%～28. 66%之间.从空间分布来看,兰州市农牧业源氨排放主要集中在皋兰县西北部与中部、红古区东南部、七里河区东西两部与榆中县东部.从时间分布来看,畜牧业源氨排放主要集中在4～9月,氮肥施用源的氨排放主要集中在3～7月和9月,其它月份排放量相对较小.     

关于畜禽养殖业环境管理的思考

介绍了畜禽养殖业对环境的污染现状及存在的问题,提出了强化环境管理的对策和措施.     

生态意识变迁的考察与草地畜牧业可持续发展--以内蒙古锡林郭勒退化草地为例

目前，内蒙古草地生态环境破坏严重。且总体上呈不断恶化的态势。这种状况的持续不仅严重影响和翻约着本地区经济和社会的总体发展。同时也威胁着包括北京在内的整个华北地区的生态安全。其内在的深层次的根源就在于包括生态意识在内的人们的文化价值观发生了“扭曲”。本文针对锡林郭勒退化草地现状与历史的分析．揭示了其中的文化特征与哲学内涵．并且指出生态意识的确立和生态文化的形成对于保护草地、建设草地的现实意义。