Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Enhancing generic ecological model for short-term prediction of Southern North Sea algal dynamics with remote sensing images

Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration.     

Continuous versus binary representations of landscape heterogeneity in spatially-explicit models of mobile populations

How a landscape is represented is an important structural assumption in spatially-explicit simulation models. Simple models tend to specify just habitat and non-habitat (binary), while more complex models may use multiple levels or a continuum of habitat quality (continuous). How these different representations influence model projections is unclear. To assess the influence of landscape representation on population models, I developed a general, individual-based model with local dispersal and examined population persistence across binary and continuous landscapes varying in the amount and fragmentation of habitat. In binary and continuous landscapes habitat and non-habitat were assigned a unique mean suitability. In continuous landscapes, suitability of each individual site was then drawn from a normal distribution with fixed variance. Populations went extinct less often and abundances were higher in continuous landscapes. Production in habitat and non-habitat was higher in continuous landscapes, because the range of habitat suitability sampled by randomly dispersing individuals was higher than the overall mean habitat suitability. Increasing mortality, dispersal distance, and spatial heterogeneity all increased the discrepancy between continuous and binary landscapes. The effect of spatial structure on the probability of extinction was greater in binary landscapes. These results show that, under certain circumstances, model projections are influenced by how variation in suitability within a landscape is represented. Care should be taken to assess how a given species actually perceives the landscape when conducting population viability analyses or empirical validation of theory.     

Role of behavioural factors in green supply chain management implementation in Indian mining industries

Green supply chain management (GSCM) integrates ecological concepts with those of supply chain management in order to minimize energy and material usage and to reduce adverse impacts of supply chain activities on the environment. GSCM implementation in mining industries depends largely upon certain factors which are influenced by human behaviours. Human behaviour is dynamic in nature and the relationships between them continuously evolve and change. In this ever-changing context, therefore, identifying and ranking the behavioural factors that affect GSCM implementation becomes essential. This can be taken as a reference by the decision makers while deciding the hierarchy of action necessary for effective implementation of green practices in mining supply chains. The present research attempts to explore various behavioural factors affecting GCSM practices and their interactions which help to attain green-enabled needs. Interpretive structural modelling (ISM) is employed in this research to extract the interrelationships among the identified behavioural factors.     

Field-breeding birds on organic and conventional arable farms in the Netherlands

In this study territory densities of field-breeding farmland birds were compared on pairwise-selected organic and conventional arable farms for two years. Differences in territory densities between the two farm types were explained examining the effects of three factors on territory densities: (1) non-crop habitats, (2) crop types and (3) within-crop factors. In both years, densities of most species did not differ between organic and conventional farms. Only skylark and lapwing were more abundant on organic farms, but only skylarks showed a consistent pattern over both years. Differences in crop types grown between the two systems were the only explaining factor for differences in densities of skylark. For lapwing, the difference was only partly due to differences in crop type, but differences in within-crop factors (probably as a result of crop management) were likely to have had an effect as well. There were no significant differences in abundance of non-crop habitats between the two farming systems, so this could not explain differences in territory densities.     

A new approach to assessment and management of the impact from medical liquid radioactive waste

The Swedish regulations concerning disposal of clinical radioactive waste are currently under revision and a graded approach is proposed for risk limitation purposes. To assist the revision procedures, a screening study was performed to estimate public exposures from liquid releases from hospitals to public sewers. The results showed that doses to sewage workers were above the dose constraint of 100muSva(-1) especially for (131)I and (99m)Tc. Hence, a dynamic model, LUCIA, was developed for realistic assessments in which radionuclide transportation in sewers was modelled. Probabilistic simulations were performed to obtain probability distributions of radionuclide concentrations in sludge. Concurrently, estimates of the effective doses to sewage workers decreased significantly and were below 10muSva(-1) except for (111)In and (131)I. However, the Kd-coefficients representing the partition of radioactivity between water and sludge in sewers are highly uncertain for (111)In. As shown by sensitivity studies, these values are the major determinant of the exposures in sewers.     

An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia

The combined influence on the environment of all projects occurring in a single area is evaluated through cumulative impact assessments (CIA), which consider the consequences of multiple projects, each insignificant on its own, yet important when evaluated collectively. Traditionally, future human activities are included in CIA using an analytical platform, commonly based on complex models that supply precise predictions but with reduced accuracy. To compensate for the lack of accuracy in current CIA approaches, we propose a shift in the paradigm governing CIA. The paradigm shift involves a change in the focus of CIA investigations from the detailed analysis of one unlikely future to the identification of the patterns describing multiple potential future changes in the environment. To illustrate the approach, a set of 144 possible and equally likely futures were developed that aimed to identify the potential impacts of forest harvesting and petroleum drilling on the habitat suitability of moose and marten in northeast British Columbia, Canada. The evolution of two measures of habitat suitability (average habitat suitability index and surface of the stands with habitat suitability index >0.5) revealed that the human activities could induce cycles in the habitat dynamics of moose and marten. The planning period of 100 years was separated into three distinct periods following a sinusoidal pattern (i.e., increase - constant - decrease in the habitat suitability measures). The attributes that could induce significant changes in the assessment of environment are the choice of harvesting age and species.     

