A graphical assessment and spatial clustering of the Deepwater Horizon oil spill impact on Laughing Gulls

The Deepwater Horizon oil spill occurred in the Gulf of Mexico on April 20, 2010. Considered the largest accidental marine oil spill in history, oil flowed for three months and approximately five million barrels of oil spilled through by mid-July 2010. In this article, we analyze bird data to assess the impact of the oil spill on the Gulf wildlife. Particularly, we want to determine in which regions Laughing Gulls were mostly affected by the oil spill, and whether those regions spatially shifted throughout the year 2010. Though our data sets have some limitations to apply statistical analysis methods, we obtained very interesting results. Our analyses showed the general consistency of the results based on two population data sets (from the 2011 Data Expo and from the eBird community) and justified the use of both publicly available data sets. We showed that the closer the surface oil spill area approached to the Laughing Gulls habitats, the more significant clusters of bird cases were observed.     

Investigating the link between $$\hbox {PM}_{2.5}$$ and atmospheric profile variables via penalized functional quantile regression

Fine particulate matter (\(\hbox {PM}_{2.5}\)) events negatively affect the health of numerous persons globally each year. Previous works have described the association between air pollution and surface-level meteorological conditions; however, there has been less focus on the task of linking air pollution events with meteorological conditions at higher levels of the atmosphere. Working within the functional data framework, we develop a penalized functional quantile regression (PFQR) procedure to model conditional quantiles of a continuous response based on a functional covariate, with the ability to penalize selected derivatives of the estimated coefficient function. Our aim is to investigate the relationship between atmospheric profile variables (APVs), assumed to be functional, and key quantiles of the conditional distribution of surface-level \(\hbox {PM}_{2.5}\). Via a simulation study, we find that the performance of our PFQR procedure compares favorably to other related approaches. We conclude with an analysis of \(\hbox {PM}_{2.5}\) data at two Southeastern US locations, Columbia, SC and Tampa, FL, where we estimate the coefficient functions for the APVs corresponding to both ‘typical’ and ‘high’ \(\hbox {PM}_{2.5}\) events. As we believe that the true coefficient functions are smooth and may be exactly zero over subsets of their domains, we impose penalties on the 0th and 2nd derivatives. Our analysis indicates that the corresponding atmospheric conditions differ between the two locations, and that the conditions differ seasonally within location.     

Comparing canopy leaf temperature of three Central European tree species based on simultaneous confidence bands for penalized splines

Temperature is an important physical factor that is known to strongly affect biodiversity as well as ecosystems and their functioning. However, research in this area is still relatively limited; this may also be attributed to the multitude of influencing factors and the complexity of the statistics involved. This study analyzes the differences between the surface temperature of three Central European broadleaf tree species. A better understanding of these differences may help to elucidate the role of microclimate in biodiversity. We consider a time series of high-resolution thermal images taken from a meteorological observation tower and calculate mean canopy leaf temperatures for beech, ash and maple (Fagus silvatica, Fraxinus excelsior and Acer pseudoplatanus). In a first step, comparable image areas are extracted from the thermal image sections of the crown of each tree species avoiding shadow areas, branches, etc. We used an automatic segmentation technique, the Otsu thresholding. Extracted canopy leaf temperature values were then processed and the resulting temperature profiles estimated by O’Sullivan penalized splines. For comparing the differences in canopy leaf temperature over time, we propose the construction of simultaneous confidence bands. The analyses show that there are significant—though small—differences in canopy surface temperature between the three tree species.     

Estimation bias under model selection for distance sampling detection functions

Many simulation studies have examined the properties of distance sampling estimators of wildlife population size. When assumptions hold, if distances are generated from a detection model and fitted using the same model, they are known to perform well. However, in practice, the true model is unknown. Therefore, standard practice includes model selection, typically using model comparison tools like Akaike Information Criterion. Here we examine the performance of standard distance sampling estimators under model selection. We compare line and point transect estimators with distances simulated from two detection functions, hazard-rate and exponential power series (EPS), over a range of sample sizes. To mimic the real-world context where the true model may not be part of the candidate set, EPS models were not included as candidates, except for the half-normal parameterization. We found median bias depended on sample size (being asymptotically unbiased) and on the form of the true detection function: negative bias (up to 15% for line transects and 30% for point transects) when the shoulder of maximum detectability was narrow, and positive bias (up to 10% for line transects and 15% for point transects) when it was wide. Generating unbiased simulations requires careful choice of detection function or very large datasets. Practitioners should collect data that result in detection functions with a shoulder similar to a half-normal and use the monotonicity constraint. Narrow-shouldered detection functions can be avoided through good field procedures and those with wide shoulder are unlikely to occur, due to heterogeneity in detectability.     

