Non-climatic Factors Research Articles

Socioeconomic determinants of modern climate change adaptation of small-scale vegetable farmers in Bohlabela District, Mpumalanga Province

Climate change significantly impacts small-scale agriculture, with limited adaptation capabilities due to lack of access to advanced science and technology. Traditional methods are ideal, but modern adaptations require significant financial investment, affecting the smallholder under-resourced agricultural sector's economic activities. The study analyzed climate change adaptation drivers among small-scale vegetable farmers, using a representative sample of 244 farmers from four villages through face-to-face interviews and semi-structured questionnaires. Using the Logistic regression model, the results showed resources (extension services), institutional (association membership) and societal influence (farm produce theft, and animal trespassing in the farming plots) to be associated with the use of modern climate change adaptation measures in the study area. The study recommends expanding extension services, strengthening community policing, creating community grazing guidelines, and training farmers on climate change causes, social cohesion, and mitigation strategies to address farm produce theft and animal trespassing. The study contributes new knowledge to the discourse of climate change adaptation by providing empirical evidence pointing out the need to consider critical non-climate factors for farmers when making climate change adaptations interventions in the smallholder farming sector.

Predictive Potential of Maize Yield in the Mesoregions of Northeast Brazil

Most of the northeastern region of Brazil (NEB) has a maize production system based on family farming, with no technological advances and totally dependent on the natural rainfall regime, which is concentrated in 4 to 5 months in most parts of the region. This means that the productivity of this crop is low in the NEB. In the northern mesoregions of the NEB, rainfall is concentrated between January and June, in the east of the NEB from April to September, and in the west of the NEB from October to March. The growing season takes place during these semesters. With this in mind, our objective was to develop a model based on canonical correlation analysis (CCA) to predict corn production in the mesoregions of the NEB between 1981 and 2010, using accumulated precipitation per semester as the predictor variable and predicting the observed production in kg/ha. Our results showed that the CCA model presented higher correlations between observed and simulated production than that obtained simply from the direct relationship between accumulated rainfall and production. The other two metrics used, RMSE and NRMSE, showed that, on average, in most mesoregions, the simulation error was around 200 kg/ha, but the accuracy was predominantly moderate, around 29% in most mesoregions, with values below 20% in six mesoregions, indicative of better model accuracy, and above 50% in two mesoregions, indicative of low accuracy. In addition, we investigated how the different combinations between two modes of climate variability with a direct influence on precipitation in the NEB impacted production in these 30 years, with the combination of El Niño and a positive Atlantic dipole being the most damaging to harvests, while years when La Niña and a negative Atlantic dipole acted together were the most favorable. Despite the satisfactory results and the practical applicability of the model developed, it should be noted that the use of only one predictor, rainfall, is a limiting factor for better model simulations since other meteorological variables and non-climatic factors have a significant impact on crops. However, the simplicity of the model and the promising results could help agricultural managers make decisions in all the states that make up the NEB.

A Greenland-wide empirical reconstruction of paleo ice sheet retreat informed by ice extent markers: PaleoGrIS version 1.0

