Local Climate Variability Research Articles

Urban soil management in the strategies for adaptation to climate change of cities in the Tropical Andes

The unique characteristics of a city amplify the impacts of climate change; therefore, urban planning in the 21st century is challenged to apply mitigation and adaptation strategies that ensure the collective well-being. Despite advances in monitoring urban environmental change, research on the application of adaptation-oriented criteria remains a challenge in urban planning in the Global South. This study proposes to include urban land management as a criterion and timely strategy for climate change adaptation in the cities of the Tropical Andes. Here, we estimate the distribution of the soil organic carbon stock (OCS) of the city of Quito (2,815 m.a.s.l.; population 2,011,388; 197.09 km2) in the following three methodological moments: i) field/laboratory: city-wide sampling design established to collect 300 soil samples (0–15 cm) and obtain data on organic carbon (OC) concentrations in addition to 30 samples for bulk density (BD); ii) predictors: geographic, spectral and anthropogenic dimensions established from 17 co-variables; and iii) spatial modeling: simple multiple regression (SMRM) and random forest (RFM) models of organic carbon concentrations and density as well as OCS stock estimation. We found that the spatial modeling techniques were complementary; however, SMRM showed a relatively higher fit both (OC: r2 = 20%, BD: r2 = 16%) when compared to RFM (OC: r2 = 8% and BD: r2 = 5%). Thus, soil carbon stock (0–0.15 m) was estimated with a spatial variation that fluctuated between 9.89 and 21.48 kg/m2; whereas, RFM showed fluctuations between 10.38 and 17.67 kg/m2. We found that spatial predictors (topography, relative humidity, precipitation, temperature) and anthropogenic predictors (population density, roads, vehicle traffic, land cover) positively influence the model, while spatial predictors have little influence and show multicollinearity with relative humidity. Our research suggests that urban land management in the 21st century provides key information for adaptation and mitigation strategies aimed at coping with global and local climate variations in the cities of the Tropical Andes.

Growth response of seven multipurpose tree species to climatic factors: A case study from northwestern Himalayas, India

Identification of the species for dendrochronological studies is of great relevance to understand various aspects of climate change. However, in the northwestern Himalayan region, dendroclimatological investigations are confined to conifer species, with broadleaved species being disregarded. Thus, the present study was conducted to assess the growth response of seven multipurpose tree species (MPTs), namely Bauhinia variegata, Celtis australis, Grewia optiva, Paulownia fortunei, Toona ciliata, Ulmus villosa and Melia composita to local climate variables, viz. temperature as well as rainfall (seasonal, monthly, average) and CO2 level by evaluating the climatic signal in tree ring chronologies at Solan district, India (altitude 1 250 m) in the mid-hills of the northwestern Himalayas. The results indicated that only the maximum, rainy season temperature and CO2 level varied significantly (P < 0.05) between 1991 and 2017. Only G. optiva exhibited a significant (P < 0.05) tendency toward increased growth. C. australis has a remarkable negative correlation with temperature variables, viz. average, maximum, spring season, March temperature, whereas T. ciliata exhibits a positive correlation with temperature variables, such as rainy season, average and April temperature. Similarly, winter, total and December rainfall have a profound effect on P. fortunei, while March rainfall adversely affected the growth of B. variegata. On the other hand, G. optiva demonstrated sensitivity to both temperature (February and May) and rainfall variables (winter, February and May). U. villosa recorded a positive correlation with rainfall (autumn and October rainfall) but a negative correlation with temperature variables (maximum and April temperature). Elevated CO2 levels affected only two species (G. optiva, M. composita) out of the seven selected species. Our findings will contribute to a better understanding of the climate growth relationships of investigated tree species, as a result, to more accurate projections of the effects of climate change on these MPTs and directing future studies.

