<b>Code and Data Metadata for Variable importance graphs using simulated variables</b>... more <b>Code and Data Metadata for Variable importance graphs using simulated variables</b> This data entry contains the code and data generated for creating the variable importance graphs as published in the article: <i>Harisena, N. V., Groen, T. A., Toxopeus, A. G., &amp; Naimi, B. (2021). When is variable importance estimation in species distribution modelling affected by spatial correlation? Ecography, 44(5), 778–788. 10.1111/ecog.05534</i> Contents 1. A Readme.docx file 2. Main_script.R file; Includes the code to be run and the instructions for running the same 3. Functions.R file; Includes all the functions to be loaded in R before running the Main_script.R file 4. Generated_Data; folder with all .Rdata files for each code step as detailed in Main_script.R along with the output .csv and .jpg files that can be matched with the output images in the publication.A CODECHECK certificate is available confirming that the computations underlying this article could be independently executed: https://doi.org/10.5281/zenodo.5574909<br><br>
Analogous to Fig. 1 but without exclusion of species with > 2000 records in Britain. Exclusion... more Analogous to Fig. 1 but without exclusion of species with > 2000 records in Britain. Exclusion of ubiquitous species did not change the overall trends detected in Fig. 1, despite changes in p and R2 values. (TIFF 76585 kb)
Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected ... more Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected by remote sensing. This paper aims at the detection of mineral alteration induced by gas seeps in a marly limestone formation, SW Iran. For this purpose, the multispectral Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the high spatial resolution WorldView-2 (WV-2) data were utilized for mapping surficial rock alteration. In addition, the potential of Visible Near Infrared (VNIR) bands of the WV-2 and its high spatial resolution for mapping alterations was determined. Band ratioing, principal component analysis (PCA), data fusion and the boosted regression trees (BRT) were applied to enhance and classify the altered and unaltered marly limestone formation. The alteration zones were identified and mapped by remote sensing analyses. Integrating the WV-2 into the ASTER data improved the spatial accuracy of the BRT classifications. The results showed that the BRT classification of the multiple band imagery (created from ASTER and WV-2) using regions of interest (ROIs) around field data provides the best discrimination between altered and unaltered areas. It is suggested that the WV-2 dataset can provide a potential tool along higher spectral resolution data for mapping alteration minerals related to hydrocarbon seeps in arid and semi-arid areas.
Proceedings of the National Academy of Sciences, 2021
Significance We combine tracks of a long-distance migratory bird with high–temporal resolution cl... more Significance We combine tracks of a long-distance migratory bird with high–temporal resolution climate data to reconstruct habitat availability month by month for the past 120,000 y. The seasonal changes of suitable habitat in the past imply that continued seasonal migration was necessary during the glacial maxima. Genomic-based estimates of effective population size indicate that more generally migratory lifestyles can be beneficially adapted to various climatic conditions. Our results provide a major step forward in understanding how migratory species will fare in the future and have important implications for how we understand the role of migration in the distribution of species and potentially speciation.
While the scientific community has focused on documenting environmental degradation and developin... more While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to...
There are several local indicators of spatial association (LISA) that allow exploration of local ... more There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in categorical data. To our knowledge, there is no indicator of local spatial association that can be used for both continuous and categorical data. We introduce ELSA, which can be used for exploring and testing local spatial association for continuous and categorical variables. We provide the R-package elsa for making these computations.
