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Study areaThe study was carried out at the University of Dodoma (UDOM) and specifically at College of Natural and Mathematical Sciences (CNMS) and College of Education (COED) (Fig. 1). These two sites were considered because they have both afforested and non-afforested areas. Furthermore, unlike other places where afforestation is uncoordinated, the selected study area has proper management and records for the afforestation program that is taking place. The study area is located at latitude of 6° 57´ and 3° 82´ and longitudinal of 36° 26´ and 35° 26´. Its elevation is estimated to be 1120 m above the sea level. The site is semi-arid area dominated by sandy loam soil classified as Oxisol. The average annual rainfall of the areas is 447 mm. Temperatures vary depending on the season, with average minimum and maximum of (18^circ{rm C}) and 32 (^circ{rm C}) respectively.Figure 1Map showing the study area within the University of Dodoma (Created using QGIS 3.28.0 Firenze version, 2022). Note: CNMS-College of natural and mathematical science, CHS-College of humanities and social science, CIVE- College of informatic and virtual education, COED-College of Education.Full size imageThe bush is leafless and dry during the dry season, but comes to life during the rainy season, when the entire countryside turns a vibrant green19,20 The remaining land is covered in woodlands, with the highest concentrations in hills (URT 2014). The vegetation consists of dry savanna shrub-thicket areas with scattered trees and grassland patches interrupted by trees and shrubs.Study design on abundance and diversity of lizardsData on lizard abundance and diversity were collected at two sites, namely the CNMS and another site located at COED. These areas were purposely selected because the afforestation program is taking place. In the selected areas, trees have been planted for the past three years, which are 2019–2021. More effort is being made to plant more trees. Also, the areas have natural vegetation characterized by thickets, shrubs, and nature trees with species as described above in the study area. This makes the areas ideal for making comparisons between the afforested and un-afforested areas. In each site, two blocks were established, in which one block consisted of an afforested area while the other block was a non-afforested area.Data collectionDocumentation of planted tree speciesThe plants observed in the study areas were recorded. In addition to that, we worked with the restoration team, which provided the list of tree species that are grown in those study areas. Secondary data was collected from the restoration team regarding the tree species and how much has been planted in the last 5 years in the study areas.Sampling of lizard for abundance and diversity determinationPitfall trapsEach block had a size of 60 m by 60 m (2600 m2). In each block, two transects were established, each with a length of 60 m and a spacing of 20 m. In each transect, 4 points were identified, whereby 10 pitfall traps of 5 L each were set at an interval of 12 m. This makes 40 pitfall traps and eight walking transects. Emptying was performed every morning for 10 consecutive days in each pitfall. Thus, a total of 800 samples were collected from pitfall traps, with 400 samples being collected at each site.Direct searchingGeneral direct searching involving time-constrained observation was also used to collect data on the lizards found in the study area. Time constrained searches were conducted as an opportunistic means of finding animals hiding under cover and flushing them as the observer approached. Searching was conducted in an area of 20 m × 20 m at each sampling point where pitfalls were set. Searching was performed by an individual who is an ecologist and is an expert in reptiles for 10 min, 3 times a day for 10 days (n = 240). To ensure consistency, the same individual was employed in searching for each sampling point.At each site, the observed lizards were identified by their numbers and habitats. Photographs of captured or observed animals were taken to aid in identification. In addition, human activities such as cultivation, roads, tree cutting, building, and distance from roads and buildings, were recorded. Furthermore, more physical structures like rocks and distances from rocks were recorded. Identification of species of lizards was performed using a guide book for east African reptiles21.Sampling and interview for the assessment of awareness of the importance of afforestationA cross-sectional survey using a semi-structured questionnaire was used to collect data from undergraduate students in four colleges, which are CNMS, COED, CHSS, and CIVE. The respondents were selected randomly from each college. These students were selected based on their familiarity with the areas that are anticipated to see what is taking place within the University of Dodoma. It was anticipated that awareness would vary by college because the programs offered differed. For example, it was predicted that students from CNMS would