Remote sensing in post-fire impact assessment and vegetation recovery monitoring

Although wildfires are considered an integral part of many terrestrial ecosystems, their regimes have been altered by human activities. With the increased occurrence of droughts, resulting from climate change, the frequency and intensity of fires are expected to increase in many areas, making our capacity to manage them more difficult in the near future. From an ecological perspective, fires can be considered as repetitive and common disturbances leading to a complete transformation of the ecosystem, particularly in its floristic composition. In addition, fires can affect a large variety of ecosystem processes, altering the ecological cycling of nutrients, affecting the natural cycle of vegetation succession and altering organic matter turnover. However, the impacts of fires on ecological processes and local biodiversity vary greatly among regions, with implications for management and restoration. Precise information about the extent and type of fire and also on the post-fire vegetation recovery is, therefore, required for the estimation of ecological and economic losses. Satellite observations are a valuable tool for the monitoring of dynamic processes occurring at the earth surface because of their synoptic coverage and regular temporal sampling. However, classical methods for change detection are often not capable of detecting land cover changes within time series that are heavily influenced by seasonal climatic variations. In this study, we mapped wildfires (occurring from 2009 till 2011) at the Cávado River basin (NE Portugal) and analyzed vegetation recovery in a Landsat time series acquired from 2004 to 2015. We focused our attention on the dynamics of vegetation recovery using FAPAR vegetation Index representing the fraction of incoming solar radiation in the photosynthetically active radiation that is absorbed by the green parts of the canopy. Specifically, we assessed: 1) the fire severity and effect, detecting changes within the trend and seasonal components of time series; 2) the vegetation recovery based on Recovery Trend Index and Cumulative Relative Recovery Index. Our findings show the importance of remote sensing data series in the assessment of the fire severity and evaluation of the degree of post-fire recovery. Furthermore, the use of remote sensing improved our ability to i) assess post-fire impacts accurately, ii) identify the territory segments at risk from exposure, and iii) develop and plan novel mitigation strategies to reduce potential wildfire impacts that might be used to promote vegetation recovery and conserve regional biodiversit

Drought effects on freshwater macroinvertebrate community in the Mediterranean: ecological network analysis as an innovative tool for bioassessment

Freshwater ecosystems in the Mediterranean region are under high pressure. Predictions point to an increase in water scarcity with negative implications to the sustainability of freshwater resources. Models at the local and regional level forecast that water stress may become particularly acute in the south-west USA, the Mediterranean Basin and the Middle East. On the other hand, at the global scale, water demand has doubled over the last fifty years due to increased demography and water intensive use. It is therefore essential to develop tools able to quickly detect environmental drought effects and establish measures that minimize their associated socio-economic impacts. From an ecological perspective, droughts are considered to be a ‘ramp disturbance’, whose effects on biological communities is influenced by factors such as timing, duration, intensity and the presence of refuges. As flows decrease, habitat space is generally reduced; organisms respond to these conditions by continuous colonisation–extinction processes that often lead to a reduction in their density or even extirpation. Network analysis can be a powerful tool to obtain useful information about the pattern of species incidence and/or species co-occurrence, revealing complex direct and indirect effects of stressors on biotic communities, beyond the simple loss or gain of species. Here, we tested how drought dynamics in rivers influence the modular partitioning of macroinvertebrates co-occurrence networks using different datasets within the Mediterranean region, covering different spatial and temporal drought surveys. We postulate that under severe drought events the contraction of available habitats/resources leads to an increasing modularity. The higher modular partitioning of networks clearly indicate that the pattern of species co-occurrence is influenced in a nontrivial way by the drought period, influencing how each species aggregate or segregate in space and time. Our findings suggest that network modularity is a key tool for biomonitoring, able to discriminate the role of drought in different datasets and giving us better information than metrics from standard methods, with the advantage of requiring the same sampling efforts as current monitoring procedures. We advocate the use of such tool to improve our capacity to quickly detect environmental drought effects and accurately assess the ecological status of Mediterranean streams under multiple stressor