The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwest... more The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwestern Europe (Portugal, Spain, France, and the extreme northwest of Italy). Over the last decades, a marked decline in its population has been observed, particularly on the northern edge of its distribution. As a result, it is currently considered a threatened species, especially in France and Italy. In France, a national action plan for its conservation has been put in place. In this study, ecological niche modelling (ENM) was carried out over the entire area of France in order to evaluate the species' potential distribution, more accurately define its ecological niche, guide future surveys, and inform land use planning so this species can be better taken into consideration. The modelling used data representing 2,757 observation points spread over the known range of the species, and 34 ecogeographical variables (climate, topography, and vegetation cover) were evaluated. After removing correlated variables, models were fitted with several combinations of variables using eight species distribution model (SDM) algorithms, and then their performance was assessed using three model accuracy metrics. Iterative trials changing the input variables were used to obtain the best model. The optimized model included nine determining variables. The results indicate the presence of this species is linked primarily to three climate variables: precipitation in the driest month, precipitation seasonality, and mean temperature in the driest quarter. The model was checked by a sample dataset that was not used to fit the model, and this validation dataset represented 25% of the overall field observations. Of the known occurrence locations kept aside to check the results, 94% fell within the presence area predicted by the modelled map with a presence probability greater than 0.7, and 90% fell within the area with a presence probability ranging from 0.8 to 1, which represents a very high predictive value. These results indicate that the models closely matched the observed distribution, suggesting a low impact of either geographical factors (barriers to dispersal), historical factors (dispersal process), or ecological factors (e.g., competition, trophic resources). The overlap between the predicted distribution and protected areas for this species reveals that less than 1% of the potential distribution area is protected by strong regulatory measures (e.g., national parks and natural reserves). The knowledge obtained in this study allows us to recommend some guidelines that would favor the conservation of this species. Résumé.-Le lézard ocellé, Timon lepidus (Daudin 1802), occupe les régions méditerranéennes du sud-ouest de l'Europe (Portugal, Espagne, France, et extrême nord-ouest de l'Italie). Au cours des dernières décennies, un fort déclin des populations a été observé, particulièrement aux marges nord de sa distribution. Il est donc considéré comme une espèce menacée, spécialement en France et en Italie. En France, il bénéficie d'un plan national d'actions en faveur de sa préservation. La modélisation de sa distribution a été conduite sur l'ensemble du territoire national en vue d'estimer sa distribution potentielle, préciser sa niche écologique, orienter les prospections futures et permettre une meilleure prise en compte de l'espèce dans l'aménagement du territoire. Le travail de modélisation repose sur 2757 points d'observation répartis sur l'ensemble de la distribution connue de l'espèce, confrontés à 34 variables climatiques, topographiques, et de couvert végétal. Après suppression des variables autocorrélées, plusieurs combinaisons de variables ont été testées, et leur performances évaluées à partir de huit algorithmes SDM. Le meilleur modèle retient neuf variables, déterminées par l'algorithme ayant la meilleure performance. Les modèles montrent que la présence de l'espèce est Official journal website: amphibian-reptile-conservation.org
In recent decades, huge efforts have been put to make multiple-sources of spatial and temporal da... more In recent decades, huge efforts have been put to make multiple-sources of spatial and temporal data available through data repositories, followed by explosive progress in technological developments of data providers, crowdsourcing, drones, sensor networks, etc. that can be expected to continue for the next decades. Examples are global initiatives such as the movebank data repository containing animal movement data at large spatial scales over long time periods, as well as the ICARUS satellite-based animal tracking technology (Wikelski et al., 2007). The question is that whether and to what extent analytical methods are developed/adopted to deal with such progress in data? This research aims to introduce moveStore, a platform that is designed on a cloud to support and boost the progresses in methods/workflows/applications developments, followed the progresses in data developments. Analogous to a data repository, moveStore provides a specific repository for methodological developments...
International Journal of Environmental Research, 2013
Remotely sensed imagery is proving to be a useful tool to estimate water depths in coastal zones.... more Remotely sensed imagery is proving to be a useful tool to estimate water depths in coastal zones. Bathymetric algorithms attempt to isolate water attenuation and hence depth from other factors by using different combinations of spectral bands. In this research, images of absolute bathymetry using two different but related methods in a region in the southern Caspian Sea coasts has been produced. The first method used a Single Band Algorithm (SBA) and assumed a constant water attenuation coefficient throughout the blue band. The second method used Principal Components Analysis (PCA) to adjust for varying water attenuation coefficients without additional ground truth data. PCA method (r=-0.672394) appears to match our control points slightly better than single band algorithm (r=-0.645404). It is clear that both methods can be used as rough estimates of bathymetry for many coastal zone studies in the southern Caspian Sea such as near shore fisheries, coastal erosion, water quality, recr...
