Land use affects total dissolved nitrogen and nitrate concentrations in tropical montane streams in Kenya

Changing climate intensifies downstream eutrophication by enhancing nitrogen availability from tropical forests

The contribution of diffuse nutrient exports from forests to downstream water bodies is significant owing to their extensive spatial distribution across watersheds. However, the intricacies of coupling mechanism between diffuse nutrient exports and meteorological factors driving downstream eutrophication remain poorly understood. Multiple methods involving field sampling, laboratory analysis, and model simulation were utilized to investigate the impact of diffuse nutrient exports from tropical forests on chlorophyll a concentration dynamic in the downstream reservoir. A strong positive correlation was observed between air temperature and chlorophyll a concentration, indicating the direct influence of climatic factors on microalgal biomass. The significant positive linear relationship was also observed between diffuse nitrate exports and chlorophyll a concentration, with a regression coefficient of 0.36 (P < 0.001), underscoring the role of nitrogen inputs in stimulating microalgal growth. The interplay between diffuse nitrate exports and meteorological factors was shown to regulate chlorophyll a concentration fluctuation. Additionally, the structural equation model revealed that increasing temperature and decreasing precipitation could elevate chlorophyll a concentration by enhancing nitrogen availability. Monte Carlo simulation results further revealed that temperature and precipitation were the most influential factors affecting chlorophyll a concentration during dry and rainy seasons, with sensitivity values of 0.94 and - 0.76, respectively. Notably, the eutrophication status was projected to deteriorate from light to moderate under diminishing precipitation conditions. These findings underscore the urgency of addressing eutrophication risks in reservoirs surrounded by tropical forests and the implementation of effective nitrate mitigation strategies is imperative, which offers theoretical guidance for the management of eutrophic water restoration within tropical rainforest regions under changing climate conditions.

The state of nitrogen in rivers and streams across sub-Saharan Africa

The nutrient status of rivers and streams is less researched in sub-Saharan Africa than in many other inhabited regions of the world. Given the expected population growth, intensification of agriculture, increased pressure on natural ecosystems and projected climate change in sub-Saharan Africa, it is crucial to quantify and understand drivers behind spatiotemporal patterns of nitrogen concentrations and loads in rivers and streams. Such knowledge can support sustainable management of water resources with the goal to provide clean water, create and maintain healthy ecosystems and prevent excessive pollution of water resources with nitrogen compounds, as is found in large parts of North America, Europe and Asia. This review provides a synthesis of the current available data from peer-reviewed literature (n = 243) on particulate and dissolved nitrogen in rivers and streams in sub-Saharan Africa, looking into seasonal and land cover-related differences. The review shows that data on nitrogen concentrations in rivers and streams is available for 32 out of the 48 countries (67 %) in sub-Saharan Africa, highlighting large data gaps given the size of the region. Differences in nitrogen concentrations between land cover types are reported, with highest median total nitrogen (3.9 mg N L-1) and nitrate (1.2 mg N L-1) concentrations observed at sites characterised by settlement and industry. In contrast, natural land cover types, like forest, have higher median (N:P) ratios (> 14.6) than cropland and urban areas (< 12.0). The analysis of paired samples from dry and wet seasons reveals varying effects of seasonality on the concentration of different nitrogen compounds between land cover types. However, the processes driving these spatiotemporal differences are still poorly understood. These findings highlight the need for a targeted research agenda for Africa to advance our understanding of the role of rivers and streams in nitrogen cycling in different ecosystems and their interaction with anthropogenic and natural drivers of change.

The detrimental effect of rainforest conversion to rubber plantations on soil dissolved organic carbon and C: N stoichiometry, mediated by altered soil biogeochemistry