Remote sensing depicts riparian vegetation responses to water stress in a humid Atlantic region

Riparian areas in the Cantabrian Atlantic ecoregion (northwest Portugal) play a key role in soil formation and conservation, regulation of nutrient and water cycle, creation of landscape aesthetic value and the preservation of biodiversity. The maintenance of their ecological integrity is crucial given the ever increase in multiple anthropogenic (water demand and agriculture) and climatic pressures (droughts and extreme events). We developed a transferable remote sensing approach, taking advantage of the latest freely available technologies (Sentinel-2 and Copernicus Land products), to detect intra-annual and inter-annual changes in riparian vegetation productivity at the river basin scale related to water stress. This study has used the normalized difference vegetation index (NDVI) to investigate riparian vegetation productivity dynamics on three different vegetation types (coniferous, broadleaved and grassland) over the past 5 years (2015-2019). Our results indicated that inter-annual seasonality differed between drier (2017) and wetter (2016) years. We found that intra-annual dynamics of NDVI were influenced by the longitudinal river zonation. Our model ranked first (r2m = 0.73) showed that the productivity of riparian vegetation during the dry season was positively influenced by annual rainfall and by the type of riparian vegetation. The emergent long lags between climatic variation and riparian plant productivity provides opportunities to forecast early warnings of climatically-driven impacts. In addition, the different average productivity levels among vegetation types should be considered when assessing climatic impacts on riparian vegetation. Future applications of Sentinel 2 products could seek to distinguish riparian areas that are likely to be more vulnerable to changes in the annual water balance from those that are more resistant under longer-term changes in climate.Contrato-Programa UIDB/04050/2020. ERA4CS/0004/2016. CLIMALERT: Climate Alert Smart System for Sustainable Water and Agriculture, an ERA-NET initiated by JPI Climate (ERA4CS programme) co-funded by the EU commission (Grant Agreement 690462) and FCT (ERA4CS/0004/2016). This work was supported by the “Contrato-Programa” UIDB/04050/2020 funded by national funds through the FCT I.P. (GP

Non-interactive effects drive multiple stressor impacts on the taxonomic and functional diversity of atlantic stream macroinvertebrates

Freshwaters are considered among the most endangered ecosystems globally due to multiple stressors, which coincide in time and space. These local stressors typically result from land-use intensification or hydroclimatic alterations, among others. Despite recent advances on multiple stressor effects, current knowledge is still limited to manipulative approaches minimizing biological and abiotic variability. Thus, the assessment of multiple stressor effects in real-world ecosystems is required. Using an extensive survey of 50 stream reaches across North Portugal, we evaluated taxonomic and functional macroinvertebrate responses to multiple stressors, including marked gradients of nutrient enrichment, flow reduction, riparian vegetation structure, thermal stress and dissolved oxygen depletion. We analyzed multiple stressor effects on two taxonomic (taxon richness, Shannon-diversity) and two trait-based diversity indices (functional richness, functional dispersion), as well as changes in trait composition. We found that multiple stressors had additive effects on all diversity metrics, with nutrient enrichment identified as the most important stressor in three out of four metrics, followed by dissolved oxygen depletion and thermal stress. Taxon richness, Shannon-diversity and functional richness responded similarly, whereas functional dispersion was driven by changes in flow velocity and thermal stress. Functional trait composition changed along a major stress gradient determined by nutrient enrichment and oxygen depletion, which was positively correlated with organisms possessing fast-living strategies, aerial respiration, adult phases, and gathering-collector feeding habits. Overall, our results reinforce the need to consider complementary facets of biodiversity to better identify assembly processes in response to multiple stressors. Our data suggest that stressor interactions may be less frequent in real-word streams than predicted by manipulative experiments, which can facilitate mitigation strategies. By combining an extensive field survey with an integrative consideration of multiple biodiversity facets, our study provides new insights that can help to better assess and manage rivers in a global change context.This work was supported by the project STREAMECO: Biodiversity and ecosystem functioning under climate change: from the gene to the stream (PTDC/CTA-AMB/31245/2017), funded by the Portuguese Foundation for Science and Technology (FCT) and the European Regional Development Fund (ERDF) through the COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI). This work was also supported by the River2Ocean project (NORTE-01-0145- FEDER-000068), co-financed by the European Regional Development Fund (ERDF), through Programa Operacional Regional do Norte (NORTE2020); by CCDR-N (Norte Portugal Regional Coordination and Development Commission) and European Funds (FEDER/POCI/COMPETE2020) through the project AgriFoodXXI (NORTE-01-0145-FEDER-000041); and by the “ContratoPrograma” UIDB/04050/2020 funded by national funds through the FCT I.P., the Centre of Molecular and Environmental Biology (CBMA). This work had the support of national funds through Portuguese Foundation for Science and Technology (FCT), under the project LA/P/0069/ 2020 granted to the Associate Laboratory ARNET. CG-C was funded by ”la Caixa” Foundation (ID 100010434), by means of a Junior Leader Fellowship contract (LCF/BQ/PR22/11920005)