Abstract. The Greenland Ice Sheet is a large contributor to global sea level rise, and current mass losses are projected to accelerate. However, model projections of future ice sheet evolution are limited by the fact that the ice sheet is not in equilibrium with present-day climate but is still adjusting to past changes that occurred over thousands of years. While the influence of such committed adjustments on future ice sheet evolution remains unquantified, it could be addressed by calibrating numerical ice sheet models over larger timescales and, importantly, against empirical data on ice margin positions. To enable such paleo data–model interactions, we need Greenland-wide empirical reconstructions of past ice sheet extent that combine geomorphological and geochronological evidence. Despite an increasing number of field studies producing new chronologies, such a reconstruction is currently lacking in Greenland. Furthermore, a time slice reconstruction can help to (i) answer open questions regarding the rate and pattern of ice margin evolution in Greenland since the glacial maximum, (ii) develop a standardised record of empirical data, and (iii) identify new sites for future field campaigns. Based on these motivations, we here present PaleoGrIS 1.0, a new Greenland-wide isochrone reconstruction of ice sheet extent evolution through the Late Glacial and early- to mid-Holocene informed by both geomorphological and geochronological markers. Our isochrones have a temporal resolution of 500 years and span ∼ 7.5 kyr from approximately 14 to 6.5 kyr BP. We describe the resulting reconstruction of the shrinking ice sheet and conduct a series of ice-sheet-wide and regional analyses to quantify retreat rates, areal extent change, and their variability across space and time. During the Late Glacial and early- to mid-Holocene, we find the Greenland Ice Sheet has lost about one-third of its areal extent (0.89 million km2). Between ∼ 14 and ∼ 8.5 kyr BP, it experienced a near-constant rate of areal extent loss of 170 ± 27 km2 yr−1. We find that the ice-sheet-scale pattern of margin retreat is well correlated to atmospheric and oceanic temperature variations, which implies a high sensitivity of the ice sheet to deglacial warming. However, during the Holocene, we observe inertia in the ice sheet system that likely caused a centennial- to millennial-scale time lag in ice extent response. At the regional scale, we observe highly heterogeneous deglacial responses in ice extent evident in both the magnitude and rate of retreat. We hypothesise that non-climatic factors, such as the asymmetrical nature of continental shelves and onshore bed topographies, play important roles in determining the regional- to valley-scale dynamics. PaleoGrIS 1.0 is an open-access database designed to be used by both the empirical and numerical modelling communities. It should prove a useful basis for improved future versions of the reconstruction when new geomorphological and geochronological data become available.

AN ECONOMIC ANALYSIS OF WHEAT PRODUCTION IN THE LIGHT OF CLIMATE CHANGE IN INDIA

India is the second-largest producer of wheat in the world. Uttar Pradesh, Punjab, Haryana, Madhya Pradesh, Rajasthan, Bihar, and Gujarat are the major wheat-producing states. Out of all of these states, Uttar Pradesh produces the larger quantity of wheat. Wheat is exported by India to Bangladesh, Sri Lanka, the United Arab Emirates, Yemen, the Philippines, and Indonesia. This study aims to analyze the effects of climate change and other non-climatic factors on wheat production in India between 1991 and 2021. The researcher used climate and non-climate change variables: mean, maximum, minimum temperature, rainfall, production, net MSP, and cultivation area. This work tested long-run cointegration using an Auto-Regressive Distributed Lag (ARDL) bound test cointegration technique to evaluate short-run relationships among modeled variables. CUSUM and CUSUMQ tests assure model reliability and validity. The study’s findings demonstrated that the cultivated area has a major role in enhancing wheat output in the short and long term, while precipitation favors wheat production. In India, a 1% increase in cultivation area can increase 1.3% in wheat production in the long run. In the short run, a 1% increase in cultivation area increased 0.58% wheat production in India. Furthermore, although the temperature has little immediate effect, it is crucial for boosting wheat output over the long term.

Impact of climatic factors and poverty on wheat yields via machine learning in a semi-arid region across West Asia.

Abstract Winter-sown wheat is particularly vulnerable to high temperatures in spring. However, little is known concerning the impact of high temperatures and other climatic and non-climatic factors in combination on winter-sown wheat yields in arid and semi-arid regions. Therefore, in this study we investigate the impacts of high temperatures and other climatic indices, including evapotranspiration and aridity index during spring months, and non-climatic factors, including technology improvement and poverty ratio on irrigated and dryland wheat yields. We employed Random Forests a machine learning technique to our long-term data (1980-2010) and annual wheat yields (irrigated and dryland) for 27 provinces of Iran. The results show that technology improvement and poverty ratio are the most important variables which explain irrigated wheat yields variability. Temperatures above 31°C, evapotranspiration and aridity index are the other variables that alter irrigated whet yields in the region during the period 1980-2010. Dryland wheat yields mainly explained by temperatures above 31°C. Poverty ratio, technology improvement, evapotranspiration and aridity index ranked after high temperatures above 31°C, respectively. This study demonstrates that, although, in arid areas technological improvement and irrigation may avoid yield reduction due to high temperatures in spring months, in poor arid areas and dryland systems, high temperatures significantly reduce wheat yields.

To what extent can we predict variation of bryophyte and tracheophyte community composition at fine spatial scale along an elevation gradient?

