Latitude or altitude as the future refugium? A case for the future of forests in Asia Minor and its surroundings.

At the current juncture with climate change, centennial projections of species distributions in biodiversity hotspots, using dynamic vegetation models may provide vital insight into conservation efforts. This study aims to answer: (1) if climate change progresses under a business-as-usual scenario of anthropogenic emissions for this century, how may the forest ranges be affected? (2) will there be potential regional extinctions of the taxa simulated? (3) may any site emerge as a potential refugium? STUDY AREA: Anatolian Peninsula and its surroundings, longitudes 24-50° E, latitudes 33-46° N. Time Period: 1961-2100. Major Taxa Studied: 25 woody species and a C3 grass-type. METHOD: Keeping a spatial window large enough to track potential changes in the vegetation range and composition especially in the mountain ranges within the study area, we parameterized a process-based regional-to-global dynamic vegetation model (LPJ-GUESS v 4.1), forced it with ERA5-Land reanalysis for the historical period, and five different bias-corrected centennial global circulation model (GCM) datasets under SSP5-8.5, and simulated the dynamic responses of key forest species. Bivariate spatio-temporal maps from the simulation results were constructed for final analysis. RESULTS: A significant increase in woody taxa biomass for the majority of our study area, towards the end of the century was simulated, where temperate taxa with high tolerance for drought and a wider range of temperatures took dominance. The mountain ranges in our study area stood out as critical potential refugia for cold favoring species. There were no regional extinctions of taxa, however, important changes in areal dominance and potential future forest composition were simulated. MAIN CONCLUSIONS: Our simulation results suggest a high potential for future forest cover in our study region by the end of the century under a high emissions scenario, sans human presence, with important changes in vegetation composition, including encroachment of grasslands ecosystems by woody taxa.

The spatial configuration of local climate zones reveals effects on wayfinding in human walking.

The importance of easy wayfinding in complex urban settings has been recognized in spatial planning. Empirical measurement and explicit representation of wayfinding, however, have been limited in deciding spatial configurations. Our study proposed and tested an approach to improving wayfinding by incorporating spatial analysis of urban forms in the Guangdong-Hong Kong-Macau Great Bay Area in China. Wayfinding was measured by an indicator of intelligibility using spatial design network analysis. Urban spatial configurations were quantified using landscape metrics to describe the spatial layouts of local climate zones (LCZs) as standardized urban forms. The statistical analysis demonstrated the significant associations between urban spatial configurations and wayfinding. These findings suggested, to improve wayfinding, 1) dispersing LCZ 1 (compact high-rise) and LCZ 2 (compact mid-rise) and 2) agglomerating LCZ 3 (compact low-rise), LCZ 5 (open mid-rise), LCZ 6 (open low-rise), and LCZ 9 (sparsely built). To our knowledge, this study is the first to incorporate the LCZ classification system into the wayfinding field, clearly providing empirically-supported solutions for dispersing and agglomerating spatial configurations. Our findings also provide insights for human-centered spatial planning by spatial co-development at local, urban, and regional levels.

Ecohydrological insight: Solar farms facilitate carbon sink enhancement in drylands.

Solar farms are critical to tackling climate change and achieving carbon neutrality. Besides producing renewable energy, a solar farm modifies microclimates and changes water distribution, consequently affecting local carbon sequestration capacity (CSC). Yet, how the CSC of an ecosystem responds to these changes after solar farm construction remains inadequately understood. Herein, the SOFAR model was adopted to reveal the effects of large-scale solar farms (LSFs) on CSC in arid northern China, with a series of numeric experiments along a climate gradient (with precipitation ranging from 70 to 500 mm yr-1). The results show that relative to pristine vegetation background, CSC was non-linearly increased by averages of 3.49-6.68%, 4.43-10.25%, 5.07-9.71% and 5.6% each year after the installation of LSFs in hyper-arid climates (with aridity index or AI = 0.04-0.05), arid climates (AI = 0.14-0.16), semi-arid climates (AI = 0.21-0.3) and semi-humid climates (AI = 0.55), respectively. The increase in available water for plants growing under the drip lines of photovoltaic panels (PVs) in LSFs is confirmed to be the overwhelming factor responsible for CSC enhancement. Although biases remain in the estimation of increased CSC in hyper- and semi-humid regions due to the high variability of climate (e.g., extreme drought events) and serious radiation reduction beneath PVs, it is certain that solar farms facilitate CSC without increasing external land use. These results will deepen our understanding of the feedback between solar farms and ambient environments and be meaningful for vegetation management in solar farms, especially in the context of climate change and carbon neutrality aims.