Rainforest conversion into rubber (Hevea brasiliensis) plantations (RP) alters global carbon cycling and contributes to climate change. However, the impact of this widespread tropical land use change on various elements of the carbon cycle is poorly understood. Here, we aimed to investigate the impact of rainforest conversion into RP on soil-dissolved organic carbon (DOC), one of the most mobile organic matter (OM) in the terrestrial ecosystem that causes the transformation and migration of C. We also explored the underlying edaphic factors regulating soil DOC changes. Our study sites were rubber monoculture, mixed-rubber plantations (H. brasiliensis, Ficus langkokensis, and Actinodaphne henryi), and a reference rainforest. We found that soil DOC concentration was 150-200% higher in RP than in rainforests, with an unchanged pattern across the seasons (dry and rainy) and plantation type. These results were concomitant with degradation in main soil properties, markedly including lower pH, electrical conductivity, SOC, available nitrogen, available phosphorus, total nitrogen (TN), and total phosphorus (TP), following the RP establishment and explicitly having a significant negative correlation with DOC. Our fitted structure equation model (SEM) highlights that RP caused accelerated DOC production and a higher DOC/DN ratio by decreasing SOC (38.5%) and nutrients (TN and TP). Further, the SEM revealed a significant negative correlation between microbial biomass C (MBC) and N (MBN) and the DOC/DN ratio, implying limited microbial degradation of DOC under RP. This is further supported by our findings of 81.1% lower MBC per unit DOC and 37.1% lower MBN per unit DN under RP compared to rainforests, indicating poor transformation of DOC to microbial biomass under RP. Collectively, our findings suggest that RP with high nutrient demands and altered soil properties lead to increased leaching of DOC due to its limited utilization by microbes. These findings underscore the importance of robust and sustainable soil management (such as optimizing plant density and legume intercropping) in RP to improve soil health and minimize DOC leaching and its potential environmental consequences.

Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia

In tropical regions, shifting from forests and traditional agroforestry to intensive plantations generates conflicts between human welfare (farmers' demands and societal needs) and environmental protection. Achieving sustainability in this transformation will inevitably involve trade-offs between multiple ecological and socioeconomic functions. To address these trade-offs, our study used a new methodological approach allowing the identification of transformation scenarios, including theoretical landscape compositions that satisfy multiple ecological functions (i.e., structural complexity, microclimatic conditions, organic carbon in plant biomass, soil organic carbon and nutrient leaching losses), and farmers needs (i.e., labor and input requirements, total income to land, and return to land and labor) while accounting for the uncertain provision of these functions and having an actual potential for adoption by farmers. We combined a robust, multi-objective optimization approach with an iterative search algorithm allowing the identification of ecological and socioeconomic functions that best explain current land-use decisions. The model then optimized the theoretical land-use composition that satisfied multiple ecological and socioeconomic functions. Between these ends, we simulated transformation scenarios reflecting the transition from current land-use composition towards a normative multifunctional optimum. These transformation scenarios involve increasing the number of optimized socioeconomic or ecological functions, leading to higher functional richness (i.e., number of functions). We applied this method to smallholder farms in the Jambi Province, Indonesia, where traditional rubber agroforestry, rubber plantations, and oil palm plantations are the main land-use systems. Given the currently practiced land-use systems, our study revealed short-term returns to land as the principal factor in explaining current land-use decisions. Fostering an alternative composition that satisfies additional socioeconomic functions would require minor changes ("low-hanging fruits"). However, satisfying even a single ecological indicator (e.g., reduction of nutrient leaching losses) would demand substantial changes in the current land-use composition ("moonshot"). This would inevitably lead to a profit decline, underscoring the need for incentives if the societal goal is to establish multifunctional agricultural landscapes. With many oil palm plantations nearing the end of their production cycles in the Jambi province, there is a unique window of opportunity to transform agricultural landscapes.

Impact of climate change and land cover dynamics on nitrate transport to surface waters

The study investigated the impact of climate and land cover change on water quality. The novel contribution of the study was to investigate the individual and combined impacts of climate and land cover change on water quality with high spatial and temporal resolution in a basin in Turkey. The global circulation model MPI-ESM-MR was dynamically downscaled to 10-km resolution under the RCP8.5 emission scenario. The Soil and Water Assessment Tool (SWAT) was used to model stream flow and nitrate loads. The land cover model outputs that were produced by the Land Change Modeler (LCM) were used for these simulation studies. Results revealed that decreasing precipitation intensity driven by climate change could significantly reduce nitrate transport to surface waters. In the 2075-2100 period, nitrate-nitrogen (NO3-N) loads transported to surface water decreased by more than 75%. Furthermore, the transition predominantly from forestry to pastoral farming systems increased loads by about 6%. The study results indicated that fine-resolution land use and climate data lead to better model performance. Environmental managers can also benefit greatly from the LCM-based forecast of land use changes and the SWAT model's attribution of changes in water quality to land use changes.