Mounting evidence points to the need for high-resolution climatic data in biodiversity analyses under global change. As we move to finer resolution, other factors than climate, including other abiotic variables and biotic interactions play, however, an increasing role, raising the question of our ability to predict community composition at fine scales. Focusing on two lineages of land plants, bryophytes and tracheophytes, we determine the relative contribution of climatic, non-climatic environmental drivers, spatial effects, community architecture and composition of one lineage to predict community composition of the other lineage, and how our ability to predict community composition varies along an elevation gradient. The relationship between community composition of one lineage and 68 environmental variables at 2-25 m spatial resolution, architecture and composition of the other lineage, and spatial factors, was investigated by hierarchical and variance partitioning across 413 2x2m plots in the Swiss Alps. Climatic data, although significant, contributed less to the model than any other variable considered. Community composition of one lineage, reflecting both direct interactions and unmeasured (hidden) abiotic factors, was the best predictor of community composition of the other lineage. Total explained variance substantially varied with elevation, underlining the fact that the strength of the species composition-environment relationship varies depending on environmental conditions. Total variance explained increased towards high elevation up to 50 %, with an increasing importance of spatial effects and vegetation architecture, pointing to increasing positive interactions and aggregated species distribution patterns in alpine environments. In tracheophytes, an increase of the contribution of non-climatic environmental factors was also observed at high elevation, in line with the hypothesis of a stronger environmental control under harsher conditions. Further improvements of our ability to predict changes in plant community composition may involve the implementation of historical variables and higher-resolution climatic data to better describe the microhabitat conditions actually experienced by organisms.

Assessment of occupants’ adaptive capacity: a case study in northern Guizhou of China

The thermal comfort of rural residents is a major issue related to people’s livelihood. Due to differences in climatic factors (e.g. local climate) and non-climatic factors (such as building structures, economic and social–cultural levels, living habits and availability of environmental control) between rural and urban areas, participants have different thermal requirements for a given thermal environment. This difference means that thermal comfort standards that consider only urban conditions may not be applicable to rural situations. Therefore, a thermal comfort field study was conducted on the thermal comfort of traditional residential houses with natural ventilation located in rural areas of northern Guizhou, China. This study aims to understand the indoor thermal conditions and perceptions of occupants in rural areas, with a total of 513 subjects that participated in a questionnaire survey. Most survey respondents accept the thermal environment in which they reside, even if the indoor temperature is not within the recommended thermal comfort range specified by international standards such as Ashrae 55. The adaptive predicted mean vote is established using the least-squares method. The adaptive coefficient λ representing the adaptive capacity is twice the recommended coefficient of the Chinese standard, GB/T 50785-2012. This confirms that rural residents have a stronger adaptability to cold conditions in winter. The findings are beneficial for improving thermal comfort and carbon dioxide emission reduction for traditional residential houses in rural areas of northern Guizhou, China.

Navigating food security in India: unravelling the interplay of climatic and non-climatic factors

Navigating food security in India: unravelling the interplay of climatic and non-climatic factors

Climate-limited vegetation change in the conterminous United States of America.

The effects of climate change on vegetation composition and distribution are evident in different ecosystems around the world. Although some climate-derived alterations on vegetation are expected to result in changes in lifeform fractional cover, disentangling the direct effects of climate change from different non-climate factors, such as land-use change, is challenging. By applying "Liebig's law of the minimum" in a geospatial context, we determined the climate-limited potential for tree, shrub, herbaceous, and non-vegetation fractional cover change for the conterminous United States and compared these potential rates to observed change rates for the period 1986 to 2018. We found that 10% of the land area of the conterminous United States appears to have climate limitations on the change in fractional cover, with a high proportion of these sites located in arid and semiarid ecosystems in the Southwest part of the country. The rates of change in lifeform fractional cover for the remaining area of the country are likely limited by non-climate factors such as the disturbance regime, land management, land-use history, soil conditions, and species interactions and adaptations.