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981\u20132018

BackgroundUnderstanding the climate variability at local scale could help suggest local adaptation responses to manage climate associated risks. This paper analyzed the variability and trend of climate in semi-arid Borana zone of southern Ethiopia over the period 1981–2018 using Mann–Kendall (MK) test, Sen’s Slope Estimator (SEE) and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) climate data (daily precipitation, daily maximum temperature (Tmax) and minimum temperature (Tmin)) were collected from National Meteorology Agency (NMA) of Ethiopia.ResultsThe results revealed the study area received a mean monthly precipitation of 39.19 mm and a monthly mean Tmax and Tmin of 29.66 °C and 16.31 °C were observed respectively. Rainfall shows a significant increasing trend during August, October and November and extremely variable during December, January and February where CV > 100%. Tmax shows a significant warming trend during August but January, February, August and October exhibited similar trend for Tmin. Rainfall and Tmin shows a significant trend during Meher and no trend for the rest of the seasons. Mean annual rainfall shows a significant increase where no trend observed for both Tmax and Tmin at this timescale. Decadal rainfall and Tmin exhibited no trend but Tmax show significant warming trend during 2001–2010 decade. Better rainfall and cooler temperature were observed in the north central, northeastern and northwestern whereas the southeastern and southwestern regions were drier and warmer.ConclusionRainfall is highly variable than temperature both at temporal and spatial scales in Borana. The intensity of rainfall decreases from the northeastern and northwestern parts towards the southwest while temperature increased from the north central parts towards the southwest for Tmax and the southeast for Tmin. The effect of topography is substantial for the local scale variability observed in the study area. Internal variability is observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.

Drivers of Collembola assemblages along an altitudinal gradient in northeast China.

Altitudinal changes in the diversity of plants and animals have been well documented; however, soil animals received little attention in this context and it is unclear whether their diversity follows general altitudinal distribution patterns. Changbai Mountain is one of few well‐conserved mountain regions comprising natural ecosystems on the Eurasian continent. Here, we present a comprehensive analysis of the diversity and community composition of Collembola along ten altitudinal sites representing five vegetation types from forest to alpine tundra. Among 7834 Collembola individuals, 84 morphospecies were identified. Species richness varied marginally significant with altitude and generally followed a unimodal relationship with altitude. By contrast, the density of Collembola did not change in a consistent way with altitude. Collembola communities changed gradually with altitude, with local habitat‐related factors (soil and litter carbon‐to‐nitrogen ratio, litter carbon content, and soil pH) and climatic variables (precipitation seasonality) identified as major drivers of changes in Collembola community composition. Notably, local habitat‐related factors explained more variation in Collembola assemblages than climatic variables. The results suggest that local habitat‐related factors including precipitation and temperature are the main drivers of changes in Collembola communities with altitude. Specifically, soil and litter carbon‐to‐nitrogen ratio correlated positively with Collembola communities at high altitudes, whereas soil pH correlated positively at low altitudes. This documents that altitudinal gradients provide unique opportunities for identifying factors driving the community composition of not only above‐ but also belowground invertebrates.

Integrated Climate Action Planning (ICLAP) in Asia-Pacific Cities: Analytical Modelling for Collaborative Decision Making

While climate change has global causations and impacts, there is growing consensus on addressing the 2 °C challenge through local actions. However, at the local level, there is disintegrated knowledge on the following: (a) short-, mid- and long-term climate vulnerability, (b) economy and GHG structures and their future pathways, and (c) useful mitigation and adaptation undertaken elsewhere. We evaluate these gaps through a comprehensive review of scientific literature and policy approaches of urban-climate studies in the Asia-Pacific Region. Based on the research findings, we develop a collaborative research framework of an integrated climate action planning (ICLAP) model for evidence-based decision-making tool. It adopts an innovative methodology integrating knowledge and data from diverse analytics, as follows: (a) spatial: downscaling global/regional climate scenarios to forecast local climate variability (50 km × 50 km) for 2030 (SDG target) and 2050; (b) statistical: a meta-analysis of 49 five-million-plus cities to forecast economic, energy and GHG scenarios; (c) bibliometric: a systematic review of global urban climate interventions from Google Scholar that collectively aid cities on policy inputs for mid-term climate variability, GHG profiles and available solutions at their disposal. We conclude with a discussion on scientific and policy relevance of such a tool in fostering overall urban, regional and global sustainability.

