Understanding Change: Integrating Rancher Knowledge Into State-and-Transition Models

Arid and semiarid rangelands often behave unpredictably in response to management actions and environmental stressors, making it difficult for ranchers to manage for long-term sustainability. State-and-transition models (STMs) depict current understanding of vegetation responses to management and environmental change in box-and-arrow diagrams. They are based on existing knowledge of the system and can be improved with long-term ecological monitoring data, histories, and experimentation. Rancher knowledge has been integrated in STMs; however, there has been little systematic analysis of how ranchers describe vegetation change, how their knowledge informs model components, and what opportunities and challenges exist for integrating local knowledge into STMs. Semistructured and field interviews demonstrated that rancher knowledge is valuable for providing detailed management histories and identifying management-defined states for STMs. Interviews with ranchers also provided an assessment of how ranchers perceive vegetation change, information about the causes of transitions, and indicators of change. Interviews placed vegetation change within a broader context of social and economic history, including regional changes in land use and management. Despite its potential utility, rancher knowledge is often heterogeneous and partial and can be difficult to elicit. Ranchers’ feedback pointed to limitations in existing ecological site-based approaches to STM development, especially issues of spatial scale, resolution, and interactions among adjacent vegetation types. Incorporating local knowledge into STM development may also increase communication between researchers and ranchers, potentially yielding more management-relevant research and more structured ways to document and learn from the evolving experiential knowledge of ranchers.     

State-and-Transition Models for Heterogeneous Landscapes: A Strategy for Development and Application

Interpretation of assessment and monitoring data requires information about how reference conditions and ecological resilience vary in space and time. Reference conditions used as benchmarks are often specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially observed in an area based on soil and climate. State-and-transition models (STMs) coupled to ecological sites specify indicators of ecological resilience and thresholds. Although general concepts surrounding STMs and ecological sites have received increasing attention, strategies to apply and quantify these concepts have not. In this paper, we outline concepts and a practical approach to potential-based land classification and STM development. Quantification emphasizes inventory techniques readily available to natural resource professionals that reveal processes interacting across spatial scales. We recommend a sequence of eight steps for the co-development of ecological sites and STMs, including 1) creation of initial concepts based on literature and workshops; 2) extensive, low-intensity traverses to refine initial concepts and to plan inventory; 3) development of a spatial hierarchy for sampling based on climate, geomorphology, and soils; 4) stratified medium-intensity inventory of plant communities and soils across a broad extent and with large sample sizes; 5) storage of plant and soil data in a single database; 6) model-building and analysis of inventory data to test initial concepts; 7) support and/or refinement of concepts; and 8) high-intensity characterization and monitoring of states. We offer a simple example of how data assembled via our sequence are used to refine ecological site classes and STMs. The linkage of inventory to expert knowledge and site-based mechanistic experiments and monitoring provides a powerful means for specifying management hypotheses and, ultimately, promoting resilience in grassland, shrubland, savanna, and forest ecosystems.     

Generalized and Specific State-and-Transition Models to Guide Management and Restoration of Caldenal Forests

Management impacts and natural events can produce ecosystem state changes that are difficult to reverse. In such cases, a detailed understanding of drivers, thresholds, and feedback mechanisms are needed to design restoration interventions. The Caldenal ecoregion in central Argentina has undergone widespread state change, and restoration is urgently needed, but as yet there has been no knowledge synthesis to support restoration actions. In this paper, we provide evidence-based guidelines for ecological restoration of the Caldenal forest derived from a general to local conceptual understanding of ecosystem dynamics. We develop a Caldenal forest state transition model based on a generalized fire-mediated savanna-woodland transition model. The generalized model depicts global similarities in fire-grass feedback loops as a primary factor controlling savanna to woodland transition (thicketization) in semiarid savannas around the world. An open forest is considered to be the reference state of the Caldenal that developed under a historical regime of frequent low-intensity fire. The introduction of large livestock herds in the region disrupted the positive fire-grass feedback loop and increased dispersal and recruitment of Prosopis caldenia, creating conditions for thicketization of the forest. Controlled, low-intensity fire can be used to build the resilience of an open forest state. Restoring open forest states from woodland states requires a large-scale selective thinning and pruning operation. Long-term restoration requires breaking the positive livestock-thicketization ? high-intensity fire feedback and reestablishing the positive grass-low intensity fire feedback to ensure the persistence of a restored open forest state.     