Identifying the impact of land use land cover change on streamflow and nitrate load following modeling approach: a case study in the upstream Dong Nai River basin, Vietnam

Tri An Reservoir is a vital source of water for agriculture, industry, hydropower, and public usage in Southern Vietnam. Due to human activities, water eutrophication has become a serious problem in recent decades. This study investigated for the first time the impact of land use and land cover (LULC) change on streamflow and nitrate load from the upstream Dong Nai River basin, which is the largest watershed of the reservoir. The study utilized several LULC scenarios, including LULC 2000, 2010, and 2020. The SWAT model was applied to model the watershed during the period 1997-2009. Results showed that the hydrological model performed satisfactorily based on the Nash-Sutcliffe efficiency (NSE) coefficient, the root mean square error observations standard deviation ratio (RSR), and the percent bias (PBIAS). The average simulated values of monthly streamflow and nitrate load were 453.7, 450.0, 446.7 m³/s and 17,699.43, 17,869.13, 17,590.81 tonnes for the LULC 2000, 2010, and 2020 scenarios, respectively. There were no significant differences in streamflow and nitrate load at the basin level under the different LULC scenarios. However, when looking at the subbasin level, there were differences in nitrate load among the scenarios. This suggests that the impacts of LULC on nitrate load may be more pronounced at smaller scales. Overall, our finding underscores the importance of modeling techniques in predicting the impacts of LULC change on streamflow and water quality, which can ultimately aid in the sustainable management of water resources.

Organic Matter Decomposition in River Ecosystems: Microbial Interactions Influenced by Total Nitrogen and Temperature in River Water

Microbes contribute to the organic matter decomposition (OMD) in river ecosystems. This study considers two aspects of OMD in river ecosystems which have not been examined in scientific studies previously, and these are the microbial interactions in OMD and the influence of environmental factors on microbial interactions. Cotton strip (CS), as a substitute for organic matter, was introduced to Luanhe River Basin in China. The results of CS assay, microbial sequencing, and redundancy analysis (RDA) showed that CS selectively enriched bacterial and fungal groups related to cellulose decomposition, achieving cotton strip decomposition (CSD). Bacterial phylum Proteobacteria and fungal phyla Rozellomycota and Ascomycota were the dominant groups associated with CSD. Network analysis and Mantel test results indicated that bacteria and fungi on CS cooperatively formed an interaction network to achieve the CSD. In the network, modules 2 and 4 were significantly positively associated with CSD, which were considered as the key modules in this study. The key modules were mainly composed of phyla Proteobacteria and Ascomycota, indicating that microbes in key modules were the effective decomposers of CS. Although keystone taxa were not directly associated with CSD, they may regulate the genera in key modules to achieve the CSD, since some keystone taxa were linked with the microbial genera associated with CSD in the key modules. Total nitrogen (TN) and temperature in water were the dominant environmental factors positively influenced CSD. The key modules 2 and 4 were positively influenced by water temperature and TN in water, respectively, and two keystone taxa were positively associated with TN. This profoundly revealed that water temperature and TN influenced the OMD through acting on the keystone taxa and key modules in microbial interactions. The research findings help us to understand the microbial interactions influenced by environmental factors in OMD in river ecosystems.

Exploring the Relationship between Ecosystem Services under Different Socio-Economic Driving Degrees

The large-scale transformation of natural ecosystems to socio-economic development land types under human activities was a primary reason for the decline of regional ecosystem services. It is a key issue for regional ecosystem planning and management to reveal the relationship between ecosystem services of different land use types under different socio-economic driving degrees. However, the current related research was not in-depth. Based on the land use data of Wuhan City in 1980, 1990, 2000, 2010, and 2020, this study classified land use into three categories according to the different degrees of human activities on natural ecosystem development: the land use of a natural ecosystem (LUNE), the land use of a productive ecosystem (LUPE), and the land use of a socio-economic system (LUSE). The InVEST model was used to simulate five ecosystem services (grain yield, water yield, carbon storage, habitat quality, and water purification), and the spatio-temporal distribution and functional transformation of the three land use types were analyzed. Results showed that with the intensified urban expansion in Wuhan, the LUSE types increased to 2.7 times that of the original. However, the natural land types basically maintained a stable area, coupling with the large-scale transformation between the LUPE and LUSE types. Land use change resulted in significant spatial changes of five ecosystem services, especially carbon storage and habitat quality. The correlation analysis indicated that the five kinds of ecosystem services mainly showed a synergistic relationship, meanwhile the LUSE type denoted the most significant correlation with ecosystem services among these three category types. This study indicated that besides the protection of natural ecosystems, the LUSE type would become the key land use type in the planning and management of improving regional ecological function.