Due to existing of oil pollution in Persian Gulf, Iranian mangrove forests have been exposed to a... more Due to existing of oil pollution in Persian Gulf, Iranian mangrove forests have been exposed to a serious risk. This study used geostatistical approach and aimed to assess the risk by exploring the concentration and spatial distribution of two of the most toxic pollutants, lead and cadmium, in surface sediments of mangrove forests. 42 sediment samples were collected and results showed that the average concentrations of recruited metals are 1.89±0.07 μg/g dw and 0.17±0.01 μg/g dw, respectively. Spatial distribution pattern of both metals were followed from spatial variable, because the variance of sampling stations in terms of toxic metals concentrations was increased with increasing the distance. Depicted maps showed that the highest concentration of both metals has often focused in Khamir Port and eastern side of Middle part. Generated information by pollution risk maps can provide a useful tool for managers about pollution status of mangrove ecosystems.
Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global w... more Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global warming and is projected to continue to rise over the twenty-first century and beyond. The importance of coastal areas for both human and natural systems has led researchers to conduct extensive studies on coastal vulnerability to SLR impacts and develop adaptation options to cope with rising sea level. Investigations to date have focused mostly on developed and highly populated coasts, as well as diverse ecosystems including tidal salt marshes and mangroves. As a result, there is less information on vulnerability and adaptation of less-developed and developing coasts to sea-level rise and its associated impacts. Hence, this research aimed at outlining an appropriate coastal management framework to adapt to SLR on the coasts that are in the early stage of development. A coastal area with a low level of development, located in southern Iran along the Gulf of Oman, was selected as a case st...
Despite improvements, studies assessing climate change effects on species range shifts fall short... more Despite improvements, studies assessing climate change effects on species range shifts fall short on aspects of data and methods.
Changes in distribution and abundance of species affect the entirety of biodiversity and monitori... more Changes in distribution and abundance of species affect the entirety of biodiversity and monitoring these changes is critical for the efficient conservation of integrity and functions of species population. However, acquiring accurate information on biodiversity over large spatial scales poses a challenge since such data is patchy and incomplete, if not unavailable, in many areas. This study aims at examining the applicability of a novel approach based on Species Distribution Models (SDMs) to develop spatial predictions of Essential Biodiversity variables (EBVs; variables to be quantified at certain points in time and space to monitor variations in biodiversity) for birds based on bird diversity metrics such as the distributions of properties of key bird habitats. A major objective of this study is to build bird SDMs which can be used to derive spatial EBVs for bird species at a regional scale. We used as predictors 16 environmental variables that are known to be ecologically meaningful for birds, including two bioclimatic variables (Bio17 = precipitation of driest quarter and Bio7 = temperature annual range) for three periods of 'current', 'future 2050′, and 'future 2070′, eleven landcover (land use) predictors, the normalized difference vegetation index, and two topographic variables (slope and topography). We used multiple modeling techniques to build presenceonly SDMs relating bird presence to environmental features of each species. Here, we show that the suitability estimated according to the SDMs can be used as a spatial 'species distribution' EBV (SD EBV) and reflect the habitat quality and trends in land use and climatic impacts on populations of bird species. These developments could facilitate monitoring of bird species across space and time, ultimately helping to identify priority conservation areas, estimate habitat suitability and provide early warning signs regarding bird distribution trends. In general, bioclimatic variables, topography and forest structure were identified to have important ties to the species probability maps generated on the basis of the SDMs, signifying a dominant role of bioclimatic variable Bio17 in the development of habitat suitability patterns.
1. Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ec... more 1. Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. 2. In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. 3. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.
