Identification des facteurs environnementaux responsables de la présence de Campylobacter Jéjuni dans les eaux de surface de l'Estrie (Québec)

Background : The sources and the epidemiology of Campylobacter jejuni (CJ) in environmental water are not well understood. We developed a spatial analysis methodology able to identify the main environmental factors predicting the presence and quantity of Campylobacter in river water. Methods : For two years, water samples were collected weekly and scanned for CJ and fecal coliforms at 32 sampling sites of Estrie hydrographic network, Québec. The quantity of CJ in water was estimated using the Most Probable Number method (MPN). The 32 sampling sites were linked to their catchment area; 10 of them were excluded from the analysis, because their hydrographic basin was not independent from the other sites. For each site, the following environmental variables were included: Water flow, slope, land-cover, land-use including type of farming, animal density, total precipitation in the 3 days prior to water sampling. A stepwise multivariate regression was realized across the different analysis windows to define the size of the area upstream from the sampling sites (from 1.5 to 24 km) which was the most closely associated with the mean quantity of CJ, and which environmental factors were associated with a higher mean quantity of CJ in water. Results : Preliminary results show that an area defined by a radius of 14 km upstream of the sample site was the most contributing zone for the bacteria (r2=0.38, p=0.002). Within this 14 km area, the only significant variable associated with a higher mean quantity of CJ was bovine density (p=0.002). When analyzing the data within a 120 m buffer zone across 14 km upstream of the sampling sites (r2=0.40, p=0.001), the only significant variable associated with a higher mean quantity of CJ was the percentage of agricultural surface (p=0.001). Conclusions : These results suggest a strong implication of bovine density in conjunction with crops and associated manure spreading on the quantity of CJ in environmental water

Spatial priorities for conserving the most intact biodiverse forests within Central Africa

The forests of Central Africa contain some of Earth's few remaining intact forests. These forests are increasingly threatened by infrastructure development, agriculture, and unsustainable extraction of natural resources (e.g. minerals, bushmeat, and timber), all of which is leading to deforestation and forest degradation, particularly defaunation, and hence causing declines in biodiversity and a significant increase in carbon emissions. Given the pervasive nature of these threats, the global importance of Central African forests for biodiversity conservation, and the limited resources for conservation and sustainable management, there is a need to identify where the most important areas are to orientate conservation efforts. We developed a novel approach for identifying spatial priorities where conservation efforts can maximize biodiversity benefits within Central Africa's most intact forest areas. We found that the Democratic Republic of Congo has the largest amount of priority areas in the region, containing more than half, followed by Gabon, the Republic of Congo and Cameroon. We compared our approach to one that solely prioritizes forest intactness and one that aims to achieve only biodiversity representation objectives. We found that when priorities are only based on forest intactness (without considering biodiversity representation), there are significantly fewer biodiversity benefits and vice versa. We therefore recommend multi-objective planning that includes biodiversity representation and forest intactness to ensure that both objectives are maximized. These results can inform various types of conservation strategies needed within the region, including land-use planning, jurisdictional REDD + initiatives, and performance related carbon payments, protected area expansion, community forest management, and forest concession plans

Identification des facteurs environnementaux responsables de la présence de Campylobacter Jéjuni dans les eaux de surface de l'Estrie (Québec)

Background : The sources and the epidemiology of Campylobacter jejuni (CJ) in environmental water are not well understood. We developed a spatial analysis methodology able to identify the main environmental factors predicting the presence and quantity of Campylobacter in river water. Methods : For two years, water samples were collected weekly and scanned for CJ and fecal coliforms at 32 sampling sites of Estrie hydrographic network, Québec. The quantity of CJ in water was estimated using the Most Probable Number method (MPN). The 32 sampling sites were linked to their catchment area; 10 of them were excluded from the analysis, because their hydrographic basin was not independent from the other sites. For each site, the following environmental variables were included: Water flow, slope, land-cover, land-use including type of farming, animal density, total precipitation in the 3 days prior to water sampling. A stepwise multivariate regression was realized across the different analysis windows to define the size of the area upstream from the sampling sites (from 1.5 to 24 km) which was the most closely associated with the mean quantity of CJ, and which environmental factors were associated with a higher mean quantity of CJ in water. Results : Preliminary results show that an area defined by a radius of 14 km upstream of the sample site was the most contributing zone for the bacteria (r2=0.38, p=0.002). Within this 14 km area, the only significant variable associated with a higher mean quantity of CJ was bovine density (p=0.002). When analyzing the data within a 120 m buffer zone across 14 km upstream of the sampling sites (r2=0.40, p=0.001), the only significant variable associated with a higher mean quantity of CJ was the percentage of agricultural surface (p=0.001). Conclusions : These results suggest a strong implication of bovine density in conjunction with crops and associated manure spreading on the quantity of CJ in environmental water