Analysis of the influence paths of land use and landscape pattern on organic matter decomposition in river ecosystems: Focusing on microbial groups

Organic matter decomposition (OMD) is one of the important river ecosystem functions. Changes in land use and landscape pattern (LULP) have a serious influence on the OMD in neighboring river ecosystems. However, there is limited information on the influence paths of LULP on organic matter decomposition in river ecosystems. In this study, cotton strip (CS) as a substitute for investigating OMD, was introduced to the delineated catchments in Luanhe River Basin in China, meanwhile combining with remote sensing interpretation, water quality analysis, microbial sequencing, and redundancy analysis (RDA) to identify the dominant LULP metrics, water quality parameters, and microbial groups controlling the OMD. Then the structural equation models (SEMs) were used to connect these dominant controlling factors to track the influence paths of LULP on OMD in river ecosystems. RDA results indicated that construction land (CON), farmland (FAR) and landscape shape index (LSI) in LULP, total nitrogen (TN), chemical oxygen demand (COD) and pH in water quality, bacterial phyla Planctomycetes and Firmicutes, as well as fungal phyla Chytridiomycota and Basidiomycota were the dominant factors controlling the OMD (quantified by tensile strength loss (TSL) and respiration (RES)). These four microbial phyla contributed significantly to OMD. SEMs further proposed three paths to explain the mechanism of LULP influencing on OMD, which were CON - TN - Firmicutes - TSL, CON - TN - Chytridiomycota - RES, and FAR - COD - Chytridiomycota - TSL. CON promoted OMD mainly through enhancing TN content in river water to increase Firmicutes and Chytridiomycota. FAR increased Chytridiomycota by decreasing COD in river water, promoting OMD. These results will deepen our understanding of the influence of LULP on river ecosystem functions and provide valuable information for policymakers and managers to carry out watershed land planning and river management in the future.

Addressing Gender Inequities in Forest Science and Research

Forest research and professional workforces continue to be dominated by men, particularly at senior and management levels. In this review, we identify some of the historical and ongoing barriers to improved gender inclusion and suggest some solutions. We showcase a selection of women in forestry from different disciplines and parts of the globe to highlight a range of research being conducted by women in forests. Boosting gender equity in forest disciplines requires a variety of approaches across local, regional and global scales. It is also important to include intersectional analyses when identifying barriers for women in forestry, but enhanced equity, diversity and inclusion will improve outcomes for forest ecosystems and social values of forests, with potential additional economic benefits.

Effect of land use changes on non-carcinogenic health risks due to nitrate exposure to drinking groundwater

This study aimed to determine the effect of land-use changes on the non-carcinogenic health risk of nitrate ion exposure of underground drinking water resources in Shiraz (Iran). To this end, 175 chemical samples for the nitrate analysis were regularly taken from 35 drinking water wells of Shiraz from 2013 to 2017, and their results were zoned using GIS. Hazard quotient (HQ) induced by nitrate ion exposure was determined in four age groups: infants, children, adolescents, and adults. Area changes of four types of land-use, including residential, agricultural and green space, industrial, and bare land within a radius of 400 m of drinking water wells, were determined using the GIS and Google Earth software. Then, all data was imported to Matlab 2018 for statistical analysis. The results showed that mean nitrate concentration increased by 2.5 mg L^-1 from 2013 to 2017. According to the zoning map, 5 and 11.4% of the area in 2013 and 2017, respectively, exceeded the drinking water standard set by nitrate (i.e., 50 mg/L). Air temperature and precipitation variations also influenced nitrate concentrations and HQ changes (R_temperature = 0.67). Children's age group was the most vulnerable, and during the study period, this vulnerability was an increasing trend, so that the HQ from 0.93 in 2013 to 0.97 in 2017 has increased. The rate of land-use changes in agricultural, industrial, bare, and urban was -1.8%, 1.3%, -4.6%, and 2.1%, respectively, and the highest correlation was observed between HQ and Diff.l residential land use (R_infant = 0.55). According to the results, the most influential factor in HQ was air temperature (R = 0.66), and urban land-use change (R > 0.44). To sum up, this study's results showed that land-use changes, especially urban and residential development, significantly affect groundwater nitrate concentration and its degree of HQ. Moreover, increasing temperature and decreasing annual precipitation can also increase the severity of this risk.

