Dense Vegetation Cover Research Articles

Cemeteries and biodiversity conservation in cities: how do landscape and patch-level attributes influence bird diversity in urban park cemeteries?

Cemeteries can help conserve biodiversity in urban landscapes, but their capacity to support native species is likely to be influenced by variables at different spatial scales. There is growing evidence on how landscape and patch-level attributes influence biodiversity in urban parks. However, there is limited evidence about cemeteries. Park cemeteries are dominated by vegetation because they are managed to simulate traditional parks, and thus, could contribute to the conservation of native fauna in cities. We present the first study on how patch variables (cemetery size and vegetation density) and landscape variables (vegetation cover and road density within 1 km) influence the richness and abundance of native birds in urban park cemeteries. During summer and autumn, we surveyed birds in park cemeteries in the Mediterranean city of Santiago, Chile – a large Latin American city located in a biodiversity hotspot. We recorded 42 bird species (38 native and 4 exotic). We found that cemeteries surrounded by high vegetation cover supported more native birds, whereas cemeteries surrounded by high road density supported low native bird abundance. We also found a seasonal effect: cemeteries supported more individuals of native birds in autumn than in summer, probably due to birds migrating to our study area from higher latitude, altitude, and surrounding environments, in their search for milder weather conditions. Our findings demonstrate that park cemeteries host a variety of native birds, which contributes to maintain biodiversity in urban landscapes. However, the surrounding landscape influences their capacity to support native birds and to conserve biodiversity in cities.

Interspecific prey neighborhoods shape risk of predation in a savanna ecosystem

In central Kenya, Ng'weno et al. used GPS relocations to find lion-killed ungulates and related kills to the surrounding density of prey, vegetation cover, and lion activity. Zebra made up the bulk of lion diets and were killed more frequently in areas with low visibility. Buffalo were killed more frequently when they did not associate with zebra, while hartebeest were killed more frequently in association with zebra. Such neighborhood effects have long been appreciated in studies on plant–herbivore interactions. Ng’weno et al. show that prey neighborhoods also are likely to influence the outcomes of predator-prey dynamics in ecosystems dominated by large mammals. Photo credit: Christian Bopp. Photo credit: Douglas Kamaru. Photo credit: Douglas Kamaru. These photographs illustrate the article “Interspecific prey neighborhoods shape risk of predation in a savanna ecosystem” by Caroline C. Ng'weno, Adam T. Ford, Alfred K. Kibungei, and Jacob R. Goheen published in Ecology. https://doi.org/10.1002/ecy.2698

Using time-series Sentinel-1 data for soil prediction on invaded coastal wetlands.

Coastal soils are particularly sensitive to nonnative species invasion. In this context, spatially explicit soil information is essential for improving the knowledge of the role of soil in changing environments, supporting coastal sustainable management. Synthetic-aperture radar (SAR) data provides an attractive opportunity to monitor soil because the acquisition of images is independent of weather and daylight. However, SAR has not been commonly used for soil prediction. In this study, we firstly investigated the temporal variation of vegetation canopy and the soil-vegetation relationship using Sentinel-1 data in an invaded coastal wetland. And then we built 3D models to predict soil properties at multiple depths. A total of 16 Sentinel-1 images were acquired in a growing season. A series of soil physicochemical properties were examined including soil bulk density, texture, organic/inorganic carbon, pH, salinity, total nitrogen, and C/N ratio, relating to three depth layers in the top 1-m depth. Our results showed that time-series Sentinel-1 data can capture temporal characteristics of vegetation, and VH/VV was more sensitive to the vegetation growth than VH and VV. The soil-vegetation relationship captured by time-series SAR data was beneficial to predict soil properties, especially for soil chemical properties. The models provided permissible prediction accuracy, with an average RPD of 0.99. We concluded that the prior understanding of the temporal variation of SAR data is essential for developing practical soil prediction strategy. Our results highlight that SAR has the potential to predict a diverse set of soil properties in coastal wetlands with dense vegetation cover.