Analysis of rainfall and temperature trends and variability in semi-arid Tharaka South Subcounty, Kenya

To better understand the impacts of climate variability, including spatiotemporal variations in mean rainfall, temperature, and other climatic elements, it is imperative to analyze the dynamics of these elements. Despite the high vulnerability of the Tharaka South Subcounty, Kenya, to the impacts of climate change and variability, no studies have analyzed the local climatic trends and variability to inform response strategies. In this study, we analyzed rainfall and temperature trends and variability in Tharaka South Subcounty using gridded rainfall and temperature data sourced from CHIRPS and CHIRTS. Variability analysis employed descriptive statistics, coefficients of variation, standardized anomalies, and the precipitation concentration index. Trends were analyzed using a Mann-Kendall test and Sen’s slope estimator. The study area is characterized by low rainfall that shows a decreasing trend. Local rainfall is generally marked by high and increasing variability, high and increasing concentration, and a high probability of extreme events. The area has also experienced increasingly severe and frequent droughts, with most years in the study period having below-average rainfall. Rainfall variability is thus characterized by a decrease in rainfall, high rainfall concentration, extreme rainfall events, and more frequent and severe droughts. Large-scale climate forcings also influence the local rainfall trends and variability. In addition, the study area has high temperatures that show an increasing trend, and the region experiences a fluctuating temperature regime. An increase in temperature is associated with a reduction in rainfall amount. Moreover, the area is marked by spatial variability of rainfall and temperature, both with positive and negative spatial trends. The findings of this study will improve understanding of climatic trends and variability, leading to a better understanding of their impacts and informing the development of effective response strategies in the study area.

Climate variations affect the growth period of young Tectona grandis Linn F. in the Amazon

Climate change is expected to increase the occurrence of severe droughts in the tropics, and little is known about its influence on tree dynamics. Tree-ring width and remote sensing tools can help understand the impacts of climate change on tree growth. We evaluated the applicability of NDVI to obtain phenological metrics (e.g., start, peak, end, and length of growth season) and explored its relationship with tree-ring width of Tectona grandis (teak). The phenological metrics and tree-ring width were correlated with each other, and with both local (temperature, precipitation, solar insolation, Standardized Precipitation Evapotranspiration Index - SPEI) and large-scale (El Niño) climatic variables. The length of season and tree-ring width of teak were positively correlated with precipitation and negatively correlated with temperature in the initial months of the growth period. Tree-ring width was negatively correlated with El Niño events. Climate variables and length of season from the prior period were correlated with the tree-ring width of the current growing period. This study demonstrated that rather than directly affecting productivity, climate might also affect the length of the growing season, which would affect tree growth in the next season.

Long-Term Lake Area Change and Its Relationship with Climate in the Endorheic Basins of the Tibetan Plateau

Lakes are sensitive indicators of climate change in the Tibetan Plateau (TP), which have shown high temporal and spatial variability in recent decades. The driving forces for the change are still not entirely clear. This study examined the area change of the lakes greater than 1 km2 in the endorheic basins of the Tibetan Plateau (EBTP) using Landsat images from 1990 to 2019, and analysed the relationships between lake area and local and large-scale climate variables at different geographic scales. The results show that lake area in the EBTP has increased significantly from 1990 to 2019 at a rate of 432.52 km2·year−1. In the past 30 years, lake area changes in the EBTP have mainly been affected by local climate variables such as precipitation and temperature. At a large scale, Indian Summer Monsoon (ISM) has correlations with lake area in western sub-regions in the Inner Basin (IB). While Atlantic Multidecadal Oscillation (AMO) has a significant connection with lake area, the North Atlantic Oscillation (NAO) does not. We also found that abnormal drought (rainfall) brought by the El Niño/La Niña events are significantly correlated with the lake area change in most sub-regions in the IB.

Climatic Variability and Human Leptospirosis Cases in Cartagena, Colombia: A 10-Year Ecological Study.

Leptospirosis is an acute febrile disease that mainly affects developing countries with tropical climates. The complexity and magnitude of this disease is attributed to socioeconomic, climatic, and environmental conditions. In this study, in a 10-year period from 2008 to 2017, the relationship between human leptospirosis cases and climatic factors in Cartagena de Indias, Colombia were evaluated. Monthly leptospirosis cases, climatic variables, and macroclimatic phenomena (El Niño and La Niña) were obtained from public datasets. Local climatic factors included temperature (maximum, average, and minimum), relative humidity, precipitation, and the number of precipitation days. Time series graphs were drawn and correlations between cases of leptospirosis and climatic variables considering lags from 0 to 10 months were examined. A total of 360 cases of leptospirosis were reported in Cartagena during the study period, of which 192 (53.3%) were systematically notified between October and December. Several correlations were detected between the number of cases, local climatic variables, and macroclimatic phenomena. Mainly, the increase of cases correlated with increased precipitation and humidity during the La Niña periods. Herein, seasonal patterns and correlations suggest that the climate in Cartagena could favor the incidence of leptospirosis. Our findings suggest that prevention and control of human leptospirosis in Cartagena should be promoted and strengthened, especially in the last quarter of the year.

