Human disturbance and shifts in vertebrate community composition in a biodiversity hotspot

Understanding how human modification of the landscape shapes vertebrate community composition is vital to understanding the current status and future trajectory of wildlife. Using a participatory approach, we deployed the largest camera-trap network in Mesoamerica to date to investigate how anthropogenic disturbance shapes the occupancy and co-occurrence of terrestrial vertebrate species in a tropical biodiversity hotspot: the Osa Peninsula, Costa Rica. We estimated species richness in different categories of land protection with rarefaction analysis and estimated the expected occupancy with a joint species distribution model that included covariates for anthropogenic disturbance, land protection, habitat quality, and habitat availability. Areas with the most stringent land-use protections (e.g., Corcovado National Park, 24 species [95% CI 23–25]) harbored significantly more species than unprotected areas (20 species [19.7–20.3]), mainly due to a reduced presence of large-bodied species of conservation concern in unprotected areas (e.g., jaguar Panthera onca and white-lipped peccary Tayassu pecari). Small-bodied generalist species, such as opossums (Didelphidae) and armadillos (Dasypus novemcinctus), in contrast, were more common at disturbed sites, resulting in a significant difference in vertebrate community composition between sites with low and high disturbance. Co-occurrence of species was also mainly associated with response to disturbance. Similar responses to disturbance create two groups of species, those whose site-level occupancy usually increased as anthropogenic disturbance increased and those whose estimated occupancy decreased. The absence of large-bodied species entails an important loss of ecological function in disturbed areas and can hinder forest development and maintenance. Efforts to protect and restore forested landscapes are likely having a positive effect on the abundance of some threatened species. These efforts, however, must be sustained and expanded to increase connectivity and ensure the long-term viability of the wildlife community.     

Emerging dynamics of environmental governance in northern post-productivist regions

The northern, resource-dependent regions of Canada have long faced distinctive social, economic, and environmental challenges and vulnerabilities. However, these regions and communities increasingly find themselves in a transitional and post-productivist context – the implications of which are largely unclear. Therefore, research is needed to identify the current and emerging challenges facing such regions and how environmental governance and planning must adjust to meet these challenges. We utilise the case study of the Northeast Superior region of Ontario to identify and analyse the dynamics developing in post-productivist, resource-dependent regions and what the implications may be for environmental governance. Several key themes and issues that emerged include an increasingly pluralistic context, new regionalism and north–south tensions, First Nation initiatives and power imbalances, and northern identities which are tied to ideas of historical resource-dependence, remoteness, and intimate and complex links to the landscape, all of which inform environmental governance and sustainability debates. As a result, the Northeast Superior case provides insight into these ongoing dynamics which encompass individuals, government, industry, organisations, and the landscape, with the resultant lessons being transferable to initiatives in other northern, remote, and circumpolar regions.     

Influence of different textile fibers on characterization of dyeing wastewater and final effluent

Textile industry needs to recover and reuse its wastewater as to fulfil the demand of increasingly strict regulations. The characterization of dyeing wastewater samples according to textile fiber and final textile effluent enables the application of different treatment methods. This study aims to characterize dyeing wastewater in black color of polyamide, polyester, and viscose fibers and final textile effluent. Samples were collected and characterized completely for major pollution indicator parameters. Dyeing wastewater of polyester showed higher values for some parameters, e.g., 4994.44% (49,944,400 mg L^?1 and 917 NTU) of turbidity and 4100.00% of phenol when compared to dyeing wastewater of other fibers. Other parameters such as pH, alkalinity, color, phosphorus, nitrogen, sulfides, chlorides, oil and grease, dissolved solids, and chemical and biochemical oxygen demand were also assessed. In addition to individual characterization, this study also presents a correlation of the contribution of each parameter to the final textile effluent. Although dyeing wastewater of polyamide contributes the most in terms of quantity for the final effluent, this study revealed that dyeing wastewater of polyester influenced the most on the final composition of the textile wastewater when evaluating color, turbidity, total iron, biochemical oxygen demand, chemical oxygen demand, phenol, mercury, oil and grease, and total phosphorus. The present study is focused on bringing new insights to provide future research with other strategies to improve the treatment of dyeing wastewater. In addition, some suggestions are also given for wastewater treatments according to type of textile fiber.     

Carbon footprint in corporate logistics operations in the food sector

Global warming is negatively affecting the environment of the planet. This situation has led to the development of international standards, such as the International Organisation for Standardization's DIS 14064‐1 and the Greenhouse Gas Protocol Corporate Standard, both of which measure corporate carbon footprints. These standards provide guidelines that can be applied to different organizational sectors. However, these are not sufficient for controlling the reduction of carbon emissions, because although they propose the use of indicators, they do not explicitly define them. In addition, in the case of emissions from wastewater treatment, they only suggest that the emissions associated with this process be considered. In the present study, an eight‐step, unified methodology based on these two international standards is proposed, focusing on direct emissions. Moreover, the step‐by‐step to data collection, calculations, and the required indicators to control the emissions are defined. The first scope considers direct emissions from sources that are owned or controlled by the company. Methane generation measurement from wastewater treatment has been included in the methodology within Scope 1, as it is the second most polluting gas after carbon dioxide, both of which give rise to global warming. The proposed methodology was tested as a case study in one of the most important companies in the food sector in Colombia.     

A Power Law Model for River Flow Velocity in Iowa Basins

This study explores power law relationships to estimate water flow velocity as a function of discharge and drainage area across river networks. We test the model using empirical data from 214 United States (U.S.) Geological Survey gauging stations distributed over the state of Iowa in the U.S. The empirical data are the measurements of the mean cross‐sectional velocity and concurrent discharge. The data are used to estimate parameters for a state‐wide model and to test for spatial variability for 15 large river basins contained within the state. Spatial differences among the basins are small but some parameters significantly differ from the state‐wide model. Using individual station data, the authors also explore a simpler power law model that disregards dependence on the drainage area. Overall, the study shows that including drainage area improves the model. Our study provides parameter values that can be directly incorporated into a regional scale routing model, and provides a framework for developing flow velocity models for hydraulically similar rivers in the U.S. and the world.     

Modeling the spatial dynamics of regional land use: the CLUE-S model

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.