Soil Evaporation in a Shaded Coffee Plantation Derived From Eddy Covariance Measurements

AbstractLittle is known about soil evaporation (Esoil) in shaded coffee plantations. In this study, Esoil and its proportion to total evapotranspiration and rainfall (P) were quantified for a densely shaded Arabica coffee plantation (~80% tree cover) in central Veracruz, Mexico, using eddy covariance (EC) measurements made above the tree canopy and at the boundary between the stem space and canopy of the coffee crop. While measurements above the canopy were made continuously during the 1‐year study period (October 2016 to September 2017), this was not possible for the above‐soil level due to logistical considerations, and hence, annual Esoil was calculated from a relationship between the ratio of the actual to the equilibrium Esoil and surface soil water content. This empirical model was calibrated using 31 days of EC measurements, representing the range in surface soil water content observed during the study period. Examining the above‐canopy and above‐soil EC measurements for quality yielded similar results with regard to stationarity (99% and 85% of the time, respectively) and degree of energy balance closure (81% and 96%, respectively). The permanent and relatively dense vegetation cover provided by the shade trees and coffee plants reduced net radiation at the soil surface to only about 12% of the above‐canopy value. Consequently, Esoil was a minor fraction of evapotranspiration (10–13%) and P (8–9%), with the spread reflecting uncertainties related to the failure to close the energy balance. In addition to the low‐energy availability, Esoil may have been reduced by the presence of a litter layer.

Linking landscape heterogeneity with lake dissolved organic matter properties assessed through absorbance and fluorescence spectroscopy: Spatial and seasonal patterns in temperate lakes of Southern Andes (Patagonia, Argentina)

Hydrological connectivity between terrestrial and aquatic systems is influenced by landscape features. Topography, vegetation cover and type, lake morphometry and climate (seasonality, precipitation) drive the timing, concentration and quality of allochthonous dissolved organic matter (DOM) inputs to lakes, influencing lake metabolism. The impact of climate changes on terrestrial-aquatic linkages depends on regional trends and ecosystems properties. We examined how landscape heterogeneity affects lake DOM in pristine temperate headwater lakes located in sharp bioclimatic gradients at the leeward side of the southern Andes (Patagonia, Argentina), and predicted their potential responses to forecasted changes in regional climate. We assessed DOM properties of deep and shallow lakes spotted along precipitation and altitudinal gradients which reflect on vegetation heterogeneity. Lake DOM (concentration, and chromophoric and fluorescent properties) was related to terrestrial bioclimatic conditions, addressing also DOM bio- and photodegradation processes. Co-effects of climate and vegetation determined the quantity and quality of allochthonous DOM inputs. Higher terrestrial signs showed up at the wettest extreme of the gradient and during the rainy season, being attributable to higher hydrological land-water connectivity, and dense vegetation cover. Under drier conditions, DOM displayed higher photobleaching signs at spatial and temporal scales. The ratio between non-humic and terrestrial humic substances indicated that DOM biodegradation dominates in shallow forested lakes and photodegradation prevails in deep ones, whereas coupled photo- and biological processing shaped the DOM pool of high altitude lakes. Overall, DOM optical metrics captured landscape heterogeneity. Under the forecasted climate changes for Patagonia (decreasing precipitation and increasing temperature), piedmont lakes may experience lower hydrological connectivity, lower terrestrial inputs and, enhanced photobleaching usually associated with longer water residence time. In high altitude lakes, terrestrial DOM inputs are expected to increase due to the upward expansion of native deciduous forests, thus becoming more similar to lakes located lower in the landscape.

Do Red Foxes (Vulpes Vulpes) Increase the Detectability of Scent Marks by Selecting Highly Conspicuous Substrates

In mammals, especially those that are nocturnal or crepuscular, chemical marks usually play a significant role as environmental labels. Scent marks in mammals can have many functions, including territorial defense and communication signals in the mating season. Furthermore, animals can increase the detectability of marks by selecting highly conspicuous locations and substrates on which to mark, such as stones and sticks, on or around faeces, other animal carcasses, anthropogenic features, and plants. Human-carnivore interactions can result in a conflict where perceived damage to livelihoods occurs in socio-economically poor areas. In the Shigar Valley, Karakorum Range, Pakistan, subsistence mixed farming is the predominant land use and red foxes (Vulpes vulpes) are widely persecuted. Understanding the effects of human activity and habitat factors on fox behaviors in the region are lacking. We used line transect surveys aided by a domestic dog (Canis familiaris) to detect fox faeces locations and characterize fox den form 2015-16-17. We encountered 467 fox scats by dog assistance. We tested for associations between scent deposition, and environmental variables including vegetation and substrate type, distribution of livestock carcasses and dung, roads and agricultural land at micro-habitat. We found more fox scats on aromatic plants, shrubs, and on or near livestock feaces and carcasses. Fox scent marking site selection varied for forested and shrub areas relative to open grassland or barren ground and vegetation cover and tree density at the microhabitat scale. The findings suggest that foxes do not avoid human activity per se and anthropogenic benefits (road kill, livestock carrion, crop food sources) may outweigh the costs of persecution. Foxes may also provide ecosystem benefits via seed dispersal, carrion removal and regulation of prey populations.