Short-term stem diameter variations in irrigated and non-irrigated stone pine (Pinus pinea L.) trees in a xeric non-native environment

Irrigation of adult stone pine trees growing in a xeric non-native habitat had positive effects not only in stem diameter growth but also in tree response to climatic variability. Stone pine is a key species from Mediterranean Europe increasingly planted in South America. The knowledge about irrigation impact on short-term stem diameter dynamics is still limited in non-native arid areas. To improve our understanding of the effect of irrigation on (1) stem diameter changes of stone pine trees in a drought-prone environment in Chile and (2) the sensitivity of the species to weather conditions. We studied daily stem diameter changes in irrigated and non-irrigated 31-year-old stone pine trees during a growing season with below average precipitation in Chile. Short-term diameter changes were recorded using high-resolution dendrometers. The detrended daily stem diameter changes, expressing tree water status, were correlated with weather variability in both irrigated and non-irrigated trees. The growth period lasted longer and the cumulative sum of daily changes increased by 130% in irrigated trees. Moreover, a similar correlation of tree water status with climatic variables was found in non-irrigated, with the exception of precipitation. Irrigation increased stone pine productivity in this xeric environment and reduced the correlations between daily stem diameter variations and local climatic variability.

Pollen evidence of variations in Holocene climate and Southern Hemisphere Westerly Wind strength on sub-Antarctic South Georgia

The Southern Hemisphere Westerlies (SHW) play a major role in the global climate system. The winds drive ocean circulation and affect the Southern Oceans’ ability to take up atmospheric CO2. Recently, the SHW core belt has strengthened and shifted south, but there is an insufficient understanding of its long-term behaviour. Palaeoclimatic records are key for capturing long-term variability through the SHW’s effect on surface temperature and moisture availability. However, terrestrial records are sparse in the Southern Hemisphere. We use a palynological record from Lake Diamond on sub-Antarctic South Georgia to provide reconstructions of vegetation and climate for the last ~10,000 years. Influx of long-distance transported pollen is used as a measure of surface wind strength. Changes in relative pollen abundance of native taxa occupying either upland (cold) or lowland (warm) environments indicate local climatic variability. On South Georgia, we find long-distance transported pollen from South American taxa, mainly Nothofagus and Ephedra. They show a general increase in abundance throughout the Holocene, with peak influxes between 5700–5400, 2800–1500 and 1000–500 cal yr BP. These intervals coincide with colder periods inferred from the palynological record, suggesting that SHW variation and temperature on South Georgia are highly connected. Agreement with palaeoecological records from eastern Patagonia show that climatic changes have been regionally consistent. The record from Lake Diamond further illustrates the importance of remote islands in contributing to a deeper understanding of atmospheric circulation and climatic variability in the sub-Antarctic.

Heterogeneous timing of freshwater input into Kobbefjord, a low‐arctic fjord in Greenland

AbstractThe majority of freshwater input from Greenland to the global ocean stems from the Greenland Ice Sheet. Currently, almost a quarter of the freshwater flowing from Greenland is derived from catchments that are disconnected from the Greenland Ice Sheet. Despite their importance to the total freshwater flux and influence on fjord geochemistry, there is relatively little monitoring data available for those catchments and therefore the drivers of regional differences in export are largely unknown. We present a dataset of 12 years of discharge of four catchments less than 15 km apart, that are different in size (between 7 and 32 km2), local glacier coverage (4%–11%) and lake cover (0%–5%). They all drain into Kobbefjord, a well‐studied fjord in West Greenland, near Greenland's capital Nuuk. Between catchments, the magnitude of discharge varies at annual, seasonal and sub‐daily timescales, due to differences in physical catchment properties as well as local climate variability. We find that annual specific discharges vary greatly (between 1.2 and 1.9 m/year on a 12‐year average) due to a longitudinal precipitation gradient from West to East caused by different amount of orographic precipitation shading. The seasonal cycle of discharge (amplitude, timing and minimum flow) differs among the sites mainly due to different exposure to solar radiation as a driver for major snowmelt; the small ice coverage in the catchments plays only a minor role in discharge variability. Dry years generally increase the relative differences in annual specific discharge and no significant temporal trends have been found in the studied catchments. On a sub‐daily timescale, the difference in timing of maximum discharge during fair‐weather days (>80% maximum solar radiation and no precipitation) ranged between 7 and 12 h, which is attributed to differences between the presence and elevation of lakes among the catchments. The response of discharge to major precipitation events is discussed, where a delay of between 5 and 7 h is found for the catchments that do not contain lakes near the gauge.

