Modeling Trends from North American Breeding Bird Survey Data: A Spatially Explicit Approach

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.     

Spatially Explicit Modeling in Ecology: A Review

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.     

Dealing with Uncertainty in Spatially Explicit Population Models

It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct estimates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate model calibration procedures can access additional sources of information, compensating the lack of direct parameter estimates. Our objective is to show how model calibration using population-level data can facilitate the construction of SEPMs that produce reliable predictions for conservation even when direct parameter estimates are inadequate. We constructed a spatially explicit and individual-based population model for the dynamics of brown bears (Ursus arctos) after a reintroduction program in Austria. To calibrate the model we developed a procedure that compared the simulated population dynamics with distinct features of the known population dynamics (=patterns). This procedure detected model parameterizations that did not reproduce the known dynamics. Global sensitivity analysis of the uncalibrated model revealed high uncertainty in most model predictions due to large parameter uncertainties (coefficients of variation CV 0.8). However, the calibrated model yielded predictions with considerably reduced uncertainty (CV 0.2). A pattern or a combination of various patterns that embed information on the entire model dynamics can reduce the uncertainty in model predictions, and the application of different patterns with high information content yields the same model predictions. In contrast, a pattern that does not embed information on the entire population dynamics (e.g., bear observations taken from sub-areas of the study area) does not reduce uncertainty in model predictions. Because population-level data for defining (multiple) patterns are often available, our approach could be applied widely.     

A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

Food security and water scarcity have become two major concerns for future human''s sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.     

Global Conservation of Protein Status between Cell Lines and Xenografts

Common preclinical models for testing anticancer treatment include cultured human tumor cell lines in monolayer, and xenografts derived from these cell lines in immunodeficient mice. Our goal was to determine how similar the xenografts are compared with their original cell line and to determine whether it is possible to predict the stability of a xenograft model beforehand. We studied a selection of 89 protein markers of interest in 14 human cell cultures and respective subcutaneous xenografts using the reverse-phase protein array technology. We specifically focused on proteins and posttranslational modifications involved in DNA repair, PI3K pathway, apoptosis, tyrosine kinase signaling, stress, cell cycle, MAPK/ERK signaling, SAPK/JNK signaling, NFκB signaling, and adhesion/cytoskeleton. Using hierarchical clustering, most cell culture-xenograft pairs cluster together, suggesting a global conservation of protein signature. Particularly, Akt, NFkB, EGFR, and Vimentin showed very stable protein expression and phosphorylation levels highlighting that 4 of 10 pathways were highly correlated whatever the model. Other proteins were heterogeneously conserved depending on the cell line. Finally, cell line models with low Akt pathway activation and low levels of Vimentin gave rise to more reliable xenograft models. These results may be useful for the extrapolation of cell culture experiments to in vivo models in novel targeted drug discovery.     

全球生物经济现状、趋势与融资前景分析*

生物经济是指通过可持续的方式,利用可再生自然资源来生产食品、能源、生物技术产品和服务的一切经济活动的总和。生物经济是继农业经济、工业经济、信息经济之后,人类经济社会发展的第四次浪潮。概述全球生物经济发展现状,梳理世界主要经济体生物经济战略布局,归纳生物经济未来发展的四个主要方向,通过调研统计分析生物制药、生物基材料和化学品、生物农业和未来食品三个生物产业重点领域的投融资数据,预判未来生物产业投融资前景,并针对我国生物产业投融资提出建议。     

Spatially Explicit Data: Stewardship and Ethical Challenges in Science

Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of data stewardship and data sharing. Formal data management plans represent a new emphasis in research, enabling access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration.     

A Spatially Explicit Model of Synchronization in Fiddler Crab Waving Displays

Fiddler crabs (Uca spp., Decapoda: Ocypodidae) are commonly found forming large aggregations in intertidal zones, where they perform rhythmic waving displays with their greatly enlarged claws. While performing these displays, fiddler crabs often synchronize their behavior with neighboring males, forming the only known synchronized visual courtship displays involving reflected light and moving body parts. Despite being one of the most conspicuous aspects of fiddler crab behavior, little is known about the mechanisms underlying synchronization of male displays. In this study we develop a spatially explicit model of fiddler crab waving displays using coupled logistic map equations. We explored two alternative models in which males either direct their attention at random angles or preferentially toward neighbors. Our results indicate that synchronization is possible over a fairly large region of parameter space. Moreover, our model was capable of generating local synchronization neighborhoods, as commonly observed in fiddler crabs under natural conditions.     

Conservation of Drill Populations in Bakossiland,Cameroon: Historical Trends and Current Status

Very little information is available on the current status of drill populations in Cameroon. We report on drill group sizes and status in Bakossiland, a mountainous area spanning 2000 km² in the Littoral and South West Provinces of southwestern Cameroon. Between 1970 and 2002 direct visual counts of drill groups (n = 105) yielded group size estimates ranging from 5 to 400 (mean ± S.E.M.; 93.1 ± 8.4). We encountered solitary adult male drills on 8 occasions. Groups were at all elevations (150–2000 m) in 5 habitat types: lowland, premontane, submontane and montane forests and montane savannah at 2000 m). Group sizes did not vary with respect to elevation, habitat type or season (wet and dry mo). However, over the past decade drills have been virtually hunted out of the Mwenzekong Mountains (Banyang Mbo Wildlife Sanctuary), and they are greatly reduced in the southern Bakossi forests of Mwendolengo, Edib Hills and Mungo River. The species became extinct in the Loum Forest Reserve in the late 1970s, and until recently was thought to have become extinct on Mount Mwanenguba. Since 1994 on Mount Kupe, the drill population has begun to recover, largely due to protection afforded by the Bakossi traditional chiefs. Traditional powers and values are still influential in the region. A new national park—Bakossi Mountains National Park— and associated Protected Areas are currently under gazettment. We discuss the effectiveness of conservation strategies in relation to the survival of drills in the area.     