Observations and analytical modeling of freshwater and rainwater lenses in coastal dune systems

Observations are reported on (i) groundwater recharge rates under various types of vegetation as measured with megalysimeters in the dunes, (ii) freshwater lenses along the Dutch North Sea coast in the early 1900s, and (iii) rainwater lenses that develop on top of laterally migrating, artificially recharged riverwater. Subsequently analytical methods are presented to estimate annual natural groundwater recharge as function of rainfall and vegetation, and to calculate the size, shape and transition zone of freshwater lenses on saline groundwater and rainwater lenses on infiltrated riverwater. An empirical correction factor, based on the hydraulic resistance of an aquitard within the freshwater lens, is proposed to account for the frequently observed reduction of the Ghyben-Herzberg ratio of 40. This factor raises the groundwater table, reduces the depth of the fresh/salt interface and increases the lens formation time. The suite of methods offers a tool box for knowledge based water management of dune systems, by rapidly predicting: (i) more or less autonomous changes due to sealevel rise, climate change and vegetation development; and (ii) the potential (side) effects of interventions. Knowing what happened or will happen to the fresh water lens or a rainwater lens is important, because changes impact on important natural habitat parameters such as salinity, depth to groundwater table, decalcification rate (and thus on pH, Ca/Al, PO₄, NH₄) and nutrient availability, and on drinking water supply. The analytical models are applied to predict effects of sealevel rise, coastal progradation, vegetation changes, and increased temperature of coastal air and river water to be infiltrated.     

Climate change impacts on a large-scale erosion coast of Hai Hau district,Vietnam and the adaptation

Among the effects of global warming, sea level rise (SLR) and severe typhoons pose the greatest threat to the stability of human settlements along coastlines. Therefore, countermeasures must be developed to mitigate the influences of strong typhoons and persistent SLR for coastal protection. This study assesses climate change impacts on coastal erosion, especially in two projected SLR scenarios of RCP2.6 and RCP8.5. The results show that SLR and severe typhoons lead to the increase of coastal erosion, beach lowering and scour. Moreover, as in projected SLR scenarios, average waves in high tide can cause severe soil erosion at inner slopes and lead to dyke failure by 2060. The paper highlights the need for additional countermeasures to protect the coast of Hai Hau district against SLR and severe typhoons. Among the alternatives available for countering these threats, applying soil stabilization and soil improvement combined with geosynthetics are promising strategies for coastal structures. Hybrid structures can be used with earth reinforcement and soil improvement. Additionally, the paper emphasizes the importance of multiple protective adaptations, including geosynthetics and ecological engineering measures against climate change-induced severe erosion on the coast of Hai Hau district.     

Are anthropogenic factors affecting nesting habitat of sea turtles? The case of Kanzul beach,Riviera Maya-Tulum (Mexico)

Marine coast modification and human pressure affects many species, including sea turtles. In order to study nine anthropogenic impacts that might affect nesting selection of females, incubation and hatching survival of loggerhead (Caretta caretta) and green turtle (Chelonia mydas), building structures were identified along a 5.2 km beach in Kanzul (Mexico). A high number of hotels and houses (88; 818 rooms), with an average density of 16.6 buildings per kilometer were found. These buildings form a barrier which prevents reaching the beach from inland, resulting in habitat fragmentation. Main pressures were detected during nesting selection (14.19% of turtle nesting attempts interrupted), and low impact were found during incubation (0.77%) and hatching (4.7%). There were three impacts defined as high: beach furniture that blocks out the movement of hatchlings or females, direct pressure by tourists, and artificial beachfront lighting that can potentially mislead hatchlings or females. High impacted areas showed lowest values in nesting selection and hatching success. Based on our results, we suggest management strategies to need to be implemented to reduce human pressure and to avoid nesting habitat loss of loggerhead and green turtle in Kanzul, Mexico.     