Integrating the Budyko framework with the emerging hot spot analysis in local land use planning for regulating surface evapotranspiration ratio.

Land use planning regulates surface hydrological processes by adjusting land properties with varied evapotranspiration ratios. However, a dearth of empirical spatial information hampers the regulation of place-specific hydrological processes. Therefore, this study proposed a Local Land Use Planning framework for EvapoTranspiration Ratio regulations (ETR-LLUP), which was tested for the developments of spatially-varied land use strategies in the Dongjiang River Basin (DRB) in Southern China. With the first attempt at integrating the Emerging Hot Spots Analysis (EHSA) with the Budyko framework, the spatiotemporal trends of evapotranspiration ratios based on evaporative index and dryness index, from 1992 to 2018, were illustrated. Then, representative land-cover types in each sub-basin were defined using Geographically Weighted Principal Component Analysis, in two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018), which in turn were identified using the Standard Precipitation Index. Finally, Geographically Weighted Regressions (GWRs) were used to detect spatially-varied relationships between land-cover proportions and evaporative index in both dry and wet climates. Results showed that the DRB was consistently a water-limited region from 1992 to 2018, and the situation was getting worse. We also identified the upper DRB as hotspots for hydrological management. Forests and croplands experienced increasingly water stress compared to other vegetation types. More importantly, the spatial results of GWR models enabled us to adjust basin land use by 1) expanding and contracting a combination of 'mosaic natural vegetation' and 'broadleaved deciduous trees' in the western and eastern parts of the basin, respectively; and 2) increasing 'broadleaved evergreen trees' in the upstream parts of the basin. These spatially-varied land use strategies based on the ETR-LLUP framework allow for place-specific hydrological management during both dry and wet climates.

Ecohydrological effects of photovoltaic solar farms on soil microclimates and moisture regimes in arid Northwest China: A modeling study.

Photovoltaic technology plays an important role in the sustainable development of clean energy, and arid areas are particularly ideal locations to build large-scale solar farms, all over the world. Modifications to the energy balance and water availability through the installation of large-scale solar farms, however, fundamentally affect the energy budget, water, and biogeochemical cycles. In-situ field observations, though, fail to draw definitive conclusions on how photovoltaic panels (PVs) affect the ambient environment, or how microclimates and soil moisture evolve under the long-term, continuous, cumulative influence of PVs. Here, we designed a synthetic model, integrating processes of energy budget and water cycle, to quantify the ecohydrological effects of PVs on soil microclimate and moisture regimes at different locations (zones) near individual PVs. Simulations run with a stochastically generated 100-year climate time series were examined to capture the evolutionary trends of soil microclimate and soil moisture. The results indicate that soil moisture content was increased by 59.8% to 113.6% in the Middle and Front zones, and soil temperature was decreased by 1.47 to 1.66 °C in all the sheltered zones, mainly because there was 5- 7 times more available water and ~27% less available radiation there, compared with the control zone. On the other hand, if the ground clearance of the PVs is too low, turbulence beneath hot PVs will have a significant influence on not only soil temperature but also soil moisture content. The innovative contribution of this study lies in reinforcing existing theoretical patterns for the development of soil microclimate and moisture dynamics influenced by PVs, and can be used to provide reliable insights into the hydrological and biogeochemical processes on Earth and the sustainable management of large-scale solar farms in arid ecosystems.