Climate Variability and Trend Analyses of Rainfall and Temperature Data of Imphal, Manipur

Understanding local climate variability and change is necessary for improving future climate forecasts and also aids preparation of informed area specific climate mitigation and adaptation strategies. Climate change at local scale is best revealed by studying observed variabilities and trends in rainfall and temperature data through statistical techniques. Therefore, this study employed standard deviation and coefficient of variability and Mann-Kendall test and Sen slope determination non-parametric techniques to perform variability and trends analyses across multiple temporal scales on climate data obtained at Imphal (Tulihal) station. The results indicate prevalence of different patterns between rainfall and temperature trends. Except for the positive trends in the month May (2mm/yr) and in the pre-monsoon season (9.49mm/yr), no other discernable patterns in rainfall data were observed. Temperature trends, on the other hand, witnessed significant positive increase in maximum, minimum and mean values. For mean temperature, all months registered significant increasing trends. At the annual and seasonal scales also, maximum, minimum and mean temperatures have increased although with varying rates. It is noteworthy to mention that temperature change has occurred at two distinct phases; before 1993 slow warming and after 1993 rapid warming. Temporal distribution of annual mean temperature captures this pattern more vividly as warming rate before 1993 was less than 0.01 compared to 0.450c/year in the latter phase. Overall, it can be said that rainfall has higher variability with very little or no pattern but temperature distribution suggests existence of strong trends in the observed data.

Influence of El Niño 2015/2016 on Climate Variability and Production of Main Crops in Langkat Regency

El Niño Southern Oscillation (ENSO) is a global phenomenon that drives local and regional climate variability. It also affects various sectors in daily life, including agriculture. Influence of El Niño is well documented in literatures and generally it gives detrimental effects on agriculture. But, our understanding on local impact to main crops in Langkat Regency, North Sumatra is limited. This study explored the influence of the 2015/16 El Niño in Langkat Regency particularly on local climate variability, and production of on rice, corn, and soybean. We used daily climate data for 1981-2016 combined with agricultural production for 2010-2016. The onset of rainy season was determined using climate data, and we divided the analysis based on the seasonal zone (ZOM). Then we statistically compared agricultural production of each main crops (rice, corn, soybean) annually to the annual mean production for 2010-2016. The results showed that El Niño shorten a wet season in 2015/16 for all ZOMs, with a decreased rainfall between 7% to 30% compared to the normal year. In contrast, agricultural production had risen for 6%-16% due to human interventions during El Niño period. The interventions were comprised of two activities: the use of climate information for agricultural management and expansion of planting area. The findings suggested that climate information will be benefit to society when it is properly used.

Latitudinal pattern of the thermal sensitivity of running speed in the endemic lizard Liolaemus multimaculatus.

Physiological performance in lizards may be affected by climate across latitudinal or altitudinal gradients. In the coastal dune barriers in central-eastern Argentina, the annual maximum environmental temperature decreases up to 2°C from low to high latitudes, while the mean relative humidity of the air decreases from 50% to 25%. Liolaemus multimaculatus, a lizard in the family Liolaemidae, is restricted to these coastal dunes. We investigated the locomotor performance of the species at 6 different sites distributed throughout its range in these dune barriers. We inquired whether locomotor performance metrics were sensitive to the thermal regime attributable to latitude. The thermal performance breadth increased from 7% to 82% with latitude, due to a decrease in its critical thermal minimum of up to 5°C at higher latitudes. Lizards from high latitude sites showed a thermal optimum, that is, the body temperature at which maximum speed is achieved, up to 4°C lower than that of lizards from the low latitude. At relatively low temperatures, the maximum running speed of high-latitude individuals was faster than that of low-latitude ones. Thermal parameters of locomotor performance were labile, decreasing as a function of latitude. These results show populations of L. multimaculatus adjust thermal physiology to cope with local climatic variations. This suggests that thermal sensitivity responds to the magnitude of latitudinal fluctuations in environmental temperature.