Deep Nitrate Accumulation in a Highly Weathered Subtropical Critical Zone Depends on the Regolith Structure and Planting Year

Nitrate accumulated deep (>100 cm) in the regolith (soil and saprolite) threatens groundwater quality, but most studies focus only on nitrate nearer the surface (<100 cm). Surface soil management versus regolith interactions affect deep nitrate leaching, but their combined impact remains unclear. This study measured how deep nitrate accumulation was affected by crop practices including orchard/cropland planting years, regolith structure, and soil properties in highly weathered subtropical red soils. Deep nitrate storage varied from 43.6 to 1116.3 kg ha^-1. Regolith thickness was positively correlated with nitrate storage (R² = 0.43, p < 0.05). Reticulated red clay (110-838 cm) had 81% of the accumulated nitrate and overlapped with 79% of the nitrate accumulation layer. All of the nitrate accumulation parameters (except for peak depth (PD)) generally increased with the planting years. The difference in peak nitrate concentration (9.0-20.0 mg kg^-1) with planting year gradient (3-58 years) varied by 2.2 times, and the difference in nitrate storage (43.6-425.7 kg ha^-1) varied by 9.8 times. Texture and pH explain 41.6% of the variation in nitrate concentration. As soil management practices interact with deeper regolith to control the spatial pattern of nitrate accumulation, vulnerable regions could be identified to avoid high accumulation.

Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models

The prediction of nitrogen not only assists in monitoring the nitrogen concentration in streams but also helps in optimizing the usage of fertilizers in agricultural fields. A precise prediction model guarantees the delivering of better-quality water for human use, as the operations of various water treatment plants depend on the concentration of nitrogen in streams. Considering the stochastic nature and the various hydrological variables upon which nitrogen concentration depends, a predictive model should be efficient enough to account for all the complexities of nature in the prediction of nitrogen concentration. For two decades, artificial neural networks (ANNs) and other models (such as autoregressive integrated moving average (ARIMA) model, hybrid model, etc.), used for predicting different complex hydrological parameters, have proved efficient and accurate up to a certain extent. In this review paper, such prediction models, created for predicting nitrogen concentration, are critically analyzed, comparing their accuracy and input variables. Moreover, future research works aiming to predict nitrogen using advanced techniques and more reliable and appropriate input variables are also discussed.

Land use controls Kenyan riverine nitrate discharge into Lake Victoria - evidence from Nyando, Nzoia and Sondu Miriu river catchments

Nitrate (NO₃^-) sources and discharge were investigated using isotope and hydrochemical analyses in three river catchments draining Lake Victoria basin, Kenya. Hierarchical cluster analysis grouped Nyando, Nzoia and Sondu Miriu River stations into clusters corresponding to major land use classes of the catchments. Mixed agriculture (MA) in Nyando showed higher NO₃^- compared to the other land uses. Nitrate levels obtained (0.1-11.6 mg L^-1) are higher than those reported in previous studies. Hydrochemistry support isotope data indicating that ammonium-based fertilizers and soil N were the major NO₃^- sources in tea dominated areas with average δ¹⁵N (6.5 ± 1.3 ‰), δ¹⁸O (6.7 ± 2.3 ‰) values. Manure/sewage were the main source in MA areas with average δ¹⁵N (8.4 ± 2.4 ‰), δ¹⁸O (7.8 ± 5.4 ‰) values. Sewage was the likely source in urban, residential & industrial areas recording average δ¹⁵N (10.0 ± 2.4 ‰), δ¹⁸O (6.9 ± 3.7 ‰) values. δ¹⁵N between land uses were significantly different (p < 0.0001) while δ¹⁸O were similar (p = 0.4). Seasonally, inorganic/organic fertilizers influenced river NO₃^- mostly in the wet cropping season. Lower NO₃^- concentrations observed in Nyando and Sondu Miriu during dry or start-wet season could be a result of in situ denitrification.

Diurnal Patterns in Solute Concentrations Measured with In Situ UV-Vis Sensors: Natural Fluctuations or Artefacts?

