Chilgoza pine is an economically and ecologically important evergreen coniferous tree species of the dry and rocky temperate zone, and a native of south Asia. This species is rated as near threatened (NT) by the International Union for Conservation of Nature (IUCN). This study hypothesized that climatic, soil and topographic variations strongly influence the distribution pattern and potential habitat suitability prediction of Chilgoza pine. Accordingly, this study was aimed to document the potential habitat suitability variations of Chilgoza pine under varying environmental scenarios by using 37 different environmental variables. The maximum entropy (MaxEnt) algorithm in MaxEnt software was used to forecast the potential habitat suitability under current and future (i.e., 2050s and 2070s) climate change scenarios (i.e., Shared Socio-economic Pathways (SSPs): 245 and 585). A total of 238 species occurrence records were collected from Afghanistan, Pakistan and India, and employed to build the predictive distribution model. The results showed that normalized difference vegetation index, mean temperature of coldest quarter, isothermality, precipitation of driest month and volumetric fraction of the coarse soil fragments (>2 mm) were the leading predictors of species presence prediction. High accuracy values (>0.9) of predicted distribution models were recorded, and remarkable shrinkage of potentially suitable habitat of Chilgoza pine was followed by Afghanistan, India and China. The estimated extent of occurrence (EOO) of the species was about 84,938 km², and the area of occupancy (AOO) was about 888 km², with 54 major sub-populations. This study concluded that, as the total predicted suitable habitat under current climate scenario (138,782 km²) is reasonably higher than the existing EOO, this might represent a case of continuous range contraction. Hence, the outcomes of this research can be used to build the future conservation and management plans accordingly for this economically valuable species in the region.

The potential distribution of Olea ferruginea was predicted by Maxent model for present and the upcoming hypothetical (2050) climatic scenario. O. ferruginea is an economically beneficial plant species. For predicting the potential distribution of O. ferruginea in Pakistan, Worldclim variables for current and future climatic change scenarios, digital elevation model (DEM) slope, and aspects with the occurrence point were used. Pearson correlation was used to reject highly correlated variables. A total of 219 sighting points were used in the Maxent modeling. The area under curve (AUC) value was higher than 0.98. The approach used in this study is considered useful in predicting the potential distribution of O. ferruginea species, and can be an effective tool in the conservation and restoration planning for human welfare. The results show that there is a significant impact under future bioclimatic scenarios on the potential distribution of O. ferruginea in Pakistan. There is a significant decrease in the overall distribution of O. ferruginea due to loss of habitats under current distribution range, but this will be compensated by gain of habitat at higher altitudes in the future climate change scenario (habitat shift). It is recommended that the areas predicted suitable for the O. ferruginea may be used for plantation of this species while the deforested land should be restored for human welfare.

Rapid urbanization in Pakistan is triggering regulated and unregulated land cover changes in planned and semiplanned urban areas. The key objective of this study is to assess the spatial–temporal fluctuations in the land use/land cover (LULC) transformations in planned (Islamabad) and semiplanned (Rawalpindi) urban areas over the last forty years (1976–2016). The study focuses on the orientation of LULC modifications and analyzes concomitant impacts on urban environmental sustainability. Therefore, remotely sensed data were retrieved and processed through Google Earth Engine (GEE) by applying supervised classifier algorithms on each of the five chosen Landsat images. The trajectory of LULC changes for each of the four periods 1976–1988, 1988–1995, 1995–2006 and 2006–2016 was critically scrutinized. The observations revealed massive physical expansions and LULC convergences during these timeframes. The proportionate share of built-up surfaces in this contextual setting substantially stretched from 0.83% in 1976 to 23.23% in 2016, while the shares of cropland and shrubberies significantly reduced. The orientation and magnitude of such changes were observed asymmetrically in the adjoining urban settlements. The assessments formulate that availability of land for urban growth, urban planning and regulatory control significantly determines the speed, scale and orientation of urbanization in planned and semiplanned areas. The study substantiates the notions that the efficient use of cost-effective remotely sensed data offers a pragmatic and reliable tool for assessing, evaluating and monitoring urban land resources. The inferences and insights are relevant for urban and regional planners as well as for other scientific communities.

Industrialization is indispensable for socio-economic development but poses far-reaching implications for resources and the environment. Consequently, industrial symbiosis-based collaborations are gaining recognition as a viable strategy to manage resource consumption for mitigating environmental distress. However, these types of synergistic collaborations are more prevalent in developed regions and are linked to larger-sized industries. Admittedly, such collaborative partnerships are less focused in developing regions and small- to medium-size enterprises (SMEs). This calls for discovering the potentials for synergistic partnerships among the small and medium scaled industrial entities in developing economies. Therefore, the study was designed to identify, assess and explore the prospects of symbiotic collaborations among SMEs in Pakistan. Moreover, the inputs are equally relevant for developing and expanding such productive associations in developing regions. Data regarding inputs and outputs was collected from sixty-one (61) SMEs through field survey during the year 2019. It was processed and analyzed to uncover existing and potential synergies among SMEs. The significant findings transpired that the majority of collaborative linkages are bilateral and are driven to maximize economic gains. However, informal networks of recyclers and absence of a stringent regulatory regime are the ground realities in developing/transforming economies. These factors symptomatically interfere with the process of formal/informal exchanges between and among firms. Furthermore, it was observed that the lack of awareness and impulsiveness of SMEs, as well as the inconsistent supply of by-products, act as barriers for such partnerships in developing countries. It calls for proactive engagements and facilitations from the state institutions through policy instruments. The study addresses a broad audience including industrialists, investors, policy makers and researchers engaged in IS studies. Moreover, the inputs will provide impetus for stimulating eco-industrial progress in developing regions such as Pakistan.

Urban ecosystem services (UES) are indispensable for life. Stakeholders are improvising strategies for a more sustainable provisioning of UES. For this purpose and for identifying orientations towards geospatial data in UES studies, the “bibliometric analysis” technique was deployed. The inclinations facilitate assessments pertaining to spatio-temporal oscillations in the supply–demand equilibrium. The propensities are gaining recognition due to time and cost effectiveness. Besides this, Remote Sensing (RS) in conjunction with Geographic Information System (GIS), enables the conduct of synoptic and robust periodic evaluations. The study analyzes inclinations towards RS in contemporary research (2010–2020) focusing, particularly, on urban ecosystem services. It specifically focuses on methodological frameworks and major sources of remotely sensed data. Therefore, a total of 261 records of research articles were identified and retrieved. Subsequently, 79 articles were selected for further processing and content analysis. It transpired that approximately 30% of the selected publications deployed remotely sensed data for assessment purposes. The majority (96%) of such studies were conducted in economically developed and industrialized countries. However, the researchers from both developed and developing countries prefer open software and free data sources. Besides this, they prefer satellite-based optical sensors over image sensors such as TIR, SAR, or light sensors for acquiring data. The findings formulate that Land Use Land Cover (LULC)-based methodologies and inclinations for assessing regulating services are more frequently pursued. The findings revealed that enhanced research collaborations, access to data, and assessment gadgets are obligatory for capacity building in developing regions. Knowledge sharing and cost-effective access to RS and GIS based platforms are incumbent for ensuring urban environmental sustainability in developing economies.