Landslide recognition and mapping in a mixed forest environment from airborne LiDAR data

A precise, accurate and complete landslide inventory is indispensable for the establishment of reliable landslide susceptibility and hazard maps. In the preparation of landslide inventories, dense vegetation cover is the major obstacle that confounds the topographic signature of landslides. Today, the growing usage of light detection and ranging (LiDAR) technology in the field of geoscience illuminates the mystery of the landscapes cloaked in dense vegetation by providing a new visual acuity to researchers. Turkey, similar to many mid-latitude mountainous countries suffering from landslides, is still continuing landslide inventory mapping with conventional methods such as aerial photo interpretations (API), although 68% of landslide events occurred under dense forest cover in the north of the country. Despite the country-wide medium-scaled landslide catalogs, the number and the abundance of landslides covered by forests remain largely unknown regardless of the increasing availability of high-resolution remote-sensing data. From these motivating insights and drawbacks, the study's focus is to evaluate the capability of mapping landslides by visually analyzing airborne LiDAR DTM derivatives and compare the results with the 1:25,000 scaled API-based inventory to understand the potential contribution of LiDAR technology in Europe's deadliest country (Turkey) in terms of landslides. The landslide mapping results for a test area located in the densely forested Ulus Basin, Western Black Sea region, reveal that the extent and the number of the mapped landslides (n = 902) from the airborne LiDAR data are much higher than those of the available API-based landslide inventory, which includes 67 landslides. Comparative analysis on topographic signatures of landslides is also underpinned on a distinct discrepancy of slope failure diagnostic indicators captured by the two available DEMs derived from LiDAR and 1:25,000 scaled topographic maps, emphasizing the success rate of LiDAR-derived DEM in recognition and mapping landslides with higher precision and accuracy. Together with all analysis results, the landslide recognizability degree assessment based on the forest cover percentage and slope height differences of landslides highlights that the LiDAR data enable landslides to be defined up to 100 m2, while this value is 20 times lower than that of estimated values from API-based landslides. In addition to underlining the contribution of LiDAR technology to the recognition of landslides hidden under dense vegetation, these findings stress the importance of LiDAR data on complete and accurate landslide inventories for production of reliable susceptibility and hazard maps and further a better understanding of the landslide processes and reducing related losses.

Towards improved, cost-effective surveillance of Ixodes ricinus ticks and associated pathogens using species distribution modelling.

Various ticks exist in the temperate hilly and pre-alpine areas of Northern Italy, where Ixodes ricinus is the more important. In this area different tick-borne pathogen monitoring projects have recently been implemented; we present here the results of a twoyear field survey of ticks and associated pathogens, conducted 2009-2010 in North-eastern Italy. The cost-effectiveness of different sampling strategies, hypothesized a posteriori based on two sub-sets of data, were compared and analysed. The same two subsets were also used to develop models of habitat suitability, using a maximum entropy algorithm based on remotely sensed data. Comparison of the two strategies (in terms of number of ticks collected, rates of pathogen detection and model accuracy) indicated that monitoring at many temporary sites was more cost-effective than monthly samplings at a few permanent sites. The two model predictions were similar and provided a greater understanding of ecological requirements of I. ricinus in the study area. Dense vegetation cover, as measured by the normalized difference vegetation index, was identified as a good predictor of tick presence, whereas high summer temperatures appeared to be a limiting factor. The study suggests that it is possible to obtain realistic results (in terms of pathogens detection and development of habitat suitability maps) with a relatively limited sampling effort and a wellplanned monitoring strategy.