In situ spectrophotometers measuring in the UV-visible spectrum are increasingly used to collect high-resolution data on stream water quality. This provides the opportunity to investigate short-term solute dynamics, including diurnal cycling. This study reports unusual changes in diurnal patterns observed when such sensors were deployed in four tropical headwater streams in Kenya. The analysis of a 5-year dataset revealed sensor-specific diurnal patterns in nitrate and dissolved organic carbon concentrations and different patterns measured by different sensors when installed at the same site. To verify these patterns, a second mobile sensor was installed at three sites for more than 3 weeks. Agreement between the measurements performed by these sensors was higher for dissolved organic carbon (r > 0.98) than for nitrate (r = 0.43–0.81) at all sites. Higher concentrations and larger amplitudes generally led to higher agreement between patterns measured by the two sensors. However, changing the position or level of shading of the mobile sensor resulted in inconsistent changes in the patterns. The results of this study show that diurnal patterns measured with UV-Vis spectrophotometers should be interpreted with caution. Further work is required to understand how these measurements are influenced by environmental conditions and sensor-specific properties.

Intensification of dairy production can increase the GHG mitigation potential of the land use sector in East Africa

Sub-Saharan Africa (SSA) could face food shortages in the future because of its growing population. Agricultural expansion causes forest degradation in SSA through livestock grazing, reducing forest carbon (C) sinks and increasing greenhouse gas (GHG) emissions. Therefore, intensification should produce more food while reducing pressure on forests. This study assessed the potential for the dairy sector in Kenya to contribute to low-emissions development by exploring three feeding scenarios. The analyses used empirical spatially explicit data, and a simulation model to quantify milk production, agricultural emissions and forest C loss due to grazing. The scenarios explored improvements in forage quality (Fo), feed conservation (Fe) and concentrate supplementation (Co): FoCo fed high-quality Napier grass (Pennisetum purpureum), FeCo supplemented maize silage and FoFeCo a combination of Napier, silage and concentrates. Land shortages and forest C loss due to grazing were quantified with land requirements and feed availability around forests. All scenarios increased milk yields by 44%-51%, FoCo reduced GHG emission intensity from 2.4 ± 0.1 to 1.6 ± 0.1 kg CO₂ eq per kg milk, FeCo reduced it to 2.2 ± 0.1, whereas FoFeCo increased it to 2.7 ± 0.2 kg CO₂ eq per kg milk because of land use change emissions. Closing the yield gap of maize by increasing N fertilizer use reduced emission intensities by 17% due to reduced emissions from conversion of grazing land. FoCo was the only scenario that mitigated agricultural and forest emissions by reducing emission intensity by 33% and overall emissions by 2.5% showing that intensification of dairy in a low-income country can increase milk yields without increasing emissions. There are, however, risks of C leakage if agricultural and forest policies are not aligned leading to loss of forest to produce concentrates. This approach will aid the assessment of the climate-smartness of livestock production practices at the national level in East Africa.

Coupled effects of climate variability and land use pattern on surface water quality: An elasticity perspective and watershed health indicators

Understanding the coupled effects of climate variability and land use on riverine nitrogen is essential for watershed management. The climate-water relationships for ammonium (NH₄-N) and nitrate (NO₃-N) were determined by an elasticity approach and then the watershed health index was estimated using the reliability, resilience, and vulnerability framework. These methods were applied to an in-situ monitoring dataset of N concentrations measured during 2010-2017 from nine sub-watersheds in the Jiulong River Watershed, China. The results showed that temperature and precipitation elasticity of NH₄-N and NO₃-N changed substantially among various land use patterns. The N concentrations were highly sensitive to extreme climate conditions, particularly at urban and agricultural sub-watersheds. The measure of risk indicators revealed that the watershed health index varied from good health to unhealthy status. Linear regression analysis was used to analyze the interactions among watershed characteristics, climate elasticity, and watershed health. Cropland and population had strong positive correlations with climate elasticity of NO₃-N. Forest and elevation had strong negative associations with climate elasticity of NO₃-N. Watershed health significantly declined with increasing proportion of cropland and population density. This study demonstrated that human-impacted watersheds were less healthy to unhealthy and tend to be more sensitive to climate variability than natural watersheds, which is useful for efforts aimed at improving watershed management.

