Climate Change Risk of Urban Growth and Land Use/Land Cover Conversion: An In-Depth Review of the Recent Research in Iran

This research is the first literature review of the past three decades' studies on the effects of urban developent and land use/land cover (LULC) change on Iran's climate change. For this purpose, 67 articles were found, evaluated, and classified according to the spatial and temporal scale, case study, period, data type, climatic factor, methodology, and meteorological data. Moreover, the reviewed literature methodologies were classified according to the purpose, method, and data source. According to the spatial-scale results, national- and city-level studies had the lowest and highest numbers, respectively. Tehran was the most case studies because Tehran is Iran’s capital and the largest metropolitan city. In terms of the temporal scale, studies predicting future changes (urban development and climate change) included 5% of the total literature. Satellite images were the most applied data in the reviewed literature (58%). Overall, 79% of the studies used temperature-related factors to explain the climatic impacts of urban growth and LULC conversion. Spatial modeling with 52% publications was the most used method, while numerical modeling with 12% studies was the least used method. This review showed broad study gaps in applying numerical models, neighborhood scales, urban micro-scale parameters, and long-term projections forecasts due to rapid urban development in Iran compared to the rest of the world. Therefore, our synthesis will assist researchers in facilitating better design for future studies in Iran and similar countries.

Spatial and Temporal Variability of Parasite Communities: Implications for Fish Stock Identification

The spatial and temporal variability of parasite communities have received little attention when used as biological tags for identifying fish stocks. This study evaluated the potential spatial and temporal variability of the parasite communities affecting three marine fish species collected between 1993 and 2017. To avoid the potential effect of host age in parasite communities, individuals of similar ages were selected: 1123 Engraulis ringens (12–24 months old), 1904 Trachurus murphyi (24–36 months old), and 630 Merluccius gayi (36–48 months old). Most taxa show differences in the prevalence at the spatial and temporal scales, but the prevalence of some larval endoparasites remains constant at the temporal scale. At the spatial scale, an analysis of similarity (ANOSIM) showed differences in the parasite communities of three species; a canonical analysis of principal coordinates (CAP) showed low values of correct allocations (CA; ≈50%) and values of allocation due to chance (AdC) were lower than the CA. At the temporal scale, an ANOSIM showed differences between the three species. A CAP showed low values of CA (≈50–60%) and the AdC was always lower than CA. Samples at the spatial scale were well allocated to their localities or nearby localities, suggesting a spatial stability. Samples from different years were not well discriminated, suggesting temporal variability. Therefore, in studies regarding parasites as a tool for stock identification, temporal variability must be taken into account.

A cloud-based toolbox for the versatile environmental annotation of biodiversity data

A vast range of research applications in biodiversity sciences requires integrating primary species, genetic, or ecosystem data with other environmental data. This integration requires a consideration of the spatial and temporal scale appropriate for the data and processes in question. But a versatile and scale flexible environmental annotation of biodiversity data remains constrained by technical hurdles. Existing tools have streamlined the intersection of occurrence records with gridded environmental data but have remained limited in their ability to address a range of spatial and temporal grains, especially for large datasets. We present the Spatiotemporal Observation Annotation Tool (STOAT), a cloud-based toolbox for flexible biodiversity–environment annotations. STOAT is optimized for large biodiversity datasets and allows user-specified spatial and temporal resolution and buffering in support of environmental characterizations that account for the uncertainty and scale of data and of relevant processes. The tool offers these services for a growing set of near global, remotely sensed, or modeled environmental data, including Landsat, MODIS, EarthEnv, and CHELSA. STOAT includes a user-friendly, web-based dashboard that provides tools for annotation task management and result visualization, linked to Map of Life, and a dedicated R package (rstoat) for programmatic access. We demonstrate STOAT functionality with several examples that illustrate phenological variation and spatial and temporal scale dependence of environmental characteristics of birds at a continental scale. We expect STOAT to facilitate broader exploration and assessment of the scale dependence of observations and processes in ecology.

Using Temporal and Spatial Scales to Unravel the Effects of Climatic Factors on Vegetation Variations in China

Spatio-temporal variation of climatic factors generally contains spatial and temporal components that have different frequencies, which may significantly affect the overall variance structure of vegetation growth at the original scale. The objective of the study was to explore the temporal- and spatial-scale-specific relationships between vegetation growth and climatic factors based on the data of half-monthly normalized difference vegetation index (NDVI), half-monthly averaged daily mean temperature (DMT), half-monthly averaged daily range of temperature (DRT), and half-monthly accumulated precipitation (AP). The complete ensemble empirical mode decomposition (CEEMD) was used to decompose the temporal series of NDVI and climatic factors, and their temporal-scale-specific relationships were examined based on the original half-month scale. Two-dimensional empirical mode decomposition (2D-EMD) was used to decompose the spatial distributions of temporally averaged NDVI and climatic factors, and their spatial-scale-specific relationships were tested based on the original resolution of 1 km. The dominant temporal scales of NDVI were around 3, 15, and >15 years, while the dominant spatial scales of NDVI were around 2 × 104 and >10 × 104 km2. The temporal-scale-specific effects of climatic factors on NDVI were the strongest under mixed forest and were the weakest under broadleaf forest. On a 15-year time scale, NDVI was positively affected by DMT and AP at the 200–1,000 mm precipitation region and negatively affected by DRT at the 200–600 mm precipitation region. Temporal effects of climatic factors had the greatest effects on NDVI in the precipitation region of 200–600 mm and in Yunnan province, and 98.08% of the study area included multi-temporal scale effects. Relationships between NDVI and climatic factors at the half-month scale and other temporal scales were different under different elevation, latitude, longitude, land types, climatic regions, and precipitation. The spatial-scale-specific effects of climatic factors on NDVI were also differed, and the area with effects of the multi-spatial scale was about 64.38%. This indicated that multi-temporal scale and multi-spatial scale analysis could help to understand the mechanisms of effect of climatic factors on vegetation growth and provide the foundation for future vegetation restoration in fragile ecosystems.

