Integrating intraseasonal grassland dynamics in cross-scale distribution modeling to support waterbird recovery plans.

Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. We developed a modeling approach for the integration of local, spatially measured ecosystem functional dynamics into a species distribution modeling (SDM) framework in which other ecologically relevant factors are modeled separately at broad scales. To illustrate the approach, we incorporated intraseasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago), which is highly dependent on water and vegetation dynamics. The Common Snipe is an Iberian grassland waterbird characteristic of European agricultural meadows and a member of one of the most threatened bird guilds. The intraseasonal dynamics of water content of vegetation were measured using the standard deviation of the normalized difference water index time series computed from bimonthly images of the Sentinel-2 satellite. The recovery plan for the Common Snipe in Galicia (northwestern Iberian Peninsula) provided an opportunity to apply our modeling framework. Model accuracy in predicting the species' distribution at a regional scale (resulting from integration of downscaled climate projections with regional habitat-topographic suitability models) was very high (area under the curve [AUC] of 0.981 and Boyce's index of 0.971). Local water-vegetation dynamic models, based exclusively on Sentinel-2 imagery, were good predictors (AUC of 0.849 and Boyce's index of 0.976). The predictive power improved (AUC of 0.92 and Boyce's index of 0.98) when local model predictions were restricted to areas identified by the continental and regional models as priorities for conservation. Our models also performed well (AUC of 0.90 and Boyce's index of 0.93) when projected to updated water-vegetation conditions. Our modeling framework enabled incorporation of key ecosystem processes closely related to water and carbon cycles while accounting for other factors ecologically relevant to endangered grassland waterbirds across different scales, allowed identification of priority areas for conservation, and provided an opportunity for cost-effective recovery planning by monitoring management effectiveness from space.

Integración de las Dinámicas Intraestacionales de los Pastizales al Modelado de la Distribución a través de Diversas Escalas para Respaldar los Planes de Recuperación de Aves Acuáticas Resumen A pesar A pesar del potencial de la teledetección para la conservación, la inclusión de estas tecnologías en los planes de recuperación de especies es muy poco habitual. En este trabajo, desarrollamos una estrategia de modelado para la integración de dinámicas ecosistémicas funcionales locales medidas espacialmente dentro de un marco de trabajo del modelado de distribución de especies (MDE), en el cual otros factores ecológicamente relevantes se modelan por separado y a escalas más generales. Para ilustrar la estrategia incorporamos las dinámicas Intraestacionales de la vegetación acuática en un MDE multiescala escalas para la agachadiza común (Gallinago gallinago), la cual es sumamente dependiente de las dinámicas del agua y la vegetación. La agachadiza común es un ave acuática de los pastizales ibéricos, característica de las praderas agrícolas de Europa y miembro de uno de los grupos de aves más amenazados. Medimos las dinámicas intraestacionales del contenido de agua de la vegetación con la desviación estándar de la serie temporal del índice de diferencia normalizada de agua a partir de las imágenes bimensuales del satélite Sentinel-2. El plan de recuperación para la agachadiza común en Galicia (noroeste de la península ibérica) proporcionó una oportunidad para aplicar nuestro marco de trabajo. La capacidad del modelo para predecir la distribución de la especie a una escala regional (resultante de la integración de proyecciones climáticas a escala reducida con modelos regionales de idoneidad hábitat-topografía) fue muy alta (área bajo la curva [AUC] de 0.981 e índice de Boyce de 0.971). El poder de predicción aumentó (AUC de 0.92 e índice de Boyce de 0.98) cuando las predicciones de los modelos locales estuvieron restringidos a áreas identificadas por los modelos continentales y regionales como prioritarias para la conservación. Nuestros modelos también tuvieron un buen desempeño (AUC de 0.90 e índice de Boyce de 0.93) cuando los proyectamos hacia las condiciones actualizadas de vegetación acuática. Nuestro marco de trabajo permitió la incorporación de procesos ecosistémicos clave intimamente relacionados con los ciclos del agua y del carbono a la vez que representaba otros factores ecológicamente relevantes para las aves acuáticas amenazadas de pastizal, a través de diferentes escalas. También permitió la identificación de áreas prioritarias para la conservación y proporcionó oportunidades para la planificación rentable de la recuperación al monitorear la efectividad del manejo desde el espacio.

Assessment of Landsat-8 and Sentinel-2 Water Indices: A Case Study in the Southwest of the Buenos Aires Province (Argentina).

