Modelling spatial patterns of urban growth in Africa

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.     

Invasive Saltcedar (Tamarix): Its Spread from the American Southwest to the Northern Great Plains

The advance of saltcedar from the American southwest to Montana between the mid-19th and mid-20th centuries crossed the Continental Divide—a major topographic and climatic barrier to natural dispersal by southern plants. Interviews, archival information, and field observations are used to explain this advance. According to archival documents, saltcedar was planted in communities adjacent to the Bighorn River in central Wyoming as part of urban beautification projects in 1936. Bureau of Reclamation reports describe tree plantings for erosion control between 1940 and 1953 within the Riverton Irrigation Project in the Wind-Bighorn River watershed. These introductions were followed by rapid natural dispersal northward by water and wind through the Wind/Bighorn system and into the Yellowstone and Missouri rivers in Montana before closure of Boysen and Bighorn dams in 1951 and 1967. Construction equipment and ornamental plantings further transported saltcedar to the Fort Peck Reservoir and the Musselshell River. We conclude that, without control at its advancing fronts, a complete ban of its sale, and removal of existing ornamental and erosion control trees, saltcedar will invade most suitable sites in the Missouri watershed and disperse northwards into western Canada.     

Tree establishment on bars in low‐order gravel‐bed mountain streams

In many large alluvial rivers, trees often recruit and survive along laterally accreted sediments on bars. This produces a gradient of tree ages and composition with distance from the active channel. However, in low‐order, gravel‐bed mountain streams, such as the stream investigated in this study, it is suggested that vertical accretion results in sediment deposition patterns on bars that are often highly patchy. Consequently, tree species and ages are also heterogeneously distributed, rather than having distinct linear or arcuate banding patterns with distance from the channel. In addition, overall age patterns of trees on these bars follow the distribution of floods, with numerous young trees and few older trees. Recruitment is fairly continuous on these bars and is not correlated with high water years, suggesting that even flows close to bankfull levels are capable of transporting fine sediment to the bars on which trees establish. This pattern of sediment deposition/erosion and the resulting tree recruitment and survival seem to be a result of valley confinement and the lack of lateral accretion in these smaller, mountainous channels. Copyright © 2011 John Wiley & Sons, Ltd.     

Phylogenomic analysis of transcriptomic sequences of mitochondria and chloroplasts of essential brown algae (Phaeophyceae) in China

The chloroplast and mitochondrion of brown algae （Class Phaeophyceae of Phylum Ochrophyta） may have originated from different endosymbiosis. In this study, we carried out phylogenomic analysis to distinguish their evolutionary lineages by using algal RNA-seq datasets of the 1 000 Plants （1KP） Project and publicly available complete genomes of mitochondria and chloroplasts of Kingdom Chromista. We have found that there is a split between Class Phaeophyceae of Phylum Ochrophyta and the others （Phylum Cryptophyta and Haptophyta） in Kingdom Chromista, and identified more diversity in chloroplast genes than mitochondrial ones in their phylogenetic trees. Taxonomy resolution for Class Phaeophyceae showed that it was divided into Laminariales-Ectocarpales clade and Fucales clade, and phylogenetic positions of Kjellmaniella crassi-folia, Hizikia fusifrome and Ishige okamurai were confirmed. Our analysis provided the basic phylogenetic relationships of Chromista algae, and demonstrated their potential ability to study endosymbiotic events.     

Benefits and drawbacks of two modelling approaches for a generalist carnivore: can models predict where Wile E. Coyote will turn up next?

Wildlife ecologists frequently make use of limited information on locations of a species of interest in combination with readily available GIS data to build models to predict space use. In addition to a wide range of statistical data models that are more commonly used, machine learning approaches provide another means to develop predictive spatial models. However, comparison of output from these two families of models for the same data set is not often carried out. It is important that wildlife managers understand the pitfalls and limitations when a single set of models is used with limited GIS data to try to predict and understand species distribution. To illustrate this, we carried out two sets of models (generalized linear mixed models (GLMMs) and boosted regression trees (BRTs)) to predict geographic occupancy of the eastern coyote (Canis latrans) on the island of Newfoundland, Canada. This exercise is illustrative of common spatial questions in wildlife research and management. Our results show that models vary depending on the approach (GLMM vs. BRT) and that, overall, BRT had higher predictive ability. Although machine learning has been criticized because it is not explicitly hypothesis-driven, it has been used in other areas of spatial modelling with success. Here, we demonstrate that it may be a useful approach for predicting wildlife space use and to generate hypotheses when data are limited. The results of this comparison can help to improve other models for species distributions and also guide future sampling and modelling initiatives.     