Using Participatory Workshops to Integrate State-and-Transition Models Created With Local Knowledge and Ecological Data

State-and-transition models (STMs) depict current understanding of vegetation dynamics and are being created for most ecological sites in the United States. Model creation is challenging due to inadequate long-term data, and most STMs rely on expert knowledge. There has been little systematic documentation of how different types of knowledge have been integrated in STMs, or what these distinct knowledge sources offer. We report on a series of participatory workshops where stakeholders helped to integrate STMs developed for the same region using local knowledge and ecological field data. With this exploratory project, we seek to understand what kinds of information local knowledge and ecological field data can provide to STMs, assess workshops as a method of integrating knowledge and evaluate how different stakeholders perceive models created with different types of knowledge. Our analysis is based on meeting notes, comments on draft models, and workshop evaluation questionnaires. We conclude that local knowledge and ecological data can complement one another, providing different types of information at different spatial and temporal scales. Participants reported that the workshop increased their knowledge of STMs and vegetation dynamics, suggesting that engaging potential model users in developing STMs is an effective outreach and education approach. Agency representatives and ranchers expressed the value of both the local knowledge and data-driven models. Agency participants were likely to critique or add components based on monitoring data or prior research, and ranchers were more likely to add states and transitions based on personal experience. As STM development continues, it is critical that range professionals think systematically about what different forms of data might contribute to model development, how we can best integrate existing knowledge and data to create credible and useful models, and how to validate the resulting STMs.     

Monitoring British Upland Ecosystems With the Use of Landscape Structure as an Indicator for State-and-Transition Models

Remote sensing and landscape ecology concepts can provide a useful framework for state-and-transition models (STM) in order to quantify thresholds at different scales, and provide useful information for scientists, land managers, and conservationists in relation to resilience management. The overall aim of this research was to develop a spatially explicit STM to quantify thresholds based on the scale of disturbance processes impacting a grazing system. Specific objectives were to develop a conceptual STM framework for upland grazing ecosystems, to quantify spatial dynamics of stable and degraded pastures, and to assess threshold occurrence. Color aerial photography from Armboth Fell in the English Lake District National Park (United Kingdom) was classified into bare rock, dwarf shrub heath (DSH), and grassland/degraded wet heath (GDWH) in four pastures with different degrees of grazing pressure. Vegetation communities from these pastures were combined with soils, climate, and landform data to create a conceptual STM framework. Each pasture was sampled with 2-ha plots to quantify DSH and GDWH spatial structure. The proposed STM consisted of two reference and three alternative states. Low–grazing-pressure areas showed significantly higher percentage of DSH cover with larger contiguous patches and lower patch density than high–grazing-pressure areas. Breakpoints, considered to be thresholds, in mean patch area were identified in our data when DSH percentage cover was < 63% and GDWH, > 77%. The present study has shown the value of a robust, reliable, and repeatable approach to identify landscape dynamics and integrate it with field data to inform a conceptual STM framework for upland grazing ecosystems. It also demonstrates the importance of selecting scales relevant to the predominant disturbance process to test for threshold occurrence, and how this approach can be integrated with current assessment methods for resilience management.     

Evaluating a State-and-Transition Model Using a Long-Term Dataset

State-and-transition models (STMs) are used in natural resource management to describe ecological site scale response to natural and anthropogenic disturbances. STMs are primarily based for expert opinion and literature reviews, lacking analytical testing to support vegetation community dynamics, thresholds, and state changes. We developed a unique approach, combining ordination and permutation MANOVA (perMANOVA) with raw data interpretation, to examine vegetation data structure and identify thresholds for a STM. We used a long-term monitoring dataset for an ecological site on the Santa Rita Experimental Range, Arizona. Basal cover of perennial grasses and canopy cover of shrubs and cacti were measured on permanent transects beginning in 1957. Data were grouped by drivers identified by the STM including species invasion, grazing, drought, and mesquite treatment. Ordination by nonmetric multidimensional scaling described the structure of the data. PerMANOVA was used to test for differences between groups of sample units. Analyses of combined key species (Lehmann's lovegrass and mesquite [Prosopis velutina Woot.]) and nonkey species patterns demonstrated an irreversible transition and occurrence of a structural threshold due to Lehmann's lovegrass invasion, as well as a short-term reversible transition (restoration pathway) following mesquite treatment. Sensitivity analysis, in which key species were removed from the dataset, showed that the relative composition of nonkey species did not differ between states previously defined by the key species. This apparent disconnect between dynamics of key and nonkey species may be related to changes in the functional attributes that were not monitored during this time series. Our analyses suggest that, for this ecological site, transition to a Lehmann's lovegrass state occurs when basal cover of this species exceeds 1–2%, which often occurs within 6 yr of its arrival. Evaluation of the restoration pathway showed a recrossing of the threshold within 6 yr of treatment and when mesquite canopy cover exceeded 10%.     