be more aware than others because they have programs and courses that teach conservation, restoration, and afforestation knowledge. Both genders were included in the survey. A total of 394 interviewees were recruited; 100 participants were from CHSS, 103 from CIVE, 101 from CNMS, and 90 from COED. The questionnaire consisted of both closed and open-ended questions. The questions consisted of information on the demographic structure of students and their awareness of the afforestation program. Concerning awareness, the questions focused on their understanding of afforestation, their participation, and other stakeholders involved in the program.Some questions had to be ranked from 1 to 5, with the answers classified as very high, high, moderate, low, and very low if they scored 5, 4, 3, 2, and 1, respectively. The questions were designed to elicit responses from respondents regarding their knowledge of the ongoing afforestation program. In addition, information on the program’s participants and their level of involvement was requested.Human ethical guideline statementAll methods were carried out in accordance with relevant guidelines and regulations.Ethical approval and consent to participateThe ethics committee of University of Dodoma granted ethical approval for this study, with reference number MA.84/261/02.Informed consentInformed consent was obtained from all participants included in the study. More

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Research site descriptionA 3-year stationary field experiment was conducted at the Yuanziqu experimental station of the Bayannur Academy of Agricultural and Animal Husbandry Sciences (40° 90′ N, 107° 17′ E), Linhe, Inner Mongolia, China, from 2019 to 2021. The site has a continental monsoon climate typical of the northern mid-temperate zone, with a mean annual temperature from 3.7  to  7.6 °C, and the potential evaporation is 2200–2400 mm15. The total precipitation during the wheat growth period (March–July) was 66 mm, 110 mm and 47 mm in 2019, 2020, and 2021, respectively. Daily air temperature and precipitation during the field trial period are presented in Fig. 1.Figure 1Daily maximum temperature, daily minimum temperature and precipitation during the growth period (March–July) of spring wheat from 2019 to 2021 in the field experiment at Linhe, Inner Mongolia, China.Full size imageThe soil at the experimental site is a silt loam. The major physical and chemical properties of the 0–20 cm soil layer at the experimental site in 2019 were as follows: a bulk density of 1.48 g cm−3, pH 8.3, organic matter content of 15.49 g kg−1, total N concentration of 1.20 g kg−1, nitrate (NO3− N) concentration of 3.98 mg N kg−1, Olsen-P concentration of 32.3 mg P kg−1 and available K concentration of 180.0 mg K kg−1.Experimental design and field managementA local popular spring wheat (Triticum aestivum L.) cultivar, Yongliang No. 4, was used in the trials. The sowing dates were 20 March, 16 March and 13 March in 2019, 2020 and 2021, respectively; the harvest dates were 15 July, 15 July and 5 July in 2019, 2020 and 2021, respectively. A total of 375 kg ha−1 wheat seeds were sown at a depth of 5 cm.Five fertilization treatments were set in the three consecutive experimental years, including the control (CK), farmer practice (FP) and three balanced fertilization treatments (BF1, BF2 and BF3), as presented in Table 1. The P and K fertilizers as single superphosphate and K2SO4 were basal dressed, respectively. Both basal- and top-dressing of N fertilizer as urea were applied as shown in the research program. The basal applications occurred during sowing, and the remaining N fertilizer was top-dressed at the tillering stage (Table 1). The experimental plot was 10 m × 7 m with 13 cm row spacing and a buffer zone of 1 m between plots. The plots were laid out in a completely randomized block design with three replications.Table 1 Fertilization regimes of the different treatments in the 2019–2021 field trial.Full size tableEvery plot was ridged around its border to ensure the uniformity of irrigation. Flood irrigation from Yellow River water was performed according to the local policy and farmer practices. Irrigation water (30 mm) was applied at the tillering, jointing, heading and grain filling stages of spring wheat in 2019–2021. Disease, weed, and pest control, as well as other management, were performed according to local standard methods.Sampling and sample analysisThree 50 cm-long rows of spring wheat plants were selected randomly and pulled from each plot, from which 10 large, middle and small seedlings were picked out during each sampling effort. Then, the roots were cut off from the junction between the root and the stem, two plant parts (leaves and stems) before the heading stage, three plant parts (leaves, stems and spikes) at the heading stage, and four plant parts (leaves, stems, glumes and grains) at the grain filling stages and maturity were separated and pooled. The samples were dried for 30 min at 105 °C and then at 80 °C in an oven (DHG-9070A, China) until they reached a constant