The accuracy assessment of three different Normalized Difference Water indices (NDWIs) was performed in La Salada, a typical lake in the Pampean region. Data were gathered during April 2019, a period in which floods occurred in a large area in the Southwest of the Buenos Aires Province (Argentina). The accuracy of the estimations using spaceborne medium-resolution multi-spectral imaging and the reliability of three NDWIs to highlight shallow water features in satellite images were evaluated using a high-resolution airbone imagery as ground truth. We show that these indices computed using Landsat-8 and Sentinel-2 imagery are only loosely correlated to the actual flooded area in shallow waters. Indeed, NDWI values vary significantly depending on the satellite mission used and the type of index computed.

Ecological environment monitoring for sustainable development goals in Gomishan international wetland, Gorgan Bay, Caspian Sea.

Monitoring of coastal ecosystems is of particular importance for sustainable development and environmental management. Remote sensing, using satellite imagery, can play an important role in these studies. In this study, changes of qualitative parameters in Gomishan wetland and Gorgan Bay located in the southeast of the Caspian Sea were investigated using Landsat images. Based on the results of the range of chlorophyll-a and water temperature changes in both ecosystems, there was an increasing trend. Evaluating of Secchi disk (transparency) ranges showed a decreasing trend until 2018. Also, among the studied years, 2009 has the lowest fluctuations. Overall, the findings of this study showed that changes in water quality parameters of Gorgan Bay and Gomishan wetland had been affected by ecological conditions and human activities such as industrial-domestic and agricultural effluents. Also, satellite data in such coastal ecosystems at different time intervals have valuable results and can be given special attention for the study of similar ecosystems.

Assessment of land use/land cover changes and its effect on land surface temperature using remote sensing techniques in Southern Punjab, Pakistan.

Land surface temperature (LST) is defined as a phenomenon which shows that microclimate of an urban system gets heated much faster than its surrounding rural climates. The expansion of buildings has a noteworthy influence on land use/land cover (LULC) due to conversion of vegetation land into commercial and residential areas and their associated infrastructure by which LST is accelerated. The objective of the research was to study the impact of changes in LULC on LST of Southern Punjab (Pakistan) through remote sensing (RS) data. Landsat images of 30-year duration (1987, 1997, 2007 and 2017) were employed for identifying vegetation indices and LST in the study region. These images also helped to work out normalized difference water index (NDWI) and normalized difference built-up index (NDBI) maps. There was an increase from 29620 (3.63 %) to 88038 ha (10.8 %) in built-up area over the 30 years. LST values were found in the range 12-42 °C, 11-44 °C, 11-45 °C and 11-47 °C in the years 1987, 1997, 2007 and 2017, respectively. Regression coefficients (R2) 0.81, 0.78, 0.84 and 0.76 were observed between NDVI and LST in the corresponding years respectively. Our study showed that NDVI and NDWI were negatively correlated with less LST; however, NDBI showed positive correlation with high LST. Our study gives critical information of LULC and LST and will be a helpful tool for policy makers for developing effective policies in managing land resources.

Wetland health assessment using DPSI framework: a case study in Kolkata Metropolitan Area.

Wetlands are among the most valuable components of the ecosystem, playing an important role in preventing floods, maintaining the hydrological cycle, protecting against natural hazards, and controlling local weather conditions and ecological restoration. The Kolkata Metropolitan Area (KMA) is considered one of the most ecologically valuable regions in terms of wetland ecosystem, but due to haphazard development and human activities, the wetlands of the city are under constant threat of degradation. Therefore, this study aims to assess the factors responsible for wetland health and their dynamics using Driving Force-Pressure-State-Impact (DPSI) framework. To assess wetland health during 2011-2020, seventeen indicators and four sub-indicators were selected to calculate weights using the analytic hierarchy process (AHP). The results showed that most of the municipalities in the healthy category were in the pressure (P) section in 2011, while fluctuations were observed in the impact (I) section in several wards during 2011-20. The condition section (S) showed the overall change in the water, vegetation, and built-up categories from 2011 to 2020, so the most dominant category was "healthy," followed by "unhealthy" and "poor." The highly significant factors worsening wetland health were population density (B1), road density (B3), per capita wastewater generation (B5), per capita solid waste generation (B7), biological oxygen demand (D1a), dissolved oxygen (D1b), pH (D1c), and total coliform (D1d). The results of the study can help develop sustainable conservation and management of the wetland ecosystem in the KMA urban area and at the global level with similar geographical conditions.