Remote sensing indicators to assess riparian vegetation and river ecosystem health

Environmental managers need information to quickly detect which stressor combinations should be addressed to reverse river degradation across large study areas. The pivotal role of riparian vegetation in regulating thermal regimes and inputs of light, nutrients and organic matter has made it a major target of stressor-mitigation and conservation actions. However, due to the dendritic and extensive nature of river networks, field-based monitoring of local riparian conditions is expensive and time-consuming. Ongoing developments in remote sensing offer an unparalleled opportunity to address this challenge. Nonetheless, there is still a limited understanding of the capacity of remote sensing indicators to predict changes in local riparian and river conditions, urging for local calibration with in situ measurements. This study aims to evaluate the capacity of remote sensing to detect impacts on quality elements commonly used in river biomonitoring: riparian vegetation, abiotic river condition and macrophyte biomass. To this end, four remote sensing metrics were tested against field-based indicators in 50 stream locations from four river basins across the Northwest of Portugal: i) the lateral riparian continuity at reach scale (riparian forest buffer width), ii) the riparian vegetation density at reach scale (Normalized Difference Vegetation Index, NDVI100m), and iii) the land use intensification at both reach (LUI100m) and iv) segment (LUI500m) scales. We found that the combination of remote sensing variables (riparian forest buffer width and the land use intensification index) correlated with riparian vegetation quality and dissolved inorganic nitrogen concentrations. We also found that the riparian vegetation density was able to predict changes in vascular plant biomass except for bryophytes. Our study provides new insights on the capacity of satellite-based indicators to assess riparian and river health, illustrating their utility for land and water managers, to identify and monitor, at a reduced cost and time, po- This work was supported by the River2Ocean project (NORTE-01-0145-FEDER-000068), co-financed by the European Regional Development Fund (ERDF), through Programa Operacional Regional do Norte (NORTE 2020).The work was also supported by the "Contrato-Programa" UIDB/04050/2020 funded by national funds through the FCT I.P., the Centre of Molecular and Environmental Biology (CBMA). CG-C was supported by a "Juan de la Cierva -Incoporacion" contract (MINECO, IJC2018-036642-I). CCS was supported by the "Financiamento Programatico" UIDP/04050/2020 funded by national funds through the FCT I.P

The CLIMALERT project: Climate alert smart system for sustainable water and agriculture