Mining activities and associated actions cause land-use/land-cover (LULC) changes across the worl... more Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST). In terms of the utilized data, satellite images of Landsat, and meteorological data of Sungun mine in Iran, Athabasca oil sands in Canada, Singrauli coalfield in India and Hambach mine in Germany, were used over the period of 1989-2019. In the first step, the spectral bands of Landsat images were employed to extract historical LULC changes in the study areas based on the homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was used to predict the future of LULC changes based on the historical changes. In addition, LST and vegetation cover maps were calculated using the single channel algorithm, and the normalized difference vegetation index (NDVI), respectively. In the second step, the trends of LST and NDVI variations in different LULC change types and over different time periods were investigated. Finally, a CA-Markov model was used to predict the LST and NDVI maps and the trend of their variations in future. The results indicated that the forest and green space cover was reduced from 9.95 in 1989 to 5.9 Km 2 in 2019 for Sungun mine, from 42.14 in 1999 to 33.09 Km 2 in 2019 for Athabasca oil sands, from 231.46 in 1996 to 263.95 Km 2 in 2016 for Singrauli coalfield, and from 180.38 in 1989 to 133.99 Km 2 in 2017 for Hambach mine, as a result of expansion and development of of mineral activities. Our findings about Sungun revealed that the areal coverage of forest and green space will decrease to 15% of the total study area by 2039, resulting in reduction of the mean NDVI by almost 0.06 and increase of mean standardized LST from 0.52 in 2019 to 0.61 in 2039. our results further indicate that for Athabasca oil sands (Singrauli coalfield, Hambach mine), the mean values of standardized LST and NDVI will change from 0.5 (0.44 and 0.4) and 0.38 (0.38, 0.35) in 2019 (2016, 2017) to 0.57 (0.5, 0.47) and 0.33 (0.32, 0.28), in 2039 (2036, 2035), respectively. This can be mainly attributed to the increasing mining activities in the past as well as future years. The discussion and conclusions presented in this study can be of interest to local planners, policy makers, and environmentalists in order to observe the damages brought to the environment and the society in a larger picture.
To the Editor-A longstanding debate exists on whether ecological phenomena should be modelled 'to... more To the Editor-A longstanding debate exists on whether ecological phenomena should be modelled 'top-down' (modelling patterns that arise from mechanisms) or 'bottom-up' (modelling mechanisms to generate pattern). Recently, the discussion re-emerged in the context of modelling the spread of SARS-CoV-2 1. Simply put, the point made by Carlson et al. was that top-down correlative models are inappropriate, whereas bottom-up epidemiological models are fine. Rather than opposing families of models, we argue that all have strengths and limitations and that judicious use of all available tools is the way forward.
<b>Code and Data Metadata for Variable importance graphs using simulated variables</b>... more <b>Code and Data Metadata for Variable importance graphs using simulated variables</b> This data entry contains the code and data generated for creating the variable importance graphs as published in the article: <i>Harisena, N. V., Groen, T. A., Toxopeus, A. G., &amp; Naimi, B. (2021). When is variable importance estimation in species distribution modelling affected by spatial correlation? Ecography, 44(5), 778–788. 10.1111/ecog.05534</i> Contents 1. A Readme.docx file 2. Main_script.R file; Includes the code to be run and the instructions for running the same 3. Functions.R file; Includes all the functions to be loaded in R before running the Main_script.R file 4. Generated_Data; folder with all .Rdata files for each code step as detailed in Main_script.R along with the output .csv and .jpg files that can be matched with the output images in the publication.A CODECHECK certificate is available confirming that the computations underlying this article could be independently executed: https://doi.org/10.5281/zenodo.5574909<br><br>
Analogous to Fig. 1 but without exclusion of species with > 2000 records in Britain. Exclusion... more Analogous to Fig. 1 but without exclusion of species with > 2000 records in Britain. Exclusion of ubiquitous species did not change the overall trends detected in Fig. 1, despite changes in p and R2 values. (TIFF 76585 kb)
Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected ... more Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected by remote sensing. This paper aims at the detection of mineral alteration induced by gas seeps in a marly limestone formation, SW Iran. For this purpose, the multispectral Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the high spatial resolution WorldView-2 (WV-2) data were utilized for mapping surficial rock alteration. In addition, the potential of Visible Near Infrared (VNIR) bands of the WV-2 and its high spatial resolution for mapping alterations was determined. Band ratioing, principal component analysis (PCA), data fusion and the boosted regression trees (BRT) were applied to enhance and classify the altered and unaltered marly limestone formation. The alteration zones were identified and mapped by remote sensing analyses. Integrating the WV-2 into the ASTER data improved the spatial accuracy of the BRT classifications. The results showed that the BRT classification of the multiple band imagery (created from ASTER and WV-2) using regions of interest (ROIs) around field data provides the best discrimination between altered and unaltered areas. It is suggested that the WV-2 dataset can provide a potential tool along higher spectral resolution data for mapping alteration minerals related to hydrocarbon seeps in arid and semi-arid areas.