Land Use, Not Stream Order, Controls N2O Concentration and Flux in the Upper Mara River Basin, Kenya

Anthropogenic activities have led to increases in nitrous oxide (N2O) emissions from river systems, but there are large uncertainties in estimates due to lack of data in tropical rivers and rapid increase in human activity. We assessed the effects of land use and river size on N2O flux and concentration in 46 stream sites in the Mara River, Kenya, during the transition from the wet (short rains) to dry season, November 2017 to January 2018. Flux estimates were similar to other studies in tropical and temperate systems, but in contrast to other studies, land use was more related to N2O concentration and flux than stream size. Agricultural stream sites had the highest fluxes (26.38 ± 5.37 N2O-N μg·m-2·hr-1) compared to both forest and livestock sites (5.66 ± 1.38 N2O-N μg·m-2·hr-1 and 6.95 ± 2.96 N2O-N μg·m-2·hr-1, respectively). N2O concentrations in forest and agriculture streams were positively correlated to stream carbon dioxide (CO2-C(aq)) but showed a negative correlation with dissolved organic carbon, and the dissolved organic carbon:dissolved inorganic nitrogen ratio. N2O concentration in the livestock sites had a negative relationship with CO2-C(aq) and a higher number of negative fluxes. We concluded that in-stream chemoautotrophic nitrification was likely the main biogeochemical process driving N2O production in agricultural and forest streams, whereas complete denitrification led to the consumption of N2O in the livestock stream sites. These results point to the need to better understand the relative importance of nitrification and denitrification in different habitats in producing N2O and for process-based studies.

Seasonal Fluxes of Dissolved Nutrients in Streams of Catchments Dominated by Swidden Agriculture in the Maya Forest of Belize, Central America

The biogeochemistry of nitrogen (N) and phosphorus (P) in tropical streams and rivers is strongly regulated by the pronounced seasonality of rainfall and associated changes in hydrology. Land use and land cover change (LULCC) can also be a dominant driver of changes in stream biogeochemistry yet responses are not fully understood and vary across different LULCC scenarios. We measured dissolved and total nitrogen (N) and phosphorus (P) concentrations in four tributary streams of the Temash River watershed in southern Belize, Central America. The dominant land use practice in each of the four study catchments was swidden agriculture. We documented a strong seasonal control on the export of nutrients from these study systems with daily N fluxes increasing approximately 10-fold during the onset of the rainy season. P fluxes increased almost 4-fold during the same time period. Comparisons with nutrient export coefficients from other tropical streams suggest that nutrient export in streams of the Temash River watershed is similar or slightly lower. Establishing improved understanding of the terrestrial and hydrologic controls of N and P transport across the terrestrial-aquatic boundary and developing a comprehensive nutrient budget that includes inputs and outputs associated with crop production is warranted in future work.

Effects of anthropogenic activities on long-term changes of nitrogen budget in a plain river network region: A case study in the Taihu Basin

Over recent decades, Taihu Lake, the third largest freshwater lake in China, has borne the brunt of intensive human activities. Non-point source pollutants and discharges of domestic wastewater are now the main cause of eutrophication. To control non-point source pollution, it is useful to have a good understanding of the spatial and temporal distribution of N (nitrogen). In this study, we applied Export Coefficient Model (ECM) and the Net Anthropogenic Nitrogen Inputs (NANI) method to estimate the N loads in the Taihu Basin at county scale since 1980. We found that N inputs and exports had increased from 6432 and 3170 kg N km^-2 yr^-1 in 1980 to 9722 and 4582 kg N km^-2 yr^-1 in 2010, respectively. The 151% increase of N inputs, but 144% increase of riverine N outputs suggested the more N was retained within the Taihu Basin. Both the population density and the urban areas were strongly correlated with N inputs and exports. Approximately 38% of the N inputs were exported in 2010, but only 19% were exported in 1980. This ratio illustrated that human activities, especially urbanization and population growth, have upset N budget in the Taihu Basin. This study supported by empirical models provides a case to demonstrate the N cascade in the Taihu Basin and can also be used to support decision making and to facilitate the development of measures to control N in the future.

Dynamics of soil microbial recovery from cropland to orchard along a 20-year chronosequence in a degraded karst ecosystem

