scholarly journals Canada Goose Gosling Mortality During Prefledging and Early Migration on Akimiski Island, Nunavut

2019 ◽  
Vol 10 (2) ◽  
pp. 314-322
Author(s):  
Rodney W. Brook ◽  
James O. Leafloor ◽  
Kenneth F. Abraham ◽  
C. Davison Ankney ◽  
Keith A. Patton

Abstract Mortality rates for precocial avian species are highest during their first year of life. For harvested species, including waterfowl, it is particularly difficult to determine causes of mortality using standard mark–recapture techniques. The timing and cause of nonhunting mortality is difficult for researchers to distinguish, and therefore, difficult to incorporate into management decisions. We marked flightless Canada goose Branta canadensis interior goslings with radio transmitters to determine the timing of mortality prior to harvest during the fall migration. We tracked survival of 206 goslings for 2 mo from an average of 50 d of age to just prior to the fall migration departure from the breeding grounds in 1999 and 2000. The most parsimonious model from a set of candidate models describing probability of survival showed clear differences between years and suggested that survival was affected by gosling size (largest survived better) and hatch timing disparity. We indexed hatch timing disparity by measuring the difference between gosling hatch date and the date of the estimated peak in forage quality as determined by the normalized difference vegetation index. The latest hatched goslings presumably had the lowest quality forage available to them. Both size and hatch timing disparity concur with a mortality cause that is most likely from complications due to malnutrition. The estimated survival probability of goslings to 51 d post marking was 0.31 (95% confidence limit = 0.22 to 0.44) in 1999 and 0.69 (95% confidence limit = 0.57 to 0.83) in 2000. Managers can make better informed decisions concerning the utility of harvest regulation in the conservation of juvenile Canada geese by better understanding the timing, causes, and annual variation of their mortality.

2020 ◽  
Vol 16 (6) ◽  
pp. 20200155
Author(s):  
Claudie Pageau ◽  
Christopher M. Tonra ◽  
Mateen Shaikh ◽  
Nancy J. Flood ◽  
Matthew W. Reudink

To avoid energy allocation conflicts, birds generally separate breeding, migration and moult during the annual cycle. North American passerines typically moult on the breeding grounds prior to autumn migration. However, some have evolved a moult-migration strategy in which they delay moult until stopping over during autumn migration. Rohwer et al . (2005) proposed the ‘push–pull hypothesis' as an explanation for the evolution of this moult strategy, but it has not been empirically tested. Poor conditions on the breeding grounds at the end of the summer would push birds to depart prior to moult, while productive stopover locations would pull them. We tested for a relationship between moult-migration and breeding grounds aridity as measured by the normalized difference vegetation index. Our results strongly support the ‘push' aspect of the push–pull hypothesis and indicate that arid breeding grounds, primarily in western North America, would drive species to evolve stopover moult-migration, although this relationship may depend upon migration distance.


2009 ◽  
Vol 18 (7) ◽  
pp. 755 ◽  
Author(s):  
Imma Oliveras ◽  
Marc Gracia ◽  
Gerard Moré ◽  
Javier Retana

In Mediterranean ecosystems, large fires frequently burn under extreme meteorological conditions, but they are usually characterized by a spatial heterogeneity of burn severities. The way in which such mixed-severity fires are a result of fuels, topography and weather remains poorly understood. We computed fire severity of a large wildfire that occurred in Catalonia, Spain, as the difference between the post- and pre-fire Normalized Difference Vegetation Index (NDVI) values obtained through Landsat images. Fuel and topographic variables were derived from remote sensing, and fire behavior variables were obtained from an exhaustive reconstruction of the fire. Results showed that fire severity had a negative relationship with percentage of canopy cover, i.e. green surviving plots were mainly those with more forested conditions. Of the topographic variables, only aspect had a significant effect on fire severity, with higher values in southern than in northern slopes. Fire severity was higher in head than in flank and back fires. The interaction of these two variables was significant, with differences between southern and northern aspects being small for head fires, but increasing in flank and back fires. The role of these variables in determining the pattern of fire severities is of primary importance for interpreting the current landscapes and for establishing effective fire prevention and extinction policies.


Author(s):  
Katarzyna Dabrowska-Zielinska ◽  
Jan Musial ◽  
Alicja Malinska ◽  
Maria Budzynska ◽  
Radoslaw Gurdak ◽  
...  