Proceedings of the National Academy of Sciences, 2021
Significance We combine tracks of a long-distance migratory bird with high–temporal resolution cl... more Significance We combine tracks of a long-distance migratory bird with high–temporal resolution climate data to reconstruct habitat availability month by month for the past 120,000 y. The seasonal changes of suitable habitat in the past imply that continued seasonal migration was necessary during the glacial maxima. Genomic-based estimates of effective population size indicate that more generally migratory lifestyles can be beneficially adapted to various climatic conditions. Our results provide a major step forward in understanding how migratory species will fare in the future and have important implications for how we understand the role of migration in the distribution of species and potentially speciation.
While the scientific community has focused on documenting environmental degradation and developin... more While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to...
There are several local indicators of spatial association (LISA) that allow exploration of local ... more There are several local indicators of spatial association (LISA) that allow exploration of local patterns in spatial data. Despite numerous situations where categorical variables are encountered, few attempts have been devoted to the development of methods to explore the local spatial pattern in categorical data. To our knowledge, there is no indicator of local spatial association that can be used for both continuous and categorical data. We introduce ELSA, which can be used for exploring and testing local spatial association for continuous and categorical variables. We provide the R-package elsa for making these computations.
The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwest... more The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwestern Europe (Portugal, Spain, France, and the extreme northwest of Italy). Over the last decades, a marked decline in its population has been observed, particularly on the northern edge of its distribution. As a result, it is currently considered a threatened species, especially in France and Italy. In France, a national action plan for its conservation has been put in place. In this study, ecological niche modelling (ENM) was carried out over the entire area of France in order to evaluate the species' potential distribution, more accurately define its ecological niche, guide future surveys, and inform land use planning so this species can be better taken into consideration. The modelling used data representing 2,757 observation points spread over the known range of the species, and 34 ecogeographical variables (climate, topography, and vegetation cover) were evaluated. After removing correlated variables, models were fitted with several combinations of variables using eight species distribution model (SDM) algorithms, and then their performance was assessed using three model accuracy metrics. Iterative trials changing the input variables were used to obtain the best model. The optimized model included nine determining variables. The results indicate the presence of this species is linked primarily to three climate variables: precipitation in the driest month, precipitation seasonality, and mean temperature in the driest quarter. The model was checked by a sample dataset that was not used to fit the model, and this validation dataset represented 25% of the overall field observations. Of the known occurrence locations kept aside to check the results, 94% fell within the presence area predicted by the modelled map with a presence probability greater than 0.7, and 90% fell within the area with a presence probability ranging from 0.8 to 1, which represents a very high predictive value. These results indicate that the models closely matched the observed distribution, suggesting a low impact of either geographical factors (barriers to dispersal), historical factors (dispersal process), or ecological factors (e.g., competition, trophic resources). The overlap between the predicted distribution and protected areas for this species reveals that less than 1% of the potential distribution area is protected by strong regulatory measures (e.g., national parks and natural reserves). The knowledge obtained in this study allows us to recommend some guidelines that would favor the conservation of this species. Résumé.-Le lézard ocellé, Timon lepidus (Daudin 1802), occupe les régions méditerranéennes du sud-ouest de l'Europe (Portugal, Espagne, France, et extrême nord-ouest de l'Italie). Au cours des dernières décennies, un fort déclin des populations a été observé, particulièrement aux marges nord de sa distribution. Il est donc considéré comme une espèce menacée, spécialement en France et en Italie. En France, il bénéficie d'un plan national d'actions en faveur de sa préservation. La modélisation de sa distribution a été conduite sur l'ensemble du territoire national en vue d'estimer sa distribution potentielle, préciser sa niche écologique, orienter les prospections futures et permettre une meilleure prise en compte de l'espèce dans l'aménagement du territoire. Le travail de modélisation repose sur 2757 points d'observation répartis sur l'ensemble de la distribution connue de l'espèce, confrontés à 34 variables climatiques, topographiques, et de couvert végétal. Après suppression des variables autocorrélées, plusieurs combinaisons de variables ont été testées, et leur performances évaluées à partir de huit algorithmes SDM. Le meilleur modèle retient neuf variables, déterminées par l'algorithme ayant la meilleure performance. Les modèles montrent que la présence de l'espèce est Official journal website: amphibian-reptile-conservation.org
In recent decades, huge efforts have been put to make multiple-sources of spatial and temporal da... more In recent decades, huge efforts have been put to make multiple-sources of spatial and temporal data available through data repositories, followed by explosive progress in technological developments of data providers, crowdsourcing, drones, sensor networks, etc. that can be expected to continue for the next decades. Examples are global initiatives such as the movebank data repository containing animal movement data at large spatial scales over long time periods, as well as the ICARUS satellite-based animal tracking technology (Wikelski et al., 2007). The question is that whether and to what extent analytical methods are developed/adopted to deal with such progress in data? This research aims to introduce moveStore, a platform that is designed on a cloud to support and boost the progresses in methods/workflows/applications developments, followed the progresses in data developments. Analogous to a data repository, moveStore provides a specific repository for methodological developments...