weight; the dry weight was then measured.The N concentrations in leaves, stems, spikes and grains of spring wheat were measured with three replications depending on the crop stage, following the Kjeldahl procedure using an element analyzer (Vario El cube, Elementar, Germany).Three soil cores containing 0–100 cm of soil were taken from each plot using an auger at the harvest of spring wheat each year. The soil samples of each 20 cm layer were collected separately and sealed immediately in a marked plastic bag. The extracts were immediately measured for nitrate-N concentration as described by Dai et al. (2015) with a continuous flow analyzer (SKALAR SAN++, Netherlands)16. The soil nitrate-N concentration was expressed on the basis of the oven-dried soil.Grain yield was evaluated at maturity by selecting two 2 m2 (avoiding border rows) randomly and harvested. A fresh weight of ∼ 1 kg of grain from each plot was weighed in the field, and the water content from each plot was oven dried for the calculation. The actual yield was adjusted by a grain water content of 13%17. Grains per spike, 1000-grain weight and spike number were determined at three 50-cm sites sampled randomly from each plot.Calculation methodsTo clarify the effect of nitrate residue in the soil under balanced fertilization, the amount of soil nitrate-N (AN, kg N ha−1) in each layer was expressed as:$${text{AN}} = left( {{text{Ti}};*;{text{Di}};*;{text{Ci}}} right)/10$$
where Ti is the soil layer thickness (cm), Di is the soil bulk density (g cm−3), Ci is the soil nitrate concentration (mg N kg−1) of the corresponding layer, and 10 is the conversion coefficient16. The AN of 0–20, 20–40, 40–60, 60–80 and 80–100 cm soil layers were recorded and measured, respectively.Nitrogen accumulation in the vegetative organs and their distribution into the grain were investigated. Based on the dry weight and corresponding measured N concentration in the different organs, apparent N translocation (TA, kg ha−1) and apparent N translocation efficiency (TR, %) were calculated as proposed by Cox et al.18 as follows:$$begin{aligned} {text{TA}} & {text{ = H}}_{{text{N}}} – {text{M}}_{{text{N}}} \ {text{TR}} & = {text{TA/H}}_{{text{N}}} *100 \ end{aligned}$$
where HN is the N assimilation in leaves or stems prior to anthesis (kg ha−1), MN is the N assimilation in leaves or stems at maturity (kg ha−1).Two parameters of nitrogen use efficiency of spring wheat, nitrogen fertilizer partial productivity (PFPN, kg/kg) and agronomic nitrogen efficiency (NAEN, kg kg−1) were determined using the following formulas:$$begin{aligned} {text{PFP}}_{{text{N}}} & = {text{ Y}}_{N; , fertilizer} /{text{N}}_{rate} \ {text{NAE}}_{{text{N}}} & = , left( {{text{Y}}_{{N;fertilizer , {-}}} {text{Y}}_{blank} } right)/{text{N}}_{rate} \ end{aligned}$$
where YN fertilizer is the grain yield of the plot with dressed N fertilizer (kg ha−1), Yblank is the grain yield of the plot without dressed N fertilizer (kg ha−1), and Nrate is the N rate of the dressed fertilizer plot (kg ha−1). Three measurements for each treatment was recorded and calculated.Two key indicators were chosen to evaluate the risk of N losses as described by Li et al. (2020)7, including N surplus (kg N per hectare per year, Nsur) and N input (kg N per hectare per year, Ninput). The N surplus was used to evaluate the risk of N losses and the N input to guide farmers’ fertilization practices directly. The detailed calculation is as follows:$$begin{aligned} {text{N}}_{{{text{sur}}}} & = {text{ N}}_{{{text{fer}}}} + {text{ N}}_{{{text{dep}}}} + {text{ N}}_{{{text{fix}}}} – {text{ N}}_{{{text{har}}}} \ {text{N}}_{{{text{input}}}} & = {text{ N}}_{{{text{har}}}} + {text{ N}}_{{{text{sur}}}} + {text{ soil N change in stock }};;;( approx 0{text{ in long run}}) \ end{aligned}$$
where Nfer, Ndep and Nfix represent N from fertilizer, atmospheric deposition and biological fixed N, respectively. Seed N was negligible as it was present in a very small amount compared to the fertilization input19. The total N deposition of spring wheat field and biological N fixation were adopted according to Li et al. (2020). Nhar refers to the harvested N in spring wheat.Economic analysisThe inputs into local spring wheat production included chemical fertilizer, irrigated water, agricultural chemicals, seed, mechanical effort and labor costs, while income was obtained from the grain and wheat straw. The net income was determined from the difference between the total output and total input. The irrigated water, agricultural chemicals, seed, mechanical effort and labor costs were the same for the different treatments. The prices of the input and output materials were determined according to the average local market prices, and fluctuations were not considered among years.Statistical analysesThe results were analyzed using SPSS software (version 19.0; SPSS Inc., Chicago, IL, USA). Analysis of variance (ANOVA) and the least significant difference (LSD) test were used, and a P value of 0.05 was considered significant. More

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