Analysis of L-Band SAR Data for Soil Moisture Estimations over Agricultural Areas in the Tropics

The main objective of this study is to analyze the potential use of L-band radar data for the estimation of soil moisture over tropical agricultural areas under dense vegetation cover conditions. Ten radar images were acquired using the Phased Array Synthetic Aperture Radar/Advanced Land Observing Satellite (PALSAR/ALOS)-2 sensor over the Berambadi watershed (south India), between June and October of 2018. Simultaneous ground measurements of soil moisture, soil roughness, and leaf area index (LAI) were also recorded. The sensitivity of PALSAR observations to variations in soil moisture has been reported by several authors, and is confirmed in the present study, even for the case of very dense crops. The radar signals are simulated using five different radar backscattering models (physical and semi-empirical), over bare soil, and over areas with various types of crop cover (turmeric, marigold, and sorghum). When the semi-empirical water cloud model (WCM) is parameterized as a function of the LAI, to account for the vegetation’s contribution to the backscattered signal, it can provide relatively accurate estimations of soil moisture in turmeric and marigold fields, but has certain limitations when applied to sorghum fields. Observed limitations highlight the need to expand the analysis beyond the LAI by including additional vegetation parameters in order to take into account volume scattering in the L-band backscattered radar signal for accurate soil moisture estimation.

The Jawz Valley. Reconstructing an Ottoman ‘waterscape’ in Mount Lebanon

Mount Lebanon, with its complex topography, abundance of water and often dense vegetation cover, has rarely featured in the new and growing field of medieval and Ottoman archaeology of the Levant. The historiography of Lebanon, by contrast, is rich and varied for this period, and addresses rural communities directly. This contribution presents the first results of cross-disciplinary research on a case study, the Jawz Valley, in northern Lebanon. It sets out to reconstruct the essential elements of this waterscape during the Ottoman period. The relationships between hydro-agricultural remains, settlement patterns and shifting or overlapping scales of administration and control of water-related infrastructure are a critical factor in establishing a diachronic perspective of social, economic and political continuity and rupture in this landscape.

Work Skills Needed by Senior Secondary School Graduates in Banana Production Enterprises for Job Security in Enugu State.

The study focused on the work-skills needed by senior secondary school graduates in banana production enterprise for job security. The study was carried out in Enugu State, Nigeria using a descriptive survey research method. Three research questions and three null hypothesis guided the study to achieve the purpose of the study. The null hypothesis was tested at probability of 0.05 level of significance and appropriate degree of freedom. The population of the study consisted of 380 respondents. There was no sampling because the population was manageable. Structured questionnaire made up of 27 items was used for data collection. The instrument was validated by three experts and cronbach Alpha statistics was used to determine the internal consistency of the instrument and a coefficient of 0.78 was obtained. A total of 360 copies of questionnaires were distributed and returned. The data was analyzed using weighted mean and standard deviation to answer the research questions and analysis of variance were used to test the null hypothesis. The findings of the study are that secondary school graduates need work-skills such as choosing a suitable site that is flat with dense vegetation cover, choosing an area with abundant rainfall, clearing the land, marking out the land and dig holes of 60cm x 60cm for planting sucker, apply organic manure inside the holes one month before planting the sucker, collect healthy suckers from existing banana plot etc. The null hypotheses tested showed that there were no significant different between the mean responses of the respondents. Based on these findings it was recommended that government should establish skill acquisition centers in various locations for training youths on banana production, schools should lay much emphasis on practical agriculture which leads to skill acquisition by the students instead of teaching only theory in classroom.

Assessing Submerged Vegetation Roughness in Streambed under Clear Water Condition Using Physical Modeling

Roughness coefficient, also called Manning’s coefficient, is one of the most important hydraulic parameters in the rivers. This coefficient, in addition to the flow conditions, depends on streambed characteristics such as type and density of vegetation. In this study, a physical model in a flume with 7 m length, 0.25 m width and 0.25 m height was conducted to evaluate the streambed roughness coefficient and consequently the discharge passing from waterways. Flume bed was filled using uniform sediment with median grain diameter of 1.9 mm, variation coefficient of 1.4 mm and a thickness of 0.4 m. Roughness coefficient variation in the slopes of 0.2, 0.4 ,and 0.6%, discharges of 4, 6, and 8 L/s and vegetation cover densities as 0, 12, 25, and 50% were investigated. To simulate the covering of streambed, vegetation scrub was used in the experiments. The results showed that by increasing the density of vegetation, roughness coefficient increases while with increasing flow velocity, slope and Froude number decreases. By analyzing the data from this study, streambed roughness coefficient was obtained in terms of different variables as applicable relationships for different conditions of flow and streambed. The results of this study with quantifying the effects of various parameters on the roughness coefficient can be used by water engineers.

