Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small,Gravel‐Filled Dam1

Kibler, Kelly, Desiree Tullos, and Mathias Kondolf, 2011. Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small, Gravel‐Filled Dam. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2011.00523.x Abstract: Dam removal is a promising river restoration technique, particularly for the vast number of rivers impounded by small dams that no longer fulfill their intended function. As the decommissioning of small dams becomes increasingly commonplace in the future, it is essential that decisions regarding how and when to remove these structures are informed by appropriate conceptual ideas outlining potential outcomes. To refine predictions, it is necessary to utilize information from ongoing dam removal monitoring to evolve predictive tools, including conceptual models. Following removal of the Brownsville Dam from the Calapooia River, Oregon, aquatic habitats directly below the dam became more heterogeneous over the short term, whereas changes further downstream were virtually undetectable. One year after dam removal, substrates of bars and riffles within 400 m downstream of the dam coarsened and a dominance of gravel and cobble sediments replaced previously hardpan substrate. New bars formed and existing bars grew such that bar area and volume increased substantially, and a pool‐riffle structure formed where plane‐bed glide formations had previously dominated. As the Brownsville Dam stored coarse rather than fine sediments, outcomes following removal differ from results of many prior dam removal studies. Therefore, we propose a refined conceptual model describing downstream geomorphic processes following small dam removal when upstream fill is dominated by coarse sediments.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

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.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.     

Modelling the fate of marine turtle hatchlings

The SLIM oceanographic model was used to examine the fate of hatchling flatback turtles (Natator depressus) in the first two weeks of their dispersal starting at Wild Duck Island, a major turtle-nesting site in the central Great Barrier Reef region of Australia. We ran simulations to investigate the effects of spring versus neap tides, hatchling's swimming behaviour during their first three days at sea, and the location of nesting beaches. The model predicted that up to 50% of the turtle hatchlings entering the sea from the windward, southern beach remained after 14 days in shallow, nearshore waters, irrespective of tides and swimming. These waters are turbid and may be inhospitable to hatchlings. In contrast >80% of hatchlings dispersing from the leeward, northern beach were dispersed to deeper water (10-40 m) in a quasi-stationary dispersion core centred around 10 km north of the nesting beach after 14 days and the offshore spread of the turtle plume was enhanced by the hatchling's seaward swimming during the first three days. This was due to the presence of a coastal boundary layer and a stagnation zone around the northern side of island, but not the southern side. The model confirmed that dispersal from eastern Queensland flatback turtle rookeries is restricted to the lagoons and coastal waters, and that water circulation and hatchling's swimming control dispersion. The model explains why more turtles nest on the northern than the southern side. This study highlights the usefulness of oceanographic models to increase knowledge about a cryptic life stage of marine turtles.     

What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods

Species distribution model is the term most frequently used in ecological modelling, but other authors used instead predictive habitat distribution model or species-habitat models. A consensual ecological modelling terminology that avoids misunderstandings and takes into account the ecological niche theory does not exist at present. Moreover, different studies differ in the type of niche that is represented by similar distribution models. I propose to use as standard ecological modelling terminology the terms “ecological niche”, “potential niche”, “realized niche” models (for modelling their respective niches), and “habitat suitability map” (for the output of the niche models). Therefore, the user can understand more easily that models always forecast species’ niche and relate more closely the different types of niche models.     

重点源大气砷铅污染排放模型及特征

在我国的非常规性污染物质中,大气重金属砷、铅已越来越多地被关注和重视。文章综述了国内外人为源对大气中重金属排放的贡献,结果显示中国是全球人为活动向大气排放重金属最多的国家之一,燃煤和有色金属冶炼行业在相当长的时间内都将是最主要且最为重要的人为排放源。通过系统调研燃煤及有色金属冶炼业资源及产业布局状况,构建目前我国大气重金属相关清单模型,进行了我国重点源大气砷、铅排放清单分析,结果表明：（1）2000-2008年我国燃煤大气砷、铅排放量共为93733t,年均增长率为7．93％,2004-2008年有色金属冶炼业大气砷、铅排放量共为18836t,年均增长率为15．2％;（2）2000-2008年各经济部门中电力部门燃煤大气砷、铅放量始终最高,占燃煤大气排放总量的44．6％-57．1％,且呈逐年升高的趋势;（3）2000-2008年各省区中山西、河北、河南和湖南省是大气砷、铅的排放大户。其中,燃煤大气砷、铅排放量主要集中在人口密集、工业集中、经济发展速度较快的北部和中东部省区,包括山西、山东、河北、河南和江苏五省,占全国燃煤排放总量的39．1％,有色金属冶炼大气砷、铅排放量主要集中在我国有色金属工业较为发达的河南及湖南省,占全国有色金属冶炼业排放总量的47．3％。可以看出,我国需要高度重视大气重金属砷、铅的污染防治,加强排放控制基础能力建设,加快建立适合中国的大气砷、铅污染防治技术政策体系。     

危险化学品道路运输安全管理现状及发展趋势研究

为降低危化品运输风险,从危化品运输风险评价、道路选线模型、技术应用、应急联动机制及平台建设、统一联控监管平台等方面进行研究分析。通过对微观视角与宏观视角、单一应用与综合应用的归类和对比,进行分析并指出存在的问题。分析表明,获取精确连续数据,考虑多种外在变量来完善评估模型,注重理论、技术和监管资源的综合应用,发展大区域联控平台将是今后研究的发展趋势。