Implications of uncontrolled water withdrawal and climate change on the water supply and demand gap in the Lake Tana sub-basin

This study evaluates the implications of multiple climatic and non-climatic factors on the water resource of the Lake Tana sub-basin, Ethiopia. The study focuses on three drivers: land use change, irrigation expansion, and climate change (CC), and their impact on the current and future water availability across the sub-basin. The study uses a random forest (RF) machine learning classifier in the Google Earth Engine (GEE) platform to detect land use land cover change (LULC) and for mapping the actual irrigated-area. The Climate Hazards Group InfraRed Precipitation and temperature data were used with station data to evaluate the implication of CC on the water availability of Lake Tana sub-basin. The supply-demand relationship was done for Gumara catchment within Tana sub-basin as an experimental site. Based on the LULC analysis, plantation, cropland, bare lands, built-up, and wetland showed an increasing trend, while forest, bush land, and grassland showed a decreasing trend. The increasing rate of crop land in the expense of natural forest, shrub land, grassland may cause runoff/flood, high soil erosion, and lower rate of groundwater recharge. The actual irrigated area mapping analysis shows a widespread irrigation near the Lake Shore and upstream parts of the sub-basin. The climate change analysis shows an increasing trend of potential evapotranspiration during the irrigation period attributed to increase in maximum temperature. The rising of potential evapotranspiration during the irrigation period creates a water shortage in the study and future periods as the crops need more water for growth. The estimated stream flow for Gumara catchment shows an increasing trend for the future period. The supply-demand relationship of the catchment shows an uneven distribution of water in the Gumara catchment both in the current and future periods resulting in unbalance abstraction of irrigation water. The study reveals that climate change, land cover change, and uncontrolled expansion of irrigated land area are likely to increase the unmet demand by increasing irrigation water demand, and this can cause conflict of interest between the users. Therefore, sustainable water resource management practices such as land management practices, and adaptive management of irrigation should be applicable to prevent or reduce the occurrence of conflict over the water demand.

Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020

ABSTRACT Forest dynamics provide important information on the ecological environment. The Three-North Shelter Forest Program (TNSFP) is one of the world’s largest reforestation/afforestation programs, however the actual changes in forest cover in the Three-North Regions (TNR) of China resulting from this program are highly uncertain. This study quantified changes in fractional forest cover (FFC) at 30 m using Landsat data from 1996 to 2020. Using the Google Earth Engine platform, more than 40,000 images from Landsat-5, Landsat 7 and Landsat-8 were integrated, and the annual surface reflectance was normalized based on the multi-band least squares regression and maximum normalized difference vegetation index composite method. An ensemble learning model trained using high-resolution Gao-Fen 2 satellite imagery was used to generate the FFC long time-series product. FFC showed an increasing trend with average rates of 0.022/10a in the last 25 years, and 0.03/10a after 2010 largely corresponding to the fourth and fifth phases of the TNSFP. There are significant regional differences in the relationship between FFC and air temperature ( R 2 = 0.37) and precipitation ( R 2 = 0.49). The increased air temperature in arid and less rainy areas inhibit the FFC increase, whereas the increase in precipitation had a promoting effect. FFC appeared more sensitive to changes in solar radiation and heat conditions in humid and rainy areas. The attribution analysis revealed that 34% of FFC changes were caused by climatic variables and 66% were caused by non-climatic factors. Among them, afforestation associated with the TNSFP significantly increased FFC, and forest fire is a key factor of forest change in the Greater Khingan Ranges and Lesser Khingan Ranges regions. Planting single tree species caused biological disasters in forests of Xinjiang and Inner Mongolia. Further analysis of the increased FFC using high-level satellite products demonstrated an improvement in environmental conditions with cooler land surface temperature and higher vegetation gross primary production over the TNR.

What are the Implications of Climatic and Non-climatic Factors on Crop Production? Evidence from Turkey

What are the Implications of Climatic and Non-climatic Factors on Crop Production? Evidence from Turkey

Climate Change Impact on Cereal Production and Food Security in Hebron Governorate: An Analytical Approach

Cereal crop failures result from climate shocks, which are caused by the climate\'s variables fluctuation and represent a complex system of interrelated elements. This study aims to explore the effects of climate change, especially precipitation and temperature fluctuations on cereal cultivation and food security in the Hebron Governorate. By utilizing a range of statistical methods, including the autoregressive distributed lag (ARDL) bounds testing approach, and incorporating qualitative insights from local agricultural experts, this research provides a thorough analysis of climate dynamics and their potential consequences on cereal cultivation and food security. \nThe analysis results uncover a prominent causal connection between these climatic elements and agricultural production, emphasizing the negative impacts of heightened carbon levels, temperature, and unpredictable rainfall events and patterns, on cereal crop yields. Furthermore, the research highlights the intricate interrelationship between non-climatic factors like energy usage, workforce, and financial growth in influencing agricultural performance. Of course, this in turn affects the fragile food security at the Hebron governorate level.