Environmental diagnosis of an urban basin from a social–ecological perspective

The critical factor in restoration and conservation of urban streams and their catchments is the human population, however the most of studies of urban ecosystems do not present social descriptors as concrete variables of analysis. The objective of this study is to perform an environmental diagnosis from a social-ecological perspective by considering both ecological and urban development descriptors of an urban basin. We selected 12 sampling sites of the Langueyú upper basin where social and ecological descriptors were determined. We arranged sampling sites according to their physicochemical characteristics (pre-urban, urban and post-urban sites). An ecological index was defined from habitat and biological descriptors: vegetation cover, richness and total density of invertebrates and organic matter. The index determined that urban and post-urban sites showed similar characteristics, and pre-urban sites presented the best habitat and biological conditions. An urbanisation index was defined from urban development descriptors: distance to the stormwater drainage network, number of industries, distance to a house without sewage, impervious surface and housing density. The results showed that the pre-urban and post-urban sites share a greater similarity in relation to the urban descriptors but with different impact in ecological quality. The headwaters in the hills (pre-urban zone) still presents a very good ecological condition (although threatened by urbanisation and tourism); however, once it crosses the dense urban area, no >5 km distance, the environmental degradation is alarming. We were able to determine that the structural measures associated with greater urbanisation, added to illegally connected sewer pipes and illegally industrial connections, produce the ecological degradation of the stream. This environmental diagnosis allowed us a deep understanding of the urbanisation impact on the ecological integrity of an urban stream in a developing country which, like many others, doesn't have monitoring programs or an integrated vision of water resources.

Assessing the impact of dams on riparian and deltaic vegetation using remotely-sensed vegetation indices and Random Forests modelling

Abstract Riparian and deltaic areas exhibit a high biodiversity and offer a number of ecosystem services but are often degraded by human activities. Dams, for example, alter the hydrologic and sediment regimes of rivers and can negatively affect riparian areas and deltas. In order to sustainably manage these ecosystems, it is, therefore, essential to assess and monitor the impacts of dams. To this end, site-assessments and in-situ measurements have commonly been used in the past, but these can be laborious, resource demanding and time consuming. Here, we investigated the impact of three dams on the riparian forest of the Nestos River Delta in Greece by employing multi-temporal satellite data. We assessed the evolution in the values of eight vegetation indices over 27 years, derived from 14 dates of Landsat data. We also employed a modelling approach, using a machine learning Random Forests model, to investigate potential linkages between the observed changes in the indices and a host of climatic and terrestrial predictor variables. Our results show that low density vegetation (0–25%) is more affected by the construction of the dams due to its proximity to anthropogenic influences and the effects of hydrologic regime alteration. In contrast, higher density vegetation cover (50–75%) appears to be largely unaffected, or even improving, due to its proximity to the river, while vegetation with intermediate coverage (25–49%) exhibits no clear trend in the Landsat-derived indices. The Random Forests model found that the most important parameters for the riparian vegetation (based on the Mean Decrease Gini and the Mean Decrease Accuracy) were the distance to the dams, the sea and the river. Our results suggest that management plans of riparian and deltaic areas need to incorporate and take into consideration new innovative management practices and monitoring studies that employ multi-temporal satellite data archives.

Vegetation Area Monitoring Through NDVI Technique: A Case Study of Dengei Pahad Micro Watershed, Khurda District, Odisha

Watershed treatment includes implementation of participatory micro-watershed-based soil and moisture conservation programs and income generation through proper natural resource management areas. This has led to increased productivity and income. Training and holistic management along with aforestation programs has led to reduction of silt flow to the lake. The assessment revealed that land degradation in the drainage basin not only leads to enhanced silt flow into the lagoon but also causes poverty, due to low productivity in the drainage basin. The drainage basin management program is conceived as a long-term participatory process to achieve an environmentally, economically and socially sustainable management of water resources. The present study deals with periodic assessment and monitoring the vegetation cover of the Dengei pahad micro watershed, Khurda District, Odisha, using NDVI techniques. NDVI is the traditional vegetation index used by researchers for extracting vegetation abundance from remotely sensed data. In essence, the algorithm isolates the dramatic increase in reflectance over the visible red to near infrared wavelengths, and normalized it by dividing by the overall brightness of each pixel in those wavelengths. Satellite data of IRS series from 1999 to 2010 and Resources at series from 2011 to 2014 along with other spatial and non-spatial data were used to find out the changes that occurred in vegetation and other land cover categories during the last 16 years. It was analyzed that dense vegetation cover has decreased up to 20.24 Ha in the year 2010 and after the awareness to the local people by CDA, has taken active role to sustain the natural resource and it has shown positive impact after the analysis through Remote Sensing data. Keywords: Micro-watershed, participatory, degradation, sustainable, NDVI, satellite, remote sensing