The vulnerability of sensitive European regions to hydro-meteorological extremes has increased dramatically over the past few decades. Extreme weather and climate events are increasingly happening worldwide due to ongoing climate change. As a consequence, hydro- meteorological disaster events are affecting the European economy, environment and society, with impacts on food production, food distribution infrastructure, livelihood assets and human health, in both rural and urban areas. Meanwhile, climate services have started to be developed to further anticipate the impacts of climate variability and to apply climate forecasts in different sectors, such as agriculture and water management. However, connections between climate information users and providers are still weak. The CLIMALERT project emerges to provide climate information in a format that prospective users find it easy to understand and/or incorporate into decision-making. The project main goals are: i) strengthen the link between climate research, water resources and the agriculture sector to assist the management of natural resources, enhance agricultural livelihoods and reduce underlying causes of vulnerability, ii) improve the techniques and tools currently used to incorporate weather and climate information into risk assessment and decision making in agriculture and water sectors, and, iii) contribute to assist decision- makers in the implementation of adaptation and mitigation strategies. In this talk, we will present the project framework, the study areas, the engagement with stakeholders, the selection of climate and hydrological indicators, and the development of an alert system platform that aims to contribute to reduce the risks and vulnerabilities for the agriculture and water management sectors, providing economically valuable services and long-term benefits to farmers and societyERA4CS/0004/2016 - CLIMALER

Subpathotypes of Avian Pathogenic Escherichia coli (APEC) Exist as Defined by their Syndromes and Virulence Traits

Avian pathogenic Escherichia coli (APEC) strains cause different types of systemic extraintestinal infections in poultry, collectively termed colibacillosis, which can cause significant economic losses in the poultry industry. To date, there have been no descriptions of genes or characteristics that allow for the classification of avian strains pathotypes responsible for causing specific diseases in their hosts. In this study we aimed to characterize avian E. coli strains representing 4 groups, including one of commensal strains (AFEC – Avian Fecal Escherichia coli) and 3 groups of APEC strains, where each group is responsible for causing a different disease syndrome in their respective hosts (septicemia, omphalitis and swollen head syndrome). We chose to examine several biological characteristics of these strains including: adhesion to eukaryotic cells, pathogenicity levels according to the lethal dose (50%) assay, phylogenetic group and virulence gene profiles. The comparison of strains based on these genotypic and phenotypic traits, using multivariate statisticals tools and complex networks, allowed us to infer information about the population structure of the studied groups. Our results indicate that APEC strains do not constitute a unique homogeneous group, but rather a structured set of subgroups, where each one is associated with a specific infectious syndrome which can possibly be used to define pathotypes or subpathotypes within APEC strains. These results offer new possibilities with which to study the genes responsible for various pathogenetic processes within APEC strains, and for vaccine development. It may be important to consider these subgroups when developing a vaccine in an effort for obtain cross protection, which has not yet been successfully accomplished when working with APEC strains

Effect of partially replacing corn with sugar cane molasses on blood parameters and composition of the M. longissimus thoracis of growing pigs

The effect of sugar cane molasses, as a partial replacement to corn in the diet, on blood parameters and composition of the M. longissimus thoracis (LT) in growing pigs was explored in this study. Twenty female pigs aged 63 days, and weighing 28.98 ± 3.56 kg, were randomly assigned to either the control or sugar cane molasses treatments. Molasses was included at the 3% level to partially replace corn in their diet. Blood samples were collected at the beginning and end of the experiments. The animals were slaughtered at 110 days of age after 47 days in the experiment, weighing 67.9 ± 5.58 kg, and an LT muscle sample was extracted and evaluated. Each animal was considered an experimental unit. The treatment had no effect on the length and area of the LT muscle. Backfat thickness was reduced when using the sugar cane molasses treatment (5.80 mm) compared to the control treatment (8.90 mm) (P < 0.05). Higher enzyme gamma-glutamyl transferase (GGT) levels were observed in animals of the control treatment (67.10 IU/L) compared to animals treated with the sugar cane molasses treatment (49.90 IU/L) (P < 0.05). Moreover, the proximal composition, fatty acid profile, and quality were not influenced by treatment. Sugar cane molasses, used as an energy source to partially replace corn in the diet of growing pigs at a level of 3%, reduced the backfat thickness of the pig carcass and improved the serum concentration of the enzyme gamma-glutamyl transferase in pigs. Key words: eye muscle area; fatty acids; meat; pig; subcutaneous fat thicknes