Association between climatic factors and respiratory syncytial virus detection rates in Cheonan, Korea.

The use of big data may facilitate the recognition and interpretation of causal relationships between disease occurrence and climatic variables. This study examined the effects of various climatic variables on the seasonal epidemiology of respiratory syncytial virus (RSV) infections in the temperate climate of Korea. Trends in RSV detection were analyzed using 9010 samples tested between January 1, 2012, and December 31, 2018, at Dankook University Hospital in Cheonan, Korea. Seasonal patterns in RSV detection frequency were compared with local climatic variables during the same period. RSV detection rate of 12.8% (n = 1150/9010) was observed, which was higher for RSV-A (7.1%) than RSV-B (5.8%) and RSV-A and RSV-B alternated each year. Children < 1 year exhibited high infection rates with RSV-A (68.5%) and RSV-B (58.7%). RSV-A and RSV-B infection rates in children under 9 years old were 96.2% and 92.1%, respectively. RSV had a significant relationship with several climatic factors. Air temperature, wind chill temperature, and particulate matter concentration were lower on days with a higher frequency of RSV detection. In contrast, atmospheric pressure was higher on days with lower RSV detection. Although the detection rates for RSV-A and RSV-B increased on days with lower air temperatures, those for RSV-B also increased on days with lower wind chill temperatures. Our findings suggest that climatic variables affect the RSV detection rate among children under 10 years of age. The present data may help predict the time when prevention strategies may be the most effective.

Spatiotemporal dynamics of dengue in Colombia in relation to the combined effects of local climate and ENSO

Dengue virus (DENV) is an endemic disease in the hot and humid low-lands of Colombia. We characterize the association of monthly series of dengue cases with indices of El Niño/Southern Oscillation (ENSO) at the tropical Pacific and local climatic variables in Colombia during the period 2007-2017 at different temporal and spatial scales. For estimation purposes, we use lagged cross-correlations (Pearson test), cross-wavelet analysis (wavelet cross spectrum, and wavelet coherence), as well as a novel nonlinear causality method, PCMCI, that allows identifying common causal drivers and links among high dimensional simultaneous and time-lagged variables. Our results evidence the strong association of DENV cases in Colombia with ENSO indices and with local temperature and rainfall. El Niño (La Niña) phenomenon is related to an increase (decrease) of dengue cases nationally and in most regions and departments, with maximum correlations occurring at shorter time lags in the Pacific and Andes regions, closer to the Pacific Ocean. This association is mainly explained by the ENSO-driven increase in temperature and decrease in rainfall, especially in the Andes and Pacific regions. The influence of ENSO is not stationary, given the reduction of DENV cases since 2005, and that local climate variables vary in space and time, which prevents to extrapolate results from one region to another. The association between DENV and ENSO varies at national and regional scales when data are disaggregated by seasons, being stronger in DJF and weaker in SON. Overall, the Pacific and Andes regions control the relationship between dengue dynamics and ENSO at national scale. Cross-wavelet analysis indicates that the ENSO-DENV relation in Colombia exhibits a strong coherence in the 12 to 16-months frequency band, which implies the frequency locking between the annual cycle and the interannual (ENSO) timescales. Results of nonlinear causality metrics reveal the complex concomitant effects of ENSO and local climate variables, while offering new insights to develop early warning systems for DENV in Colombia.

Responses of Soil Microbial Community and Enzyme Activities to Shrub Species Artemisia gmelinii in Relation to Varying Rainfall in a Semiarid Land, SW China