Application of the target fish community model to an urban river system

Several models have been developed to assess the biological integrity of aquatic systems using fish community data. One of these, the target fish community (TFC) model, has been used primarily to assess the biological integrity of larger, mainstem rivers in southern New England with basins characterized by dispersed human activities. We tested the efficacy of the TFC approach to specify the fish community in the highly urbanized Charles River watershed in eastern Massachusetts. To create a TFC for the Charles River we assembled a list of fish species that historically inhabited the Charles River watershed, identified geomorphically and zoogeographically similar reference rivers regarded as being in high quality condition, amassed fish survey data for the reference rivers, and extracted from the collections the information needed to define a TFC. We used a similarity measurement method to assess the extent to which the study river community complies with the TFC and an inference approach to summarize the manner in which the existing fish community differed from target conditions. The five most abundant species in the TFC were common shiners (34%), fallfish (17%) redbreast sunfish (11%), white suckers (8%), and American eel (7%). Three of the five species predicted to be most abundant in the TFC were scarce or absent in the existing river community. Further, the river was dominated by macrohabitat generalists (99%) while the TFC was predicted to contain 19% fluvial specialist species, 43% fluvial dependent species, and 38% macrohabitat generalist species. In addition, while the target community was dominated by fish intolerant (37%) and moderately tolerant (39%) of water quality degradation, the existing community was dominated by tolerant individuals (59%) and lacked intolerant species expected in the TFC. Similarity scores for species, habitat use specialization, and water quality degradation tolerance categories were 28%, 35% and 66%, respectively. The clear pattern of deviations from target conditions when observing fish habitat requirements strongly suggests that physical habitat change should be a priority for river enhancement in the Charles River. Comparison of our target and existing fish communities to those from a comprehensive study of Northeastern fish assemblage responses to urban intensity gradients revealed very similar results. Likewise, comparison of our TFC community and affinity scores to those of other TFCs from similar regions also yielded similar results and encouraging findings. Based on the positive results of these comparisons, the utility of the findings from the inference approach, and the widespread adoption of the TFC in the Northeast US, it appears that the TFC approach can be used effectively to identify the composition of a healthy fish community and guide river enhancements in both highly urbanized and non-urbanized streams and rivers in the Northeast US.     

Population viability of the Siberian Tiger in a changing landscape: Going, going and gone?

The Amur tiger (Panthera tigris altaica) is a flagship species of the boreal forest ecosystem in northeastern China and Russia Far East. During the past century, the tiger population has declined sharply from more than 3000 to fewer than 600 individuals, and its habitat has become much smaller and greatly fragmented. Poaching, habitat degradation, habitat loss, and habitat fragmentation have been widely recognized as the primary causes for the observed population decline. Using a population viability analysis tool (RAMAS/GIS), we simulated the effects of poaching, habitat degradation, habitat loss, and habitat fragmentation on the population dynamics and extinction risk of the Amur tiger, and then explored the relative effectiveness of three conservation strategies involving improving habitat quality and establishing movement corridors in China and Russia. A series of controlled simulation experiments were performed based on the current spatial distribution of habitat and field-observed vital rates. Our results showed that the Amur tiger population could be viable for the next 100 years if the current habitat area and quality were well-maintained, with poaching strictly prohibited of the tigers and their main prey species. Poaching and habitat degradation (mainly prey scarcity) had the largest negative impacts on the tiger population persistence. While the effect of habitat loss was also substantial, habitat fragmentation per se had less influence on the long-term fate of the tiger population. However, to sustain the subpopulations in both Russia and China would take much greater conservation efforts. The viability of the Chinese population of tigers would rely heavily on its connectivity with the largest patch on the other side of the border. Improving the habitat quality of small patches only or increasing habitat connectivity through movement corridors alone would not be enough to guarantee the long-term population persistence of the Amur tiger in both Russia and China. The only conservation strategy that allowed for long-term persistence of tigers in both countries required both the improvement of habitat quality and the establishment of a transnational reserve network. Our study provides new insights into the metapopulation dynamics and persistence of the Amur tiger, which should be useful in landscape and conservation planning for protecting the biggest cat species in the world.