Restoration and sequestration of carbon and nitrogen in the degraded northern coastal area in Nile Delta,Egypt for climate change mitigation

Most of coastal area in Nile Delta, Egypt, is salt-affected soils and have low carbon (C) and nitrogen (N) inputs as a result of declining vegetation growth and low net primary production. Therefore, this study amid to compare between C and N pools in degraded (uncultivated and salt-affected soil) and restored (cultivated and reclaimed 20 years ago) locations in North Nile Delta. and to examine the impact of cultivation on sequestering C and N pools in this area as one of the most important methods for mitigating climate change impacts. C and N pools increased significantly in surface soil from 2.99 and 0.43 Mgh^?1 in uncultivated sites to 19.26 and 1.66 Mgh^?1 in cultivated ones as salinity was reduced and net primary production was increased due to leaching and reclamation. Particulate (associated with sand) and nonparticulate (associated with clay +silt) soil organic C or N was significantly higher cultivated sites. In addition, nonparticulate organic C or N was lower than particulate part indicating and supporting the strong relationship between organic matter and clay. The sequestration rate (in approximately 1 m profile) was 1.69 and 0.14 Mgh^?1 yr.^?1 C and N pools respectively. Although the cultivation is leading to loss of organic matter in some areas; C and N in this coastal area are partially restored and stored. Therefore, restoration and appropriate management practices will lead to mitigate the negative impacts of climate change in this area.     

Aboveground biomass and carbon stock are related with soil humidity in a mangrove at the Piraquê-Açu River,Southeastern Brazil

In Brazil, few studies have been conducted about the assimilation of carbon and biomass accumulation in mangroves despite its great role as a carbon sink. In this sense, this study aimed to estimate the aboveground biomass (AGB) and carbon stocked by mangrove species in a stretch along the Piraquê-Açu River in southeastern Brazil, and to verify their relation with some soil parameters. For such, the height and diameter of all trees inside six plots of 100 m² were measured and used to quantify AGB through an allometric equation, and soil samples were collected to calculate granulometry, humidity, time of infiltration and permeability. Multiple regressions were used to identify relations between AGB and soil parameters. A total of 296 trees were found in the area and the AGB and carbon assimilated were 2.92 t ha^?1 and 1.46 t ha^?1, respectively. Laguncularia racemosa was the most abundant species and contributed with 61% of these values. Only a positive relation between AGB/carbon of L. racemosa and soil humidity was found, probably due to the substrate characteristics which contain a large concentration of silt/clay, and may store more water and do not yet provide firmness to the roots. By comparison, this mangrove had a low amount of AGB and carbon stocked and has yet to develop structurally. Along with other ecological functions and its associated ecosystem services such as supplying food for the local community, these features highlight the importance to conserve the studied mangrove and the interlinked coastal ecosystems.     

Spatiotemporal changes and fragmentation of mangroves and its effects on fish diversity in Ca Mau Province (Vietnam)

Mangroves are important economically and ecologically, however mangrove cover has declined dramatically leading to habitat fragmentation and biodiversity loss. Information on mangrove cover change, fragmentation and impacts on fish diversity is poorly understood. The aims of this study are to detect spatiotemporal changes and mangrove status, examine fragmentation changes and associated effects on fish diversity. Landsat images in1989, 2000, and 2013 were used to classify mangrove cover in Ca Mau Province (Vietnam) and validated against high resolution Pleiades imagery. Fragmentation changes in mangrove cover were examined using series of landscape metrics evaluated against fish diversity indices (Simpson’s index, Jaccard’s coefficient and relative abundance). Results show that mangrove cover has declined 24.6% in the province. Currently, high and moderately dense mangroves distribute in southern half of the region while the low density mangroves occurs in the northern half. Over the 24 year study periods, the number of patches and edge density has increased 58% and 53.9%, respectively, while the mean patch size and mean patch edge has decreased 52.3% and 26.6%. Fish diversity in the more highly fragmented mangrove area was 1.78 times lower than the less fragmented mangrove. The study illustrates the applicability of using Landsat satellite imagery for use in mangrove fragmentation studies as well as the impact of fragmentation.