Widely distributed shrubs in drylands can locally alter soil physicochemical properties, which distinguish soil under plant canopy from soil outside the canopy. In the present study, we used a dominant shrub species Artemisia gmelinii in a semiarid land, SW China, to investigate the consequences of “shrub resource islands” for soil microbial communities and enzymatic activities. Such investigation was made at four sites that differed in rates of rainfall to examine how the consequences were altered by variation in the local climate. The results showed that A. gmelinii enhanced fungal abundance but did not influence bacterial abundance, resulting in higher total microbial abundance and fungal-to-bacterial ratio in under-canopy soil compared to outside-canopy soil. Microbial community composition also differed between the two soils, but this difference only occurred at sites of low rainfall. Redundancy analysis revealed that such composition was attributed to variation in soil water content, bulk density, and total phosphorus as a result of shrub canopy and varying rates of rainfall. Activities of hydrolytic enzymes (β-1,4-glucosidase, β-1,4-N-acetylglucosaminidase, alkaline phosphatase, and leucine aminopeptidase) were higher in under-canopy soil than in outside-canopy soil, among which C-acquisition enzyme, β-1,4-glucosidase, and P-acquisition enzyme, alkaline phosphatase, were also higher in the soil of high rainfall. The overall pattern of enzyme activities did not show differences between under- and outside-canopy soils, but it separated the sites of high rate from that of low rates of rainfall. This pattern was primarily driven by variation in soil physicochemical properties rather than variation in soil microbial community, suggesting that the distribution pattern of enzyme activities may be more sensitive to variation in rainfall than to shrub canopy. In conclusion, our study shows that shrub species A. gmelinii can shift the soil microbial community to be fungal-dominant and increase hydrolytic enzyme activities, and such effect may depend on local climatic variation, for example, rainfall changes in the semiarid land. The findings of this study highlight the important roles of shrub vegetation in soil biological functions and the sensitivity of such roles to climatic variation in semiarid ecosystems.

Patterns of abundance reveal evidence of translocation and climate effects on Houbara bustard population recovery

AbstractPopulation reinforcement, through translocations of individuals, aims to restore populations of threatened species. The increase in population size or geographic distribution is often used as positive facts when assessing the recovery of a species, making abundance monitoring a major criterion. Based on 8‐year monitoring of a reinforced population of North African Houbara bustard (Chlamydotis undulata undulata), over an area of 50 170 km² in the eastern region of Morocco, we assessed the success of management actions by assessing spatial and temporal variation in abundance as well as the factors driving this variation. We used count data to estimate and spatialize population abundance. We then assessed environmental (climate) and management covariates (release effort and hunting management) associated with temporal and spatial variation in abundance. The overall estimate of abundance in the study area was 16 918 individuals (95% CI = 13 629–21 027) over our study period, with strong variation between years (range = 10 409–32 401). Our results highlighted strong spatial heterogeneity over the study area, linked to spatial variation in local climate and management conditions. Local abundances were negatively associated with local temperature, were higher in hunting than in non‐hunting areas, and were positively influenced by the number of birds released around the focal point. In addition to describing the spatio‐temporal variation in the abundance of the species on a large scale, we estimated two major proxies of its conservation status: population size and population trend. The determination of these proxies and the comparison with the counterfactual state of the species confirms the beneficial impact of the restoration and protection program on the dynamics of the North African Houbara bustard, while underlining the dependence of these dynamics on ongoing management.

Predictive assessment from ANN and MLR models to optimize the ideal evaporative/hybrid cooler based on experimental observations

Single-stage evaporative coolers like a direct evaporative cooler (DEC) and indirect evaporative cooler (IEC) are not versatile in their applicability in diverse climatic conditions due to their dependency on local climatic variation. To overcome this, an indigenously designed three-stage cooling system capable of operating in single-stage modes like DEC, IEC, and direct expansion (DX), and multi-stage modes like IEC-DEC, DEC-DX, and IEC-DEC-DX is developed. Detailed energetic and exergetic investigations are conducted based on experimental data acquired from 20th-26th of each month from April to July 2019. The thermodynamic analyses lead to optimizing the ideal cooling system for tropical climate through the development and comparison of artificial neural network (ANN) and multiple linear regression (MLR) models by predicting the wet-bulb effectiveness (ε), coefficient of performance (COP), and exergy efficiency (ηex). The input parameters for the predictive models include ambient temperature, ambient relative humidity, conditioned air temperature, and corresponding relative humidity. Based on the predictions, it can be concluded that the ANN is superior to the MLR method for performance prediction, with a minimum mean square error. Although the IEC-DEC is observed ideal for tropical climate due to higher cooling capacity and COP in extreme summer, the efficacy of IEC-DEC-DX cannot be ignored for its all-weather competency. The ANN models predict thermodynamic performance parameters of proposed coolers within the error limit of ±10%.