Soil moisture (SM) plays an essential role in environmental studies related to wetlands, an ecosystem sensitive to climate change. Hence, there is the need for its constant monitoring. SAR (Synthetic Aperture Radar) satellite imagery is the only mean to fulfill this objective regardless of the weather. The objective of the study was to develop the methodology for SM retrieval under wetland vegetation using Sentinel-1 (S-1) satellite data. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in northeastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The NDVI (Normalized Difference Vegetation Index) was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to soil moisture retrieval for a broad range of NDVI values and soil moisture conditions. The new methodology is based on research into the effect of vegetation on backscatter () changes under different soil moisture and vegetation (NDVI) conditions. It was found that the state of the vegetation may be described by the difference between  VH and  VV, or the ratio of  VV/VH, as calculated from the Sentinel-1 images. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the new developed models and includes the derived indices based on S-1, allowed the estimation of SM for peatlands with reasonable accuracy (RMSE ~ 10 vol. %). Due to the temporal frequency of the two S-1 satellites’ (S-1A and S-1B) acquisitions, it is possible to monitor SM changes every six days. The conclusion drawn from the study emphasizes a demand for the derivation of specific soil moisture retrieval algorithms that are suited for wetland ecosystems, where soil moisture is several times higher than in agricultural areas.


2017 ◽  
Vol 26 (45) ◽  
Author(s):  
Michael Ezequiel Gómez-Rodríguez ◽  
Francisco José Molina-Pérez ◽  
Diana María Agudelo-Echavarría ◽  
Julio Eduardo Cañón-Barriga ◽  
Fabio De Jesús Vélez-Macías

The municipality of Nechí (Antioquia, Colombia) has a long mining history associated with the extraction of gold. This paper evaluates the evolution of land cover changes caused by this mining activity over 24 years. The spatial analysis was based on the Normalized Difference Vegetation Index (NDVI) of three LANDSAT images (1986, 1996 and 2010). The difference in NDVI values between 1986 and 2010 were used to determine the actual state of vegetation, the direction of change (improvement, stability or deterioration), and the area associated with each soil cover. Polygons for different types of coverage (forest, pasture, bare soil, and water bodies) were extracted from each satellite image to quantify the changes and develop land cover maps for each year. Results show that almost 124.8 km² of forest have been lost during the analyzed period. By contrast, water bodies gained an area of 66.3 km². Both results may be related to the type of gold exploitation in the region.


2020 ◽  
Vol 12 (18) ◽  
pp. 2879
Author(s):  
Valentine Aubard ◽  
João E. Pereira-Pires ◽  
Manuel L. Campagnolo ◽  
José M. C. Pereira ◽  
André Mora ◽  
...  

Fuel break (FB) networks are strategic locations for fire control and suppression. In order to be effective for wildfire control, they need to be maintained through regular interventions to reduce fuel loads. In this paper, we describe a monitoring system relying on Earth observations to detect fuel reduction inside the FB network being implemented in Portugal. Two fast automated pixel-based methodologies for monthly monitoring of fuel removals in FB are developed and compared. The first method (M1) is a classical supervised classification using the difference and postdisturbance image of monthly image composites. To take into account the impact of different land cover and phenology in the detection of fuel treatments, a second method (M2) based on an innovative statistical change detection approach was developed. M2 explores time series of vegetation indices and does not require training data or user-defined thresholds. The two algorithms were applied to Sentinel-2 10 m bands and fully processed in the cloud-based platform Google Earth Engine. Overall, the unsupervised M2, which is based on a Welch t-test of two moving window averages, gives better results than the supervised M1 and is suitable for an automated countrywide fuel treatment detection. For both methods, two vegetation indices, the Modified Excess of Green and the Normalized Difference Vegetation Index, were compared and exhibited similar performances.


ÈKOBIOTEH ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 178-185
Author(s):  
I.R. Tuktamyshev ◽  
◽  
P.S. Shirokikh ◽  
R.Y. Mullagulov ◽  
◽  
...  

Abandoned arable land is a widespread phenomenon in land use. Methods based on the use of remote sensing data are most suitable for studying and monitoring farmlands overgrown with forest. Multispectral satellite images and vegetation indices can reflect the difference at certain stages of the successional development of fallow vegetation. The aim of the work is to evaluate the informative value of individual channels of medium-resolution images of Landsat satellites and the normalized difference vegetation index (NDVI) for identifying vegetation areas at various stages of reforestation succession on abandoned arable land in the zone of distribution of broad-leaved forests in the Urals. As the source material we used 30 georeferenced relevés of different overgrowth stages made in 2012, and 9 cloudless Landsat 5 TM and Landsat 7 ETM+ images for the period from April to October 2011. Using the data, NDVI and values of three spectral bands (Red, NIR, Thermal) were calculated for the relevé points. The most informative when dividing the stages of reforestation on abandoned fields in the zone of distribution of broad-leaved forests in the Urals were the NDVI vegetation index and the surface temperature estimated by the thermal channel. In addition, the red band can be useful for identifying the initial stage of succession.