Mapping groundwater-dependent ecosystems in arid Central Asia: Implications for controlling regional land degradation.

Groundwater-dependent ecosystems (GDEs) exist all over the world, especially in water-limited regions. To achieve better water management, it is necessary to map and identify GDEs. Central Asia (CA) is one of the most arid regions in the mid-latitudes and one of the major regions with shallow groundwater tables. However, the role of groundwater in the impacts of climate change and regional anthropogenic activities on environmental risks, especially regional desertification, is inadequately understood due to the limited available research on GDEs. In the present study, a remote sensing-based method was used for mapping GDEs in regional CA, and three means-overlay analysis, correlation analysis, and the water balance method-were adopted to validate the accuracy of the mapping outcomes. Our results indicated that: 1) GDEs were concentrated around large lakes and in central Kazakhstan (between 46°N and 50°N latitudes), and areas "Very Likely" and "Likely" to be GDEs accounted for 36.89%, and 28.85% of the total natural vegetation areas, respectively; 2) at the watershed scale, the Sarysu Basin had the largest proportion (94.02% of the area) of potential GDEs while the Ysyk-Kol Basin had the lowest proportion (17.84%); 3) all the three validation methods indicated a good performance for our GDE mapping results. We concluded that the remote sensing-based GDE identification method can be considered a potential approach for mapping GDEs regionally. Better recognition of relationships among groundwater availability, ecosystem health and groundwater management policies should be developed by conducting further studies, to protect GDEs and to prevent regional land degradation.

Gravimetry-based water storage shifting over the China-India border area controlled by regional climate variability.

The regional water storage shifting causes nonstationary spatial distribution of droughts and flooding, leading to water management challenges, environmental degradation and economic losses. The regional water storage shifting is becoming evident due to the increasing climate variability. However, the previous studies for climate drivers behind the water storage shifting are not rigorously quantified. In this study, the terrestrial water storage (TWS) spatial shifting pattern during 2002-2017 over the China-India border area (CIBA) is developed using the Gravity Recovery and Climate Experiment (GRACE), suggesting that the Indus-Ganges-Brahmaputra basin (IGBB) was wetting while the central Qinghai-Tibet Plateau (QTP) was drying. Similar drying and wetting patterns were also found in the precipitation, snow depth, Palmer Drought Severity Index (PDSI) and potential evaporation data. Based on our newly proposed Indian monsoon (IM) and western North Pacific monsoon (WNPM) variation indices, the water shifting pattern over the CIBA was found to be affected by the weakening of the variation of IM and WNPM through modulating the regional atmospheric circulation. The weakening of IM and WNPM variations has shown to be attributed to the decreasing temperature gradient between the CIBA and the Indian Ocean, and possibly related to increasing regional temperatures associated with the increasing global temperature. As the global warming intensifies, it is expected that the regional TWS shifting pattern over the CIBA will be further exaggerated, stressing the need of advancing water resources management for local communities in the region.

The influence of meteorological conditions and atmospheric circulation types on PM10 levels in western Turkey.

High levels of atmospheric pollutants have been frequently measured in Turkey during the last decade. Specifically, the occurrence of these high particulate matter concentrations is often related to either local-scale conditions or regional-scale transport. In order to better understand the atmospheric factors that trigger poor air quality, further research investigating the relationship between air pollution and meteorological variables or atmospheric circulation patterns is needed. In this study, the influence of synoptic-scale weather types on PM10 levels over the Aegean region of Turkey is investigated for the period 2008-2015. First of all, hourly PM10 concentrations of 13 air quality stations are respectively converted to daily, seasonal, and regional averages. The seasonal variability of PM10 values in the region indicates that high particulate matter concentrations are registered in winter, fall, spring, and summer months with mean values at 90.6 (± 38.3 standard deviation), 66.9 (± 28.3), 61.6 (± 23.4), and 54.1 (± 12.8) µg m-3, respectively. In regard to the synoptic-scale approach, eight directional and two vorticity types of the Lamb weather type (LWT) method are used in the analysis. Based on the results, poor air quality conditions are observed in all seasons during active southeasterly (SE, interaction between a low pressure over Italy and a high pressure over the Caspian Sea) circulation types (CTs). In winter, mainly easterly (E), SE, southerly (S), and anticyclonic (A) weather patterns result in above normal PM10 concentrations. In addition to these four CTs, southwesterly (SW) types also cause higher PM10 values in the spring season. During summer, SE, SW, westerly (W), and cyclonic (C) CTs are associated with above-normal PM10 values. During fall, obvious higher PM10 concentrations are found during SE, S, and A types.

Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A geospatial modeling approach - Part 1.

Headwater wetlands affect ecosystem integrity of downstream waters; however, many wetlands - particularly geographically isolated wetlands (GIWs) - continue to be at risk. A significant portion of US federal policy is based on the jurisdictional status of wetlands, which is partly determined by the relationship between wetlands and downstream waters, including the cumulative impact of wetlands on those waters. We present a novel multi-phase geospatial modeling method to help elucidate hydrological relationship between GIWs and downstream waters at the landscape scale. The presented approach in this study used inundation maps derived from time series remotely sensed data between 1985 and 2010, weather and hydrological records, and ancillary geospatial data including information from the US Fish and Wildlife Service National Wetlands Inventory (NWI). The study site was a headwater catchment (292 km2) of the Choptank River Basin, located in the Mid-Atlantic region of USA, which contained a large number of Delmarva bays. The results showed inundation extent within GIWs varied, in aggregate, in response to weather variability (r = 0.58; p-value = 0.05), and was well correlated with streamflow (r = 0.81; p-value < 0.01) and base flow (r = 0.57; p-value < 0.1) conditions. The relationship between inundation patterns and stream discharge also varied with NWI hydrologic modifiers. The GIWs with water regime characterized by longer durations of flooding exhibited stronger correlations with stream discharge, but those GIWs with shorter durations of flooding were less correlated with stream discharge. This analysis suggests the mutual reliance (i.e., connection) of wetlands and streams on groundwater. GIWs appeared to function in aggregate, and it is likely that the combined effect of these wetlands significantly influenced the functioning of downstream waters.

Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A catchment modeling approach - Part 2.

In Part 1 of this two-part manuscript series, we presented an effective assessment method for mapping inundation of geographically isolated wetlands (GIWs) and quantifying their cumulative landscape-scale hydrological connectivity with downstream waters using time series remotely sensed data (Yeo et al., 2018). This study suggested strong hydrological coupling between GIWs and downstream waters at the seasonal timescale via groundwater. This follow-on paper investigates the hydrological connectivity of GIWs with downstream waters and cumulative watershed-scale hydrological impacts over multiple time scales. Modifications were made to the representation of wetland processes within the Soil and Water Assessment Tool (SWAT). A version of SWAT with improved wetland function, SWAT-WET, was applied to Greensboro Watershed, which is located in the Mid-Atlantic Region of USA, to simulate hydrological processes over 1985-2015 under two contrasting land use scenarios (i.e., presence and absence of GIWs). Comparative analysis of simulation outputs elucidated how GIWs could influence partitioning of precipitation between evapotranspiration (ET) and terrestrial water storage, and affect water transport mechanisms and routing processes that generate streamflow. Model results showed that GIWs influenced the watershed water budget and stream flow generation processes over the long-term (30 year), inter-annual, and monthly time scales. GIWs in the study watershed increased terrestrial water storage during the wet season, and buffered the dynamics of shallow groundwater during the dry season. The inter-annual modeling analysis illustrated that densely distributed GIWs can exert strong hydrological influence on downstream waters by regulating surface water runoff, while maintaining groundwater recharge and ET under changing (wetter) climate conditions. The study findings highlight the hydrological connectivity of GIWs with downstream waters and the cumulative hydrological influence of GIWs as hydrologic sources to downstream ecosystems through different runoff processes over multiple time scales.