Wetland characteristics affect abundance and diversity of wintering birds: A case study in South-Western Iran.

Water availability is an important driver of bird population change, and its effects are likely to increase in coming decades under climate change. Here we assess effects of temperature, precipitation, and water area on wintering bird populations in Miyangaran Wetland in southwestern Iran. Modeling methods including, generalized linear model (GLM) and hierarchical partitioning were used to examine the relative importance of variables. The number of wintering species, inhabiting the wetland, varied among years, ranging from 10 to 48 species. The total number of wintering birds showed a significant decreasing trend. A significant increasing trend was obtained for shorebirds, while waterfowl species were significantly decreased. The GLM showed that species abundance, richness, and diversity were significantly correlated with the standardized precipitation index (SPI), annual precipitation, and normalized difference water index (NDWI). Hierarchical partitioning analysis also identified NDWI, SPI, and annual precipitation as the most important variables with average independent effects of 35, 36 (p < .01) and 17% (p < .05), respectively. Our results revealed that the water area plays a major role in determining the structure of bird diversity and abundance, affecting both waterfowl and shorebirds.

Effect of Urbanization on the River Network Structure in Zhengzhou City, China.

Hydrological problems, such as flood disasters, can be caused by the influence of urbanization on river network structures in plain areas. Taking the main urban region of Zhengzhou city as the research area, based on six remote sensing images from 1992 to 2015, the modified normalized difference water index method and a land-use transfer matrix were used to reconstruct river network data to study the temporal and spatial changes in the river system. In addition, the analytic hierarchy process and the entropy weight method were used to construct pattern indexes of the river system to quantitatively evaluate the inner relationship between the urbanization process and the river network structure in the plain area. The results showed that the percentages of arable land, forest and grassland, water, and unused land in Zhengzhou that was transferred to construction land from 1992 to 2015 were 59.10%, 51.05%, 29.83%, and 58.76%, respectively. In the past 34 years, the morphological indices, structural indices, and connectivity indices of the river system experienced a trend of high to low, and then increased, with the structural indices being significantly correlated with construction land use (p < 0.05). The regression equation R2 between urbanization level and river length, water area, river network density, water surface rate, connection rate, and connectivity ranged from 0.677 to 0.966, which could well reflect the response relationship between urbanization and the river network. In addition, the outflow was greater than the inflow, which has destroyed the natural structure of the channel.

Monitoring migratory birds of India's largest shallow saline Ramsar site (Sambhar Lake) using geospatial data for wetland restoration.

Globally, saline lakes occupy about 23% by area, and 44% by volume. Importantly, these lakes might desiccate by 2025 due to agricultural diversion, illegal encroachment, or modify due to pollution, and invasive species. India's largest saline lake, Sambhar is currently shrinking at a phenomenal rate of 4.23% every decade due to illegal saltpan encroachments. This study aims to identify the trend of migratory birds and monthly wetland status. Birds' survey was conducted for 2019, 2020 and 2021, and combined it with literature data of 1994, 2003, and 2013, for understanding their visiting trends, feeding habits, migratory and resident birds ratio, along with ecological diversity index analysis. Normalized Difference Water Index (NDWI) was scripted in Google Earth Engine. Results state that lake has been suitable for 97 species. Highest NDWI values was 0.71 in 2021 and lowest 0.008 in 2019. Notably, the decreasing trend of migratory birds coupled with decreasing water level indicates the dubious status for its existence. If these causal factors are not checked, it might completely desiccate. Authors recommend a few steps that might help conservation. Least, the cost of restoration might exceed the revenue generation. Supplementary Information: The online version contains supplementary material available at 10.1007/s11273-022-09875-3.

Competing Vegetation Structure Indices for Estimating Spatial Constrains in Carabid Abundance Patterns in Chinese Grasslands Reveal Complex Scale and Habitat Patterns.

Carabid communities are influenced by landscape features. Chinese steppes are subject to increasing desertification processes that are changing land-cover characteristics with negative impacts on insect communities. Despite those warnings, how land-cover characteristics influence carabid communities in steppe ecosystems remains unknown. The aim of this study is to investigate how landscape characteristics drive carabid abundance in different steppes (desert, typical, and meadow steppes) at different spatial scales. Carabid abundances were estimated using pitfall traps. Various landscape indices were derived from Landsat 8 Operational Land Imager (OLI) images. Indices expressing moisture and productivity were, in general, those with the highest correlations. Different indices capture landscape aspects that influence carabid abundance at different scales, in which the patchiness of desert vegetation plays a major role. Carabid abundance correlations with landscape characteristics rely on the type of grassland, on the vegetation index, and on the scale considered. Proper scales and indices are steppe type-specific, highlighting the need of considering various scales and indices to explain species abundances from remotely sensed data.