Author(s):  
C. Rodriguez Gonzalez ◽  
Y. Acevedo Arcia ◽  
E. Frank Buss

Abstract. Leishmaniasis encompasses a group of vector-borne parasitic diseases, characterized by their diversity and complexity, that affect both humans and other vertebrates. They are caused by different species of parasites of the Leishmania genus, which are transmitted by bites from hematophagous female sandflies. This work proposed to model the occurrence probability of five sandflies species of sanitary interest for South America, from a bibliographic compilation of records of the last 10 years. To develop the model, the free software MaxEnt was used. This exploratory analysis made it possible to visualize the areas where the species are distributed. In addition, we analyzed land changes in vegetation around a town in Jujuy province, Argentina, where a leishmaniasis outbreak occurred during the years 2017 and 2018. For this, Sentinel-2 images were used, and a change vector was calculated for the difference between two dates of the Normalized Difference Vegetation Index (NDVI). This part of the work was made using SNAP software for images pre-procesing, Python for the change vector obtention and QGIS for the result post-procesing. From the exploration of MaxEnt software we were able to know the most suitable places for the distribution of the most important five species in the study region, and therefore, to project future decision-making to prevent and control leishmaniasis transmission. And in turn, obtain an approximation of how anthropogenic activities, as deforestation, can have an influence on leishmaniasis specific outbreaks transmitted by these species. Finally, from the exploration of the different tools used in this work, the importance of validation with field data for the generation of accurate analyses and predictions is highlighted. It implies that more data collection is necessary to validate the models and analyzes generated, to guarantee the contribution of the tools in macro-ecological studies of species linked to disease transmission.


2018 ◽  
Vol 10 (12) ◽  
pp. 1979 ◽  
Author(s):  
Katarzyna Dabrowska-Zielinska ◽  
Jan Musial ◽  
Alicja Malinska ◽  
Maria Budzynska ◽  
Radoslaw Gurdak ◽  
...  

The objective of the study was to estimate soil moisture (SM) from Sentinel-1 (S-1) satellite images acquired over wetlands. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in north-eastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to SM retrieval for a broad range of vegetation and soil moisture conditions. The methodology is based on research into the effect of vegetation on backscatter (σ°) changes under different soil moisture and Normalized Difference Vegetation Index (NDVI) values. The NDVI was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. It was found that the state of the vegetation expressed by NDVI can be described by the indices such as the difference between σ° VH and VV, or the ratio of σ° VV/VH, as calculated from the Sentinel-1 images in the logarithmic domain. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the newly developed models using Water Cloud Model (WCM) that includes the derived indices based on S-1, allowed the estimation of SM for wetlands with reasonable accuracy (10 vol. %). The developed soil moisture retrieval algorithms based on S-1 data are suited for wetland ecosystems, where soil moisture values are several times higher than in agricultural areas.


2019 ◽  
Vol 40 (21) ◽  
pp. 8146-8173 ◽  
Author(s):  
Gumma ◽  
Nelson ◽  
Yamano

Rice is a staple food crop of India and is grown on 44 Mha (2011–12), 58.6% of which are irrigated. An inevitable phenomenon which looms over all aspects of human life and affects rice production in India is drought. Assessing drought damage using geospatial datasets available in the public domain, such as the Normalized Difference Vegetation Index (NDVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), can provide specific and local ecoregion information for developing drought-resistant rice varieties. Based on multi-temporal NDVI data and field observations in 2009, we developed a methodology to identify and map drought-affected areas in India. A long-term (10-year) average of NDVI during the rainy (kharif) season (June–October) was compared with NDVI from a known drought year (2002–03) to identify changes in rice area. Rainfall data from the Tropical Rainfall Monitoring Mission (TRMM) was used to support the drought analysis. Spectral matching techniques were used to categorise the drought-affected rice areas into three classes – severe, moderate, and mild based on the intensity of damage assessed through field sampling. Based on these ground survey samples, spectral signatures were generated. It was found that the rice area was about 16% less in the drought year (2002–03) than in a normal year (2000–01). A comparison of the MODIS-derived rice area affected by drought in 2002 for each state and district against the difference in the kharif season harvested rice area between 2000 and 2002 (from official statistics) revealed a substantial difference in harvested area in 2002 that was largely attributable to drought. An 84.7% correlation was found between the MODIS-derived drought-affected area in 2002 and the reduction in harvested area from 2000–01 to 2002–03. Good spatial correlation was found between the drought-affected rice areas and reduction of rice harvested areas in different rice ecologies, indicating the usefulness of such geospatial datasets in assessing abiotic stress such as drought and its consequences.


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