某型飞机襟翼机构显示动力学仿真研究

本文通过Hyper Woks软件对某型飞机襟翼机构进行显示动力学分析,通过采用RADIOSS求解器,利用中心差分法,成功得到襟翼运动机构在气动载荷下的运动情况,验证滑轮与滑轨之间运动方式。     

基于稀疏表示的目标追踪方法

目标追踪作为图像理解重要的一部分,在公安工作中有着广泛的应用。但是对于一些复杂场景,车辆、行人众多、背景多样,传统的目标追踪算法难以达到理想效果。本文概述了稀疏表示基本概念和稀疏编码的方法,对稀疏表示方法在目标追踪领域中重要研究进展进行总结归纳,并展望了稀疏表示方法在目标追踪领域的发展方向。     

肉用绵羊杂交模式试验研究

用小尾寒羊和引入绵羊品种建立最佳的杂交体系,以无角陶赛特(P)公羊与小尾寒羊(H)母羊级进杂交,或以无角陶赛特(P)公羊与杂交母羊(罗姆尼小尾寒羊F1,陶赛特小尾寒羊F1)进行终端杂交.结果表明,三元杂交羊0～6月龄生长速度快,高于级进杂交三代羊;三元杂交母羊均为全年发情,级进三代母羊春季发情比例较低;三元杂交母羊产羔率也高于级进杂交三代母羊.     

New Models of Hemostasis

Hemostasis is an essential protective mechanism that depends on a delicate balance of procoagulant and anticoagulant processes. The waterfall/cascade models of coagulation are useful for understanding several essential steps of coagulation in vitro. These have resulted in the creation of the plasma-based tests used commonly and the ability to identify deficiencies in the extrinsic, intrinsic, and common pathways of coagulation. The model was also essential in elucidating the role of several of the inhibitors of coagulation and is currently used to demonstrate coagulation as it occurs in plasma in a static environment that is devoid of endothelial interactions. The intrinsic pathway originally described by these models does not appear to be essential for in vivo hemostasis but may play a role in pathologic thrombosis. The waterfall/cascade models' lack of cellular elements sets the stage for the cell-based model of coagulation. The cell-based model of blood coagulation, which includes the varied, complicated network of factors necessary for appropriate in vivo coagulation to occur, was the next step in the evolution of our understanding of coagulation. Recently, researchers have focused on real-time, in vivo models of hemostasis and this research reveals unexpected phenomena.     

Representation of results of feed evaluation. 3. Mixed feed

Model investigations into error dimension and error distribution with regard to piglet rearing feed show that the sampling regulations for mixed feed as laid down in TGL 29080/01 of the GDR basically guarantee the representativeness of the samples as to the assessment of lots. Based on the total scatter and the confidence intervals, the minimum and maximum contents laid down in the standards of quality can be observed. In comparison with pellets, the total scatter particularly for raw ash and the minerals Ca, Na, Mn and Cu is bigger when the mixed feed is provided in the form of coarse meal, which is due to high partial errors in sampling and the prepartion of sampling (partition). The quota of analysis errors in the total error is significant for parameters with relatively low content values (crude fibre, crude fat) and vitamin A in contrast to dry matter, crude protein, raw ash, bulk elements and starch so that double or triple determinations (for vitamin A) are appropriate and to be taken into consideration. Results with regard to vitamins and trace elements make a first survey possible.     

养牛业产业化经营的若干模式

本文详尽介绍了几种适合我国的养牛产业化经营模式,为我国养牛业的发展提供一些新的思路。