International Journal of Environmental Research, 2013
Remotely sensed imagery is proving to be a useful tool to estimate water depths in coastal zones.... more Remotely sensed imagery is proving to be a useful tool to estimate water depths in coastal zones. Bathymetric algorithms attempt to isolate water attenuation and hence depth from other factors by using different combinations of spectral bands. In this research, images of absolute bathymetry using two different but related methods in a region in the southern Caspian Sea coasts has been produced. The first method used a Single Band Algorithm (SBA) and assumed a constant water attenuation coefficient throughout the blue band. The second method used Principal Components Analysis (PCA) to adjust for varying water attenuation coefficients without additional ground truth data. PCA method (r=-0.672394) appears to match our control points slightly better than single band algorithm (r=-0.645404). It is clear that both methods can be used as rough estimates of bathymetry for many coastal zone studies in the southern Caspian Sea such as near shore fisheries, coastal erosion, water quality, recr...
Due to existing of oil pollution in Persian Gulf, Iranian mangrove forests have been exposed to a... more Due to existing of oil pollution in Persian Gulf, Iranian mangrove forests have been exposed to a serious risk. This study used geostatistical approach and aimed to assess the risk by exploring the concentration and spatial distribution of two of the most toxic pollutants, lead and cadmium, in surface sediments of mangrove forests. 42 sediment samples were collected and results showed that the average concentrations of recruited metals are 1.89±0.07 μg/g dw and 0.17±0.01 μg/g dw, respectively. Spatial distribution pattern of both metals were followed from spatial variable, because the variance of sampling stations in terms of toxic metals concentrations was increased with increasing the distance. Depicted maps showed that the highest concentration of both metals has often focused in Khamir Port and eastern side of Middle part. Generated information by pollution risk maps can provide a useful tool for managers about pollution status of mangrove ecosystems.
Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global w... more Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global warming and is projected to continue to rise over the twenty-first century and beyond. The importance of coastal areas for both human and natural systems has led researchers to conduct extensive studies on coastal vulnerability to SLR impacts and develop adaptation options to cope with rising sea level. Investigations to date have focused mostly on developed and highly populated coasts, as well as diverse ecosystems including tidal salt marshes and mangroves. As a result, there is less information on vulnerability and adaptation of less-developed and developing coasts to sea-level rise and its associated impacts. Hence, this research aimed at outlining an appropriate coastal management framework to adapt to SLR on the coasts that are in the early stage of development. A coastal area with a low level of development, located in southern Iran along the Gulf of Oman, was selected as a case st...
Despite improvements, studies assessing climate change effects on species range shifts fall short... more Despite improvements, studies assessing climate change effects on species range shifts fall short on aspects of data and methods.