The 'Grain for Green' project (GGP) is the largest ecological rehabilitation project in China. A large body of croplands has been abandoned or converted to shrubs or grasslands since 1999. Soil microbes are recognized as sensitive responders of environmental changes, therefore, they are considered as a key component of ecological rehabilitation. However, very limited field experiments have been conducted to investigate the responses of soil microorganisms to restoration projects, especially in karst regions of China. In order to evaluate the response of soil microbial community to ecological restoration, we determined soil microbial community composition by means of qPCR, PLFAs, and high-throughput amplicon sequencing following conversion of cropland to Chinese prickly ash (Zanthoxylum bungeanum Maxim) orchard (CP) along a 20-year chronosequence in a degraded karst ecosystem. Our results showed that soil nutrient contents significantly increased following cropland to CP conversion. qPCR results showed that the highest bacterial abundance was found in the 20-year CP, but bacterial abundance decreased during the first 5-year land-use conversion. Conversion of cropland to CP strongly impacted soil microbial community composition, despite the cropland sites having a long cultivation history (>50 years). However, soil bacterial diversity remained unchanged within a 20-year land-use conversion. Actinobacteria, Proteobacteria, and Acidobacteria were the main bacterial phyla in all land-use sites. In particular, various members of Actinobacteria (e.g., Solirubrobacteraceae) tended to increase their relative abundances in responding to land-use conversion, which may imply that the shifts of soil microbial communities associated with recovering of ecological conditions. Overall, given the rapid yet differential response to ecological restoration, investigation of the belowground microbial community can provide an effective way of assessing ecological recovery of restoration projects in the karst region.

Differences in N loading affect DOM dynamics during typhoon events in a forested mountainous catchment

The dissolved organic matter (DOM) and nutrient dynamics in small mountainous rivers (SMRs) strongly depend on hydrologic conditions, and especially on extreme events. Here, we investigated the quantity and quality of DOM and inorganic nutrients during base-flow and typhoon events, in a chronically N-saturated mainstream and low N-loaded tributaries of a forested small mountainous reservoir catchment in Taiwan. Our results suggest that divergent transport mechanisms were triggered in the mainstream vs. tributaries during typhoons. The mainstream DON increased from 3.4 to 34.7% of the TDN pool with a static DOC:NO₃-N ratio and enhanced DOM freshness, signalling a N-enriched DOM transport. Conversely, DON decreased from 46 to 6% of the TDN pool in the tributaries and was coupled with a rapid increase of the DOC:NO₃-N ratio and humified DOM signals, suggesting the DON and DOC were passively and simultaneously transported. This study confirmed hydrology and spatial dimensions being the main drivers shaping the composition and concentration of DOM and inorganic nutrients in small mountainous catchments subject to hydrologic extremes. We highlighted that the dominant flow paths largely controlled the N-saturation status and DOM composition within each sub-catchment, the effect of land-use could therefore be obscured. Furthermore, N-saturation status and DOM composition are not only a result of hydrologic dynamics, but potential agents modifying the transport mechanism of solutes export from fluvial systems. We emphasize the importance of viewing elemental dynamics from the perspective of a terrestrial-aquatic continuum; and of taking hydrologic phases and individual catchment characteristics into account in water quality management.

Management intensity controls soil N2O fluxes in an Afromontane ecosystem

Studies that quantify nitrous oxide (N₂O) fluxes from African tropical forests and adjacent managed land uses are scarce. The expansion of smallholder agriculture and commercial agriculture into the Mau forest, the largest montane forest in Kenya, has caused large-scale land use change over the last decades. We measured annual soil N₂O fluxes between August 2015 and July 2016 from natural forests and compared them to the N₂O fluxes from land either managed by smallholder farmers for grazing and tea production, or commercial tea and eucalyptus plantations (n=18). Air samples from 5 pooled static chambers were collected between 8:00am and 11:30am and used within each plot to calculate the gas flux rates. Annual soil N₂O fluxes ranged between 0.2 and 2.9kgNha^-1yr^-1 at smallholder sites and 0.6-1.7kgNha^-1yr^-1 at the commercial agriculture sites, with no difference between land uses (p=0.98 and p=0.18, respectively). There was marked variation within land uses and, in particular, within those managed by smallholder farmers where management was also highly variable. Plots receiving fertilizer applications and those with high densities of livestock showed the highest N₂O fluxes (1.6±0.3kgN₂O-Nha^-1yr^-1, n=7) followed by natural forests (1.1±0.1kgN₂O-Nha^-1yr^-1, n=6); although these were not significantly different (p=0.19). Significantly lower fluxes (0.5±0.1kgNha^-1yr^-1, p<0.01, n=5) were found on plots that received little or no inputs. Daily soil N₂O flux rates were not correlated with concurrent measurements of water filled pore space (WFPS), soil temperature or inorganic nitrogen (IN) concentrations. However, IN intensity, a measure of exposure of soil microbes (in both time and magnitude) to IN concentrations was strongly correlated with annual soil N₂O fluxes.