Экологическая устойчивость почв лесных ландшафтов г.Иркутска и его окрестностей

The forest soils (burozems, sod podzolic soils, gray and gray metamorphic soils) and plant communities, altogether performing important environmental protection functions, were investigated in the vicinity of Irkutsk city in Russia (N52º17'24.03'', E 104º16’50.62"). The preservation of natural forest sites in the residential areas, as well as enhancing of the “green” infrastructure of the city by creating artificial forest stands with sustainable coenotic composition will significantly decrease contamination and pollution. The study assessed the potential of environmental susceptibility of soils in different districts of Irkutsk and its vicinity. The natural soil sustainability potential of the region results from the diversity of parent bedrock material, relief of the terrain, loamy and clay granulometry, derived from the Pleistocene loess-like loams and the Miocene clays, relatively high humus content of predominantly humate-fulvate composition, dense vegetation cover of pronounced biodiversity of trees (pine, aspen and birch), etc. Gray and gray metamorphic soils can be characterized as being environmentally the most sustainable. Taiga biocenoses were shown to contribute significantly to the improvement of the sanitary-hygienic and environmental status of the studied areas. The result underscores an urgent need to take into account soil and soil cover sustainability potential while creating a green environmental protection framework in the city and its vicinity. Sufficient fertility and environmental sustainability of soils in the studied area serve as a stable basis for the preservation of relic park forests and for the development of cultural and recreational landscapes in the region.

Investigations on the parent material of soils of two Nile Valleys with different river dynamics (White Nile and Blue Nile)

Soils of two Nile Valleys (White Nile and Blue Nile) and the neighboring Nubian Sandstone plateaus (Qoz) in Central Sudan were investigated. The White and Blue Niles rise from different areas and are different in their water flow velocity, flood amplitude and flooding time. The results of this study show that sediments of both valleys consist of an allochthonous and a parautochthonous component. The allochthonous part of the White Nile and Blue Nile show different texture and mineralogical composition. It consists of smectite-rich clayey material in the White Nile whereas the Blue Nile sediment contains carbonates, is rich on smectite and is silty-clay. The parauthochthone part in both Nile Valleys is sandy and rich on kaolinite. Its origin is predominantly eolian and fluvio-eolian from Nubian Sandstone. Its amount in the first terraces (youngest terraces) is highest and lowest in the second Terraces. This point out, that the youngest terraces as well as the third terrace on the Blue Nile were developed in a time when the surrounding area was covered with a loose vegetation cover (ergo-dry climate) and the second terraces were developed in a period with a dense vegetation cover (ergo wet climate).

Structure of the benthic macrofauna of an anthropogenic influenced area: Skhira Bay (Gulf of Gabès, central Mediterranean Sea).

Skhira Bay located in the Gulf of Gabès, on the southeastern coast of Tunisia, is an important area in terms of its dense vegetation coverage, wide continental shelf, and fisheries resources. However, this area with a typically micro-tidal range is subject to intensive anthropogenic pressures: soft bottom trawling, chemical pollution from phosphoric acid production, and shipping activity. The present study is the first investigation of the structure of the benthic macrofauna on this part of the Tunisian coast. In April 2010, 28 stations were sampled along four transects from the phosphogypsum outfall on an inshore-offshore gradient. A total of 239 macrobenthos taxa, belonging to nine zoological groups and 140 families, were identified with a dominance of polychaetes (33.5%), crustaceans (29.4%), and mollusks (19.6%). Results show that the stations facing the phosphogypsum discharges are the most disturbed and characterized by a poorly diversified macrofauna. The macrofauna is dominated by carnivores, suspension feeders, and selective deposit feeders, and seems to be linked more to the availability of trophic resources than to disturbance. Four benthic assemblages are identified using Cluster and MDS analyses linked to edaphic factors, such as sediment structure, organic matter content, inshore/offshore gradient, and the proximity of the phosphogypsum outfall. The biotic indices (AMBI and BO2A) calculated from macrofauna data show that the ecological status of Skhira Bay varies overall from moderate to good. This study suggests initiating a long-term monitoring program to improve our understanding of the temporal changes of this ecosystem, to recommend the necessary conservation measures in this area of high-value natural heritage.