Changes in distribution and abundance of species affect the entirety of biodiversity and monitori... more Changes in distribution and abundance of species affect the entirety of biodiversity and monitoring these changes is critical for the efficient conservation of integrity and functions of species population. However, acquiring accurate information on biodiversity over large spatial scales poses a challenge since such data is patchy and incomplete, if not unavailable, in many areas. This study aims at examining the applicability of a novel approach based on Species Distribution Models (SDMs) to develop spatial predictions of Essential Biodiversity variables (EBVs; variables to be quantified at certain points in time and space to monitor variations in biodiversity) for birds based on bird diversity metrics such as the distributions of properties of key bird habitats. A major objective of this study is to build bird SDMs which can be used to derive spatial EBVs for bird species at a regional scale. We used as predictors 16 environmental variables that are known to be ecologically meaningful for birds, including two bioclimatic variables (Bio17 = precipitation of driest quarter and Bio7 = temperature annual range) for three periods of 'current', 'future 2050′, and 'future 2070′, eleven landcover (land use) predictors, the normalized difference vegetation index, and two topographic variables (slope and topography). We used multiple modeling techniques to build presenceonly SDMs relating bird presence to environmental features of each species. Here, we show that the suitability estimated according to the SDMs can be used as a spatial 'species distribution' EBV (SD EBV) and reflect the habitat quality and trends in land use and climatic impacts on populations of bird species. These developments could facilitate monitoring of bird species across space and time, ultimately helping to identify priority conservation areas, estimate habitat suitability and provide early warning signs regarding bird distribution trends. In general, bioclimatic variables, topography and forest structure were identified to have important ties to the species probability maps generated on the basis of the SDMs, signifying a dominant role of bioclimatic variable Bio17 in the development of habitat suitability patterns.
1. Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ec... more 1. Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. 2. In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. 3. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.
Mining activities and associated actions cause land-use/land-cover (LULC) changes across the worl... more Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST). In terms of the utilized data, satellite images of Landsat, and meteorological data of Sungun mine in Iran, Athabasca oil sands in Canada, Singrauli coalfield in India and Hambach mine in Germany, were used over the period of 1989-2019. In the first step, the spectral bands of Landsat images were employed to extract historical LULC changes in the study areas based on the homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was used to predict the future of LULC changes based on the historical changes. In addition, LST and vegetation cover maps were calculated using the single channel algorithm, and the normalized difference vegetation index (NDVI), respectively. In the second step, the trends of LST and NDVI variations in different LULC change types and over different time periods were investigated. Finally, a CA-Markov model was used to predict the LST and NDVI maps and the trend of their variations in future. The results indicated that the forest and green space cover was reduced from 9.95 in 1989 to 5.9 Km 2 in 2019 for Sungun mine, from 42.14 in 1999 to 33.09 Km 2 in 2019 for Athabasca oil sands, from 231.46 in 1996 to 263.95 Km 2 in 2016 for Singrauli coalfield, and from 180.38 in 1989 to 133.99 Km 2 in 2017 for Hambach mine, as a result of expansion and development of of mineral activities. Our findings about Sungun revealed that the areal coverage of forest and green space will decrease to 15% of the total study area by 2039, resulting in reduction of the mean NDVI by almost 0.06 and increase of mean standardized LST from 0.52 in 2019 to 0.61 in 2039. our results further indicate that for Athabasca oil sands (Singrauli coalfield, Hambach mine), the mean values of standardized LST and NDVI will change from 0.5 (0.44 and 0.4) and 0.38 (0.38, 0.35) in 2019 (2016, 2017) to 0.57 (0.5, 0.47) and 0.33 (0.32, 0.28), in 2039 (2036, 2035), respectively. This can be mainly attributed to the increasing mining activities in the past as well as future years. The discussion and conclusions presented in this study can be of interest to local planners, policy makers, and environmentalists in order to observe the damages brought to the environment and the society in a larger picture.
To the Editor-A longstanding debate exists on whether ecological phenomena should be modelled 'to... more To the Editor-A longstanding debate exists on whether ecological phenomena should be modelled 'top-down' (modelling patterns that arise from mechanisms) or 'bottom-up' (modelling mechanisms to generate pattern). Recently, the discussion re-emerged in the context of modelling the spread of SARS-CoV-2 1. Simply put, the point made by Carlson et al. was that top-down correlative models are inappropriate, whereas bottom-up epidemiological models are fine. Rather than opposing families of models, we argue that all have strengths and limitations and that judicious use of all available tools is the way forward.
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Papers by Babak Naimi