The stemflow of trees in a Bornean lowland tropical forest

Stemflow volume generation in lowland tropical forests was measured over a 1‐year period in the Malaysian state of Sarawak. The stemflow volume generated by 66 free‐standing trees with a diameter at breast height (DBH) over 1 cm and a tree height over 1 m were measured daily in a representative 10 m × 10 m plot of the forest. Throughfall in the plot was also measured using 20 gauges in a fixed position. Of the 2292 mm of total rainfall observed during the year‐long period, stemflow accounted for 3·5%, throughfall for 82% and there was an interception loss of 14·5%. Understory trees (DBH < 10 cm) played an important role in stemflow generation, producing 77% of the overall stemflow volume and 90% during storms with less than 20 mm of rainfall. Also, owing to their efficiency at funneling rainfall or throughfall water received by their crowns, some understory trees noticeably reduced the catches of the throughfall gauges situated under the reach of their crown areas. During storms producing greater than 20 mm of rainfall, 80% of the total stemflow occurred; trees with a large DBH or height and for which the ratio between crown's diameter and depth is less than 1, tended to generate more stemflow volume in these storms. Mean areal stemflow as a fraction of rainfall in this lowland tropical forest was 3·4%, but may range from 1–10% depending upon the proportion of trees that are high or poor stemflow yielders. Trees with DBH greater than 10 cm were likely to contribute less than 1% of the 3·4% mean areal stemflow in the forest. Copyright © 2004 John Wiley & Sons, Ltd.     

Paleoenvironmental and paleoecological reconstruction of a freshwater oasis in savannah grassland at FLK North, Olduvai Gorge, Tanzania

The records of early hominins are commonly localized both temporally and spatially even in archaeologically rich basins like Olduvai Gorge, Tanzania. The FLK North site was discovered in 1960, but the reason for the exact location of this dense concentration of fossils and stone tools on a lake-margin flat has not been explained. We present new geological and geochemical information from six excavations in upper Bed I, which revealed up to 1.4-m-thick carbonate deposits, attesting to the presence of freshwater springs in the area surrounding FLK North. The δ¹⁸O signatures of the tufa are typical for meteoric water that has evolved during evaporation. Tuff IF that caps the sequence was deposited on uneven topography with the highest area a low-relief ridge between two faults at the archaeological site and lowest areas being sites of groundwater discharge. The model proposed here is that rainfall on adjacent highlands was transported to the basin where faults acted as conduits for water. Similar hydrogeological settings at modern lakes Manyara and Eyasi, currently support lush groundwater forest and woodland despite arid climate. FLK North may have been an “oasis” offering freshwater and shelter for consuming meat by both carnivores and hominins.     

Criteria for Selecting and Adjusting Ground-Motion Models for Specific Target Regions: Application to Central Europe and Rock Sites

A vital component of any seismic hazard analysis is a model for predicting the expected distribution of ground motions at a site due to possible earthquake scenarios. The limited nature of the datasets from which such models are derived gives rise to epistemic uncertainty in both the median estimates and the associated aleatory variability of these predictive equations. In order to capture this epistemic uncertainty in a seismic hazard analysis, more than one ground-motion prediction equation must be used, and the tool that is currently employed to combine multiple models is the logic tree. Candidate ground-motion models for a logic tree should be selected in order to obtain the smallest possible suite of equations that can capture the expected range of possible ground motions in the target region. This is achieved by starting from a comprehensive list of available equations and then applying criteria for rejecting those considered inappropriate in terms of quality, derivation or applicability. Once the final list of candidate models is established, adjustments must be applied to achieve parameter compatibility. Additional adjustments can also be applied to remove the effect of systematic differences between host and target regions. These procedures are applied to select and adjust ground-motion models for the analysis of seismic hazard at rock sites in West Central Europe. This region is chosen for illustrative purposes particularly because it highlights the issue of using ground-motion models derived from small magnitude earthquakes in the analysis of hazard due to much larger events. Some of the pitfalls of extrapolating ground-motion models from small to large magnitude earthquakes in low seismicity regions are discussed for the selected target region.     

Late Holocene paleoenvironmental change in a Great Lakes coastal wetland: integrating pollen and diatom datasets

Multiple proxy indicators are regularly used to present robust arguments for paleoenvironmental change. We use fossil pollen and diatoms from a 495-cm core taken from Cootes Paradise, a coastal wetland in the western end of Lake Ontario, to investigate ecological changes in the late Holocene. We use consensus analysis to demonstrate that pollen diagrams are best zoned after the data have been split into source area, in this case upland and wetland taxa, because each group responds differently to environmental change. We also use consensus analysis to demonstrate the sensitivity of clustering to the distance measure used. The record begins at 2400 ¹⁴C years BP, when the wetland was dominated by shallow water emergents and epiphytic diatoms. At 2100 ¹⁴C years BP, a decline in the epiphytic diatoms Epithemia spp., a rise in Poaceae (cf. Zizania aquatica) pollen and a coincident increase in pollen concentration suggest a water level rise at this time. At about 800 ¹⁴C years BP, the diatom record shows a pulse in small benthic Fragilaria species; shortly after, a shift occurs in the upland tree pollen spectra involving an increase in Pinus and a decline in Fagus. This shift in upland forest trees has been associated elsewhere with the Little Ice Age and the diatom data present some evidence for impacts of this climatic event on aquatic systems. The diatom and pollen records both indicate large changes associated with the effects of European settlement, including rises in Ambrosia as well as Typha angustifolia pollen. Planktonic diatoms dominate post-settlement assemblages indicating large-scale hydrological and ecological changes, probably associated with the introduction of carp and alterations to the Iroquois bar which separates the wetland from Lake Ontario. Our work at Cootes Paradise is important for multi-proxy coastal wetland studies in general, in addition to the late Holocene environmental history and prehistory of the Great Lakes region.