Tropical Timber Rush in Peruvian Amazonia: Spatial Allocation of Forest Concessions in an Uninventoried Frontier

Land-use allocation has important implications for the conservation and management of tropical forests. Peru’s forestry regime has recently been reformed and more than 7 million ha has been assigned as forest concessions. This potentially has a drastic impact on the land-use practices and species composition of the assigned areas. Nevertheless, the environmental variation found within the concessions and the process applied to delimit them are poorly studied and documented. Thus, it is difficult to estimate the biological impacts of forestry activities in concessions or plan them sustainably. This paper reveals the characteristics of the current concession allocation in Loreto, Peruvian Amazonia, using environmental and access-related variables and compares the concessions to other major land-use assignments. The work draws on a number of data sets describing land-use, ecosystem diversity, and fluvial network in the region. According to our data, certain environment types such as relatively fertile Pebas soils are overrepresented in the concessions, while others, like floodplain forests, are underrepresented in comparison to other land-use assignments. Concessions also have less anthropogenic disturbance than other areas. Furthermore, concessions are located on average further from the river network than the other land-use assignments studied. We claim that forest classification based on productivity, soil fertility, accessibility, and biodiversity patterns is an achievable long-term goal for forest authorities in Peru, and in many other tropical countries. We present a rough design of a geographic information system incorporating environmental, logging, and access-related data that could be applied to approach this goal in Peru.     

Quantification of a Primary Production Model Using Two Versions of the Spectral Distribution of the Phytoplankton Absorption Coefficient

In a recent publication, we discussed and presented a semi-empirical phytoplankton primary production model. In the present paper, our main purpose is to determine how the algorithms of a primary production model change when different values of specific absorption coefficient by phytoplankton are used in the model. A new version of our earlier model was quantified for this purpose. Differences between the previous and the new models are as follows: (a) the spectra of the specific absorption coefficient of light by phytoplankton differ in the new model from those used in the previous model, and (b) the quantification of the new model brings about a change in the parameters of the algorithm for the quantum yield of carbon fixation. We compared the results of primary production profiles obtained by the new model with those measured in situ and also with the values obtained by the previous model. Due to an adequate choice of quantification parameters, both the old and new models give rather close values of phytoplankton primary production. In the present study, the computational algorithms of both models have been automated. The resulting programs calculate the temporal–spatial variability of phytoplankton primary production, providing hourly values from morning to evening, daily sums, and monthly sums. The input of a table of initial parameters and selected depths produces rapid calculations of the model's results, which are given as vertical profiles of primary production and areal values.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

First-trimester assessment of placenta function and the prediction of preeclampsia and intrauterine growth restriction

Preeclampsia and intrauterine growth restriction (IUGR) are major contributors to perinatal mortality and morbidity worldwide. Both are characterized by impaired trophoblastic invasion of the maternal spiral arteries and their conversion from narrow muscular vessels to wide non-muscular channels. Despite improvement in the understanding of the pathophysiology of these conditions, ability to accurately identify pregnant woman who will develop them is limited. This greatly impairs the development and testing of preventive interventions. While different measures of placental dysfunction have been associated with increased risk for adverse pregnancy outcomes, the ability of any single one to accurately predict these outcomes is poor. Developing predictive tests is further challenged by difficulty in the timing of the measurements, as both the structural and biochemical characteristics of the placenta change with increasing gestational age. The ideal screening test would accurately predict the development of adverse pregnancy outcomes early enough to provide a window for preventive interventions. Improvement in ultrasound technology provides potentially useful novel tools for evaluating placental structure, but measuresments need to be standardized in order to be useful. Maternal serum analyte screening is a noninvasive test of placental biochemical function, but present serum marker alone is not sufficiently accurate to suggest its routine use in clinical practice. The use of first trimester biochemical markers in combination with uterine artery Doppler screening is promising as a potential screening tool. Prospective longitudinal studies using standardized methodology are necessary to further evaluate the choice of parameters and strategies of combination to achieve the best predictive models. Copyright © 2010 John Wiley & Sons, Ltd.     

Using Wikipedia to measure public interest in biodiversity and conservation

The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study human–nature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined. We considered the potential of Wikipedia, the online encyclopedia, as a resource for conservation culturomics and outlined methods for using Wikipedia data in conservation. Wikipedia's large size, widespread use, underlying data structure, and open access to both its content and usage analytics make it well suited to conservation culturomics research. Limitations of Wikipedia data include the lack of location information associated with some metadata and limited information on the motivations of many users. Seven methodological steps to consider when using Wikipedia data in conservation include metadata selection, temporality, taxonomy, language representation, Wikipedia geography, physical and biological geography, and comparative metrics. Each of these methodological decisions can affect measures of online interest. As a case study, we explored these themes by analyzing 757 million Wikipedia page views associated with the Wikipedia pages for 10,099 species of birds across 251 Wikipedia language editions. We found that Wikipedia data have the potential to generate insight for conservation and are particularly useful for quantifying patterns of public interest at large scales.     

Evaluating the Impact of Distance Measures on Deforestation Simulations in the Fluvial Landscapes of Amazonia

Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility in our study area. The most accurate simulation is achieved when time distance to market center is used in association with distance to transport network and additional landscape variables. Although traditional Euclidean measures result in clearly lower simulation accuracy when used separately, the combination of two complementary Euclidean measures enhances simulation accuracy significantly. Our results highlight the need for site and context sensitive selection of accessibility variables. More sophisticated accessibility measures can potentially improve LUCC models’ spatial accuracy, which often remains low.     

Life cycle inventory analyses for five waste management options for discarded newspaper.

This paper presents the results of life cycle inventory (LCI) analyses that were carried out to determine the environmental impacts (emissions, resource extractions and land use) of different newspaper waste management options for the Helsinki Metropolitan Area (HMA). LCI analyses were performed for five product systems, in which discarded newspapers were divided into two streams: separately collected newspapers and newspapers in mixed waste. In all the options, the manufacturing and printing processes of newspaper were kept unchanged. The waste management alternatives included combinations of material recycling, energy recovery and landfilling. These product systems were modelled using the current collection rate of newspaper and four additional collection rates. The LCIs of the product systems showed that the life cycle phase causing the most environmental impacts was the paper mill. When comparing the different waste management systems, the energy recovery options were in general superior to landfilling. The ecological implications of the increased energy recovery and decreased material recycling of newspaper were, however, not yet considered in the study. These aspects were assessed in the life cycle impact assessment (LCIA), which was performed after the LCI phase.