Examining spatiotemporal salinity dynamics in the Mekong River Delta using Landsat time series imagery and a spatial regression approach.

Most coastal areas globally face water shortages in the dry season due to salinization and drought. The Mekong River Delta (MRD) is recognized as the "Rice Bowl" in Vietnam but the negative effects of salinization and drought have damaged rice production in recent decades. However, regional assessment of the perturbation has been lacking. A Landsat-based satellite salinity index, the Enhanced Salinity Index (ESI), was developed in this study to explore patterns of annual salinity variations in agricultural land and their relationship to drought in the MRD from 1989 to 2018. The performance of the index was superior to that of other previously published remotely sensed indices, based on correlations with field measurements of electrical conductivity (i.e. groundwater and soil EC), which can be used as a proxy for salinity. The time-series ESI was then utilized to explore the spatiotemporal dynamics of salinity in the study area using the Theil-Send median trend (TS) and Mann-Kendall significance tests (MK). In addition, temporal relationships with the Normalized Difference Water Index (NDWI) were used to investigate the relationship between drought and saline intrusion. Our results showed that freshwater and brackish areas increased inland, whereas those developed for shrimp farming may increase soil and groundwater salinity. A negative correlation between drought and salinity was also observed in surface water where fish and shrimp farming activities took place, while a positive relationship was discovered in rice and annual cropland areas. This study highlights the use of ESI as an effective parameter for modelling vegetation salinity and its relationship with cropland change. We also demonstrate the feasibility of integrating satellite imagery with spatiotemporal analyses to monitor and assess regional salinization dynamics.

Understanding the relationship between urban blue infrastructure and land surface temperature.

Urban heat island (UHI) effect has serious negative impacts on urban ecosystems and human well-being. Mitigation of UHI using nature-based solutions is highly desirable. It was well known that urban green infrastructure (UGI), i.e., urban vegetation, can effectively mitigate UHI effect. However, the potential of urban blue infrastructure (UBI), i.e., urban surface water, on UHI mitigation is not well understood, although its potential to lower UHI effect via evaporation is similar to the biophysical mechanism of evapotranspiration through vegetation. In this paper, we study the relationship between UBI and land surface temperature (LST) in Wuhan city in central China, using a normalized difference water index (NDWI), maximum local cool island intensity and the maximum cooling distance as indicators for the cooling effects of UBI, respectively. We found a significant negative linear relationship between mean LST and NDWI after NDWI passes a critical threshold value. NDWI is an effective biophysical parameter to delineate the spatial distribution of UBI. The cooling effects of UBI are influenced both by its size and shape. Water surface temperature decreased logarithmically with increasing UBI size, critical threshold values of UBI size corresponding to maximum cooling efficiency do exists. Maximum cooling distance and maximum local cool island intensity are also affected by the shape and size of UBI, and exhibit seasonal and spatial variations. These results provide insights for urban landscape planning regarding how to use UBI as a nature-based solution to improve urban thermal environment.

Change detection for Lake Burullus, Egypt using remote sensing and GIS approaches.

Lake Burullus is the second largest natural coastal lake in Egypt. It has an economic importance for fish yield. However, several anthropogenic activities such as industrial, agriculture, and reclamation activities lead to a deterioration of its water quality and a decrease of the water body area of the lake. This study aims to detect the spatiotemporal changes of Lake Burullus in the period 1972-2015 using 12 Landsat {(1,3-MSS), (4,5-TM), and (7-ETM+)} imageries and water indices approach. To extract water feature from imageries, the Normalized Difference Water Index (NDWI) and the Water Ratio Index (WRI) were applied. The NDWI was applied to the MSS imageries. For other TM and ETM+ imageries, the WRI was applied. Obtained results show a significant decrease in the water area of the Lake Burullus, where it lost about (49%) of its surface area during the period from the year 1972 to the year 2015. A rapid decrease in the lake surface area was noticed through the period from 1972 to 1984. A prediction model was built depending on the calculated water area of the lake. Finally, the multi-temporal maps of the lake surface area are overlaid to produce a map for the changes of the lake surface area using Geographic Information System (GIS).