Forest condition in the Congo Basin for the assessment of ecosystem conservation status

Quantifying ecological condition, notably the extent of forest degradation is important for understanding and designing measures to protect biodiversity and enhancing the capacity of forests to deliver ecosystem services. Conservation planning, particularly the prioritization of management interventions for forests, is often lacking spatial data on forest degradation, and it is often overlooked within decision-making processes. We develop a continuous metric termed Forest Condition (FC) which aims to measure the degree of forest degradation on a scale from 0 to 100, incorporating the temporal history of forest change over any spatial extent. We parameterize this metric based on estimated changes in above ground biomass in the context of forest fragmentation over time to estimate a continuous measure of forest degradation for Congo Basin countries. We estimate that just <70% of Congo Basin forests remain fully intact, a decrease from 78% in the year 2000. FC was validated by direct remote sensing measurements from Landsat imagery for DRC. Results showed that FC was significantly positively correlated with forest canopy cover, gap area per hectare, and magnitude of temporal change in Normalized Burn Ratio. We tested the ability of FC to distinguish primary and secondary degradation and deforestation and found significant differences in gap area and spectral anomalies to validate our theoretical model. We apply the IUCN Red List of Ecosystems criteria to demonstrate the integration of forest condition to assess the risk of ecosystem collapse. Based on this assessment, we found that without including FC in the assessment of biotic disruption, 12 ecosystems representing over 11% of forested area in 2015 would not have been assigned a threat status, and an additional 9 ecosystems would have a lower threat status. Our overall assessment of ecosystems found about half of all Congo Basin ecosystem types, accounting for 20% of all forest area are threatened to some degree, including 4 ecosystems (<1% of total area) which are critically engendered. FC is a transferrable and scalable assessment to support forest monitoring, planning, and management

Assessing spatial patterns of burn severity for guiding post-fire salvage logging in boreal forests of Eastern Canada

Areas affected by forest fires are increasing worldwide, making salvage logging (i.e., harvesting fire-affected trees) an increasingly used practice to reduce the economic impacts of fire on forestry. However, salvage logging can have strong ecological impacts, notably on post-fire forest regeneration and biodiversity. Burn severity (i.e., the degree to which fires impact the vegetation and soil) is also a central element that interacts with pre-fire forest characteristics and salvages logging to control post-fire forest dynamics and biodiversity. In an ecosystem-based forest management context, spatial patterns of burn severity should thus be considered when planning salvage logging operations. This study presents a simple and innovative method to generate burn severity maps with Landsat and Sentinel-2 multispectral imageries to support salvage logging operations rapidly after a fire event. We assembled a unique dataset involving 330 plots from 10 burns (from 2010 to 2020) in which burn severity has been estimated on the field using the composite burn index (CBI) approach in eastern North America. CBI values were modelled as a univariate function of changes in spectral indices using the first cloud-free post-fire satellite images taken after the burns. Our results demonstrate that using free satellite images with straightforward methods can produce reliable and ecologically meaningful burn severity maps within the few weeks following a fire event. The method was then applied to a case study with salvage logging that illustrates how our burn severity maps could be a useful tool for guiding post-fire forestry operations in an ecosystem-based management context. We combined burn severity maps with pre-fire forest composition and age maps to assess immediate post-fire forest. We discuss how such an approach helps to guide salvage planning and maintain residual forests that are representative of the initial post-fire spatial variability in burn severity and pre-fire vegetation. We conclude that rapid mapping of burn severity after a forest fire event may offer many other applications for identifying and managing recently burned forests