Modeling canopy conductance and transpiration from solar-induced chlorophyll fluorescence

Vegetation transpiration (T) is the process of plant water loss through the stomata on the leaf surface and plays a key role in the energy and water balance of the land surface, especially with dense vegetation cover. To date, however, estimation of ecosystem-scale T is still rather uncertain mainly due to errors in modeling canopy resistance or conductance. Considering the intrinsic link between photosynthesis and chlorophyll fluorescence, the recent available remote sensing of solar-induced chlorophyll fluorescence (SIF) provides a valuable opportunity to estimate plants T at large scales. In this study, we demonstrate how remote sensing of SIF relates to canopy stomatal conductance and transpiration at diurnal and seasonal scales with continuous ground measurements of SIF at three flux sites in forest, cropland and grassland ecosystems. The results show that both ground and spaceborne SIF observations are good indicators of canopy conductance at both diurnal and seasonal scales (R2 = 0.57 and 0.74 for forest, R2 = 0.62 and 0.80 for cropland, R2 = 0.52 and 0.63 for grassland, respectively). Then, empirical SIF-based canopy conductance models are employed to estimate hourly and daily transpiration. We evaluate our ecosystem T estimations against latent heat fluxes measured by eddy covariance systems with more satisfactory results for forest (R2 = 0.57 and 0.71), and cropland (R2 = 0.77 and 0.83) than for grassland (R2 = 0.13 and 0.22) at hourly and daily time scales. Our results suggest the potential of remotely-sensed SIF for estimating canopy conductance and plant transpiration, but a more mechanistic understanding is needed for their link.

Epidemiological estimates of Acute Respiratory diseases and Asthma using Geostatistical tools in Rawalpindi, Pakistan

Event Abstract Back to Event Epidemiological estimates of Acute Respiratory diseases and Asthma using Geostatistical tools in Rawalpindi, Pakistan Ahmad S. Saeed1* and Javiria Younis1 1 Fatima Jinnah Women University, Pakistan Respiratory diseases are a major cause of death in developing countries. Allocation of scarce resources in developing countries is a major problem for which identification of high risk areas and patterns of disease spread are necessary. A Cohort study design was used in this study.Using 2011-2015 diseased person data for Acute Respiratory Diseases and Asthma from District Health Office, Rawalpindi we examined emerging hotspots and spatiotemporal trends of diseases spread by using geostatistical tools in ArcGIS 10.2. Climatic parameters and land use was also correlated with disease incidence to examine the effect on disease spread. Pattern of diseases was found to be random throughout the district and incidence rate per thousand people was highest for tehsil Kotli Sattian. Most of the hotspots lied in the areas with large settlements and dense vegetation cover. Cold related Asthma and Acute Respiratory Diseases was also revealed along with the seasonal outbreaks of Asthma in mid spring and autumn. Shift of Asthma towards denser vegetation areas and towards agricultural areas was seen for Acute Respiratory Diseases. Climatic parameters such as temperature and rainfall also showed strong correlation with disease incidence. Rawalpindi district is prone to cold weather related Asthma and Acute Respiratory Diseases. There is a need to conduct detailed study on aeroallergens and air pollution in study area especially in high risk areas to control the spread and intensity of these respiratory diseases. Acknowledgements Authors are thankful to District Health Office for provision of data Keywords: Respiratory diseases, Hotspot analysis, Air Pollutants, Pakistan, Asthama Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019. Presentation Type: Regular oral presentation Topic: Emerging GIS, data science and sensor technologies adapted to animal, plant and human health, including precision medicine and precision farming Citation: Saeed AS and Younis J (2019). Epidemiological estimates of Acute Respiratory diseases and Asthma using Geostatistical tools in Rawalpindi, Pakistan. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00005 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Jun 2019; Published Online: 27 Sep 2019. * Correspondence: Mx. Ahmad S Saeed, Fatima Jinnah Women University, Rawalpindi, Pakistan, drsaeed@fjwu.edu.pk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ahmad S Saeed Javiria Younis Google Ahmad S Saeed Javiria Younis Google Scholar Ahmad S Saeed Javiria Younis PubMed Ahmad S Saeed Javiria Younis Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.