The climatic suitability of New Zealand for Cirsium arvense and its biological control agent Cassida rubiginosa

The leaf-feeding beetle, Cassida rubiginosa, was introduced into New Zealand from Europe in 2007 as a biological control agent for Cirsium arvense (Californian thistle) and is now widely distributed. To determine the extent to which geographically variable climate might explain its observed sporadic impact, we developed a climate-niche model for each of the species using CLIMEX. The models reveal that the climate throughout most of New Zealand is variably suitable for both species, although everywhere relatively less suitable for the beetle. However, we found no evidence that this climate suitability bias favouring the thistle explains the sporadic impact of the beetle. First, 64 geographically separate beetle populations classified by field observers according to their impact on the thistle (‘none’, n = 29; ‘low’, n = 22; ‘high’, n = 13) showed no relationship with the modelled climate suitability (Ecoclimatic Index) of their locations for either the beetle or the thistle. Second, the two models reveal a similar climate suitability bias favouring the thistle throughout much of the species’ ‘eco-climatic suitability space’ in their native range (Eurasia) where the beetle is a widespread natural enemy of the thistle. Hypothetical explanations for the sporadic impact of the beetle in New Zealand are explored, including lack of suitable overwintering habitat, predation, and incompatible thistle control operations. We conclude that in general, climate suitability, while a necessary condition, is alone insufficient for the success of a weed biological control program, and that non-climatic habitat factors may often explain spatially patchy impacts of natural enemies such as C. rubiginosa.

Controls on Quaternary geochemical and mineralogical variability in the Koora Basin and South Kenya Rift

The South Kenya Rift is comprised of a series of N-S-oriented grabens with sediments that preserve an approximate one-million-year environmental history that reflects the interplay of climate, tectonism and volcanism. This study attempts to disentangle the relative roles of these major controls by comparing the geochemical records preserved in three sedimentary basins. The study focuses on the Koora Basin using bulk geochemical data in a 139-m-long core. This record is then compared with geochemical data and environmental histories from a 196-m-long core at Magadi and outcrops in the Olorgesailie Basin. Four climatic phases (1000–850; 850–470; 470–400; 400–0 ka) are recognised at Koora, which can also be distinguished in the Magadi and Olorgesailie Basins. However, inter-basin contrasts also suggest that additional, non-climatic factors influenced these geochemical histories, particularly during four intervals. These include 1) the Magadi Transition (MT; ∼770–700 ka), 2) the Magadi Tectonic Event (MTE; ∼540 ka), 3) the Koora Instability Period (KIP; ∼325–180 ka), and 4) the Trona Precipitation Period (TPP; ∼105–0 ka). Prior to the MT, Zr/TiO2, La/Lu, Mo, As, V and Na/Ca in Magadi and Koora cores were similar but afterwards diverged. Major reductions in transition metals at Magadi during the MTE reflect tectonically-induced cross-rift drainage diversion. This contrasts with the Koora and Olorgesailie basins where these metals were constant from ∼1000 to 300 ka. The KIP represents a significant increase in volcanic inputs to the Koora Basin and increased geochemical variability. Bromine (Br), which reflects peralkaline volcanic activity and/or evaporative concentration, is elevated during the KIP at Koora but is below detection limits in the rest of the Koora core. Br in the Magadi core does not correlate with that in the Koora record, suggesting contrasting accumulation processes. The TPP represents a phase of trona precipitation at Magadi but not at Koora. This difference partly reflects increased magmatic CO2 rising along faults in the Magadi basin during a period of increasing aridity. Rare-earth element patterns indicate a major change at Magadi with many anomalies after about 325 ka to the present, caused by the development of hypersaline waters, which did not occur at Koora or Olorgesailie. The geochemical data from the three basins help to partially separate climatic controls from those related to volcanism, tectonism and local geomorphology.