New Spatially Explicit Method for Detecting Extracellular Protease Activity in Biofilms

A novel method of detecting extracellular protease activity at biofilm-substratum interfaces was developed. This method utilizes fluorescent molecules bound to cellulose substrata with a lectin. Extracellular proteases degrade the lectin and release the fluorochrome into solution. This new technique and a standard dissolved-substrate assay detected similar responses of biofilm extracellular protease activity to experimental manipulation of N supply. Combination of this technique with confocal scanning laser microscopy allowed direct visualization of microspatial patterns of bacterial distribution and extracellular protease activity at the biofilm-substratum interface.     

Spatially Explicit Characterization of Acidifying and Eutrophying Air Pollution in Life-Cycle Assessment

Abstract: Simple models are often used to assess the potential impact of acidifying and eutrophying substances released during the life cycle of products. As fate, background depositions, and ecosystem sensitivity are not included in these models, environmental life-cycle assessment of products (LCA) may produce incorrect results for these impact categories. This paper outlines the spatially explicit regional air pollution information and simulation model (RAINSLCA), which was developed for the calculation of acidification and terrestrial eutrophication potentials of ammonia (NH3) and nitrogen oxide (NOx) air emissions and acidification potentials for sulfur dioxide (SO2) air emissions for Europe and a number of European regions, taking fate,     

A Spatially Explicit Model of Stabilizing Selection for Improving Phylogenetic Inference

Ultraconserved elements (UCEs) are stretches of hundreds of nucleotides with highly conserved cores flanked by variable regions. Although the selective forces responsible for the preservation of UCEs are unknown, they are nonetheless believed to contain phylogenetically meaningful information from deep to shallow divergence events. Phylogenetic applications of UCEs assume the same degree of rate heterogeneity applies across the entire locus, including variable flanking regions. We present a Wright–Fisher model of selection on nucleotides (SelON) which includes the effects of mutation, drift, and spatially varying, stabilizing selection for an optimal nucleotide sequence. The SelON model assumes the strength of stabilizing selection follows a position-dependent Gaussian function whose exact shape can vary between UCEs. We evaluate SelON by comparing its performance to a simpler and spatially invariant GTR+Γ model using an empirical data set of 400 vertebrate UCEs used to determine the phylogenetic position of turtles. We observe much improvement in model fit of SelON over the GTR+Γ model, and support for turtles as sister to lepidosaurs. Overall, the UCE-specific parameters SelON estimates provide a compact way of quantifying the strength and variation in selection within and across UCEs. SelON can also be extended to include more realistic mapping functions between sequence and stabilizing selection as well as allow for greater levels of rate heterogeneity. By more explicitly modeling the nature of selection on UCEs, SelON and similar approaches can be used to better understand the biological mechanisms responsible for their preservation across highly divergent taxa and long evolutionary time scales.     

Spatially Explicit Life Cycle Analysis of Cellulosic Ethanol Production Scenarios in Southwestern Michigan

Modeling the life cycle of fuel pathways for cellulosic ethanol (CE) can help identify logistical barriers and anticipated impacts for the emerging commercial CE industry. Such models contain high amounts of variability, primarily due to the varying nature of agricultural production but also because of limitations in the availability of data at the local scale, resulting in the typical practice of using average values. In this study, 12 spatially explicit, cradle-to-refinery gate CE pathways were developed that vary by feedstock (corn stover, switchgrass, and Miscanthus), nitrogen application rate (higher, lower), pretreatment method (ammonia fiber expansion [AFEX], dilute acid), and co-product treatment method (mass allocation, sub-division), in which feedstock production was modeled at the watershed scale over a nine-county area in Southwestern Michigan. When comparing feedstocks, the model showed that corn stover yielded higher global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) than the perennial feedstocks of switchgrass and Miscanthus, on an average per area basis. Full life cycle results per MJ of produced ethanol demonstrated more mixed results, with corn stover-derived CE scenarios that use sub-division as a co-product treatment method yielding similarly favorable outcomes as switchgrass- and Miscanthus-derived CE scenarios. Variability was found to be greater between feedstocks than watersheds. Additionally, scenarios using dilute acid pretreatment had more favorable results than those using AFEX pretreatment.     

Global Diversity and Conservation Priorities in the Cactaceae

The purpose of this paper was to analyze the diversity patterns of Cactaceae at a global scale, to identify those countries where conservation actions should be performed. In order to do this, the species richness and the number of endemic species for 34 American countries were determined. With these data, the relationship between the total number of species or the number of endemic species and the area of the countries were analyzed. In addition, a complementarity analysis was conducted to determine the most important countries for cactus conservation. Results showed that Mexico had the highest number of total and endemic species followed by Argentina, Bolivia, Brazil, and Peru, among others. There was a significant positive relationship between both, the total and endemic species, and the area of the countries. Despite this fact, the cactus diversity in Mexico, Argentina, Peru, Bolivia, Chile, and Costa Rica was higher than expected according to their area. Further, these countries also presented the highest proportions of endemic species. The complementarity analysis indicated that 24 countries are necessary to preserve all cactus species. However, 94% of all species could be preserved with only 10 countries. Considering the diversity patterns and the complementarity analysis, three important groups for cactus conservation were identified: (1) Mexico, Argentina, Peru, Bolivia, Chile, and Costa Rica, (2) Paraguay and Cuba, and (3) Brazil and USA. Conservation efforts should be focused on these countries in order to preserve cactus diversity.