A Quantitative Modeling and Prediction Method for Sustained Rainfall-PM2.5 Removal Modes on a Micro-Temporal Scale

PM2.5 is unanimously considered to be an important indicator of air quality. Sustained rainfall is a kind of typical but complex rainfall process in southern China with an uncertain duration and intervals. During sustained rainfall, the variation of PM2.5 concentrations in hour-level time series is diverse and complex. However, existing analytical methods mainly examine overall removals at the annual/monthly time scale, missing a quantitative analysis mode that applies micro-scale time data to describe the removal phenomenon. In order to further achieve air quality prediction and prevention in the short term, it is necessary to analyze its micro-temporal removal effect for atmospheric environment quality forecasting. This paper proposed a quantitative modeling and prediction method for sustained rainfall-PM2.5 removal modes on a micro-temporal scale. Firstly, a set of quantitative modes for sustained rainfall-PM2.5 removal mode in a micro-temporal scale were constructed. Then, a mode-constrained prediction of the sustained rainfall-PM2.5 removal effect using the factorization machines (FM) was proposed to predict the future sustained rainfall removal effect. Moreover, the historical observation data of Nanjing city at an hourly scale from 2016 to January 2020 were used for mode modeling. Meanwhile, the whole 2020 year observation data were used for the sustained rainfall-PM2.5 removal phenomenon prediction. The experiment shows the reasonableness and effectiveness of the proposed method.

Molecular phylogenetic analysis of the genus Gloydius (Squamata, Viperidae, Crotalinae), with description of two new alpine species from Qinghai-Tibet Plateau, China

We provide a molecular phylogeny of Asian pit vipers (the genus Gloydius) based on four mitochondrial genes (12S, 16S, ND4, and cytb). Sequences of Gloydius himalayanus, the only member of the genus that occurs south of the Himalayan range, are included for the first time. In addition, two new species of the genus Gloydius are described based on specimens collected from Zayu, Tibet, west of the Nujiang River and Heishui, Sichuan, east of the Qinghai-Tibet Plateau. The new species, Gloydius lipipengi sp. nov., can be differentiated from its congeners by the combination of the following characters: the third supralabial not reaching the orbit (separated from it by a suborbital scale); wide, black-bordered greyish postorbital stripe extending from the posterior margin of the orbit (not separated by the postoculars, covering most of the anterior temporal scale) to the ventral surface of the neck; irregular black annular crossbands on the mid-body; 23-21-15 dorsal scales; 165 ventral scales, and 46 subcaudal scales. Gloydius swildsp. nov. can be differentiated from its congeners by the narrower postorbital stripe (only half the width of the anterior temporal scale, the lower edge is approximately straight and bordered with white); a pair of arched stripes on the occiput; lateral body lakes black spots; a pair of round spots on the parietal scales; 21 rows of mid-body dorsal scales; zigzag dark brown stripes on the dorsum; 168–170 ventral scales, and 43–46 subcaudal scales. The molecular phylogeny in this study supports the sister relationship between G. lipipengisp. nov. and G. rubromaculatus, another recently described species from the Qinghai-Tibet Plateau, more than 500 km away, and indicate the basal position of G. himalayanus within the genus and relatively distant relationship to its congeners.

A Systematic Review of Spatial-Temporal Scale Issues in Sociohydrology

Sociohydrology is a recent effort to integrate coupled human-water systems to understand the dynamics and co-evolution of the system in a holistic sense. However, due to the complexity and uncertainty involved in coupled human-water systems, the feedbacks and interactions are inherently difficult to model. Part of this complexity is due to the multi-scale nature across space and time at which different hydrologic and social processes occur and the varying scale at which data is available. This systematic review seeks to comprehensively collect those documents that conduct analysis within the sociohydrology framework to quantify the spatial-temporal scale(s) and the types of variables and datasets that were used. Overall, a majority of sociohydrology studies reviewed were primarily published in hydrological journals and contain more established hydrological, rather than social, models. The spatial extents varied by political and natural boundaries with the most common being cities and watersheds. Temporal extents also varied from event-based to millennial timescales where decadal and yearly were the most common. In addition to this, current limitations of sociohydrology research, notably the absence of an interdisciplinary unity, future directions, and implications for scholars doing sociohydrology are discussed.