Vulnerability of communities' livelihoods to the impacts of climate change in north-western highlands of Tanzania

Climate change has emerged as one of the critical challenges to human well-being. Changing climate places direct and indirect impacts on human activities and is mainly triggered by non-climatic stressors, which are diverse and inherent in many communities. However, there has been diversity in how climate and non-climatic stress factors affect human well-being and thus requiring locally specific contextualisation of how climate change is driving change in many ecosystems. This study analysed climate and non-climate factors for communities' vulnerability and impacts using a landscape approach in selected villages in the western highlands of Tanzania, specifically in Kasulu and Buhigwe districts in Kigoma Region. The aim was to understand communities' vulnerability to the impacts of climate, and non-climate processes, particularly with regard to livelihoods and impacts, particularly in forest resources. Study sites and respondents were selected through simple random and purposive sampling methods. Data were collected through household surveys, key informants interviews, and focus group discussions. Meteorological data were used for the analysis of climatic changes. Quantitative data analysis tools included meteorological statistics software such as CLIDATA, INSTAT, XLSTAT and SPSS. Theme-content analysis was used to analyse qualitative data. Findings indicate inter-annual and seasonal variabilities of rainfall and temperature levels from the normal across the study sites. The study revealed significant increasing trends for mean annual Maximum and Minimum temperature. Significant changes in rainfall patterns were decreasing seasonal and annual rainfall trends, unreliable onset and cessation, and erratic seasonal rainfall. The maximum decline of seasonal rainfall had slope values of −14.51, while the maximum decline of annual rainfall trends had a slope value of −12.76. The minimum decline for seasonal rainfall had slope values of −2.17, and annual rainfall trends had slope values of −1.36. Villages in the highland zone were found to be highly vulnerable to the impacts of climate change and non-climate stress factors, with a 0.61 vulnerability index value. Major climate stress factors for communities' vulnerability included seasonal variability of rainfall and temperature increase, which influenced the increase of pests and diseases and other unfavourable climatic conditions that affect crop production and livestock keeping. The effects, directly and indirectly, influenced the low agricultural yields and decreased income. Non-climate stress factors such as landscape characteristics, mobility, inadequate extension services, and low household asset endowment might have been accelerating communities' vulnerability to the effects of the changing climate. Moreover, the study shows the climate change on a community's resilience. Generally, changes in climate conditions result in many adverse consequences and have been influencing communities' vulnerability.

Sustainable livelihood capital and climate change adaptation in Pakistan's agriculture: Structural equation modeling analysis in the VIABLE framework

This study aims to assess the role of sustainable livelihood capital, the mediation of investments and farming purposes, and the moderation of climatic and non-climatic factors in the adaptation process, particularly in the aspects of Crop, Farm, Irrigation, and Economic Management. Moreover, guided by the VIABLE (Values and Investments for Agent-Based Interaction and Learning in Environmental Systems) framework, we analyze stakeholders' actions, priorities, and goals in the climate change adaptation process. A structured questionnaire was designed based on a five-point Likert scale covering the concepts of livelihood capital, climate change adaptation, investment priorities, farming constraints, and farmers' decision-making factors. Field data were collected from 800 farmers during December 2021 to February 2022 in the irrigated agricultural regions in the Indus Plain of the Punjab and Sindh provinces, Pakistan. We employed the Partial Least Square Structural Equation Modeling approach to the VIABLE framework (VIABLE-SEM) to analyze the collected data. The results confirm livelihood capital as the most significant determinant (beta = 0.57, effect size = 0.503) for farmers’ adaptation strategies in the Indus plain. Other variables, such as the principal purpose of farming, available investment options, natural and human constraints, appear less important. We identified 13 significant viability pathways that show investment priorities, farming purposes, and constraints faced by the farmers in climate change adaptation. The study also found that non-climatic factors negatively influence (beta = −0.156) the relationship between capital and adaptation, while climatic factors positively influence (beta = 0.050) this relationship. Interestingly, the presence of these influencing factors increases the adaptive capacity of farmers. These findings have important implications for policymakers and researchers in designing and implementing effective climate change adaptation strategies in the agricultural sector of Pakistan.

Understanding factors intercepting response of rice farmers to climate change in Ebonyi State, Nigeria

<p>Understanding factors intercepting the response of rice farmers to climate change in Ebonyi State, Nigeria, was investigated. A total of 70 rice farmers were sampled using a multi-stage sampling technique and administered a questionnaire. Primary data was collected and analyzed using descriptive statistics (mean, frequency, percentage, chart) and an ordinary least squares multiple regression model. Results show that the rice farmers cultivated on small land holdings, were relatively educated, sourced their land via inheritance, and had 16 years of farming experience. Results reveal that 72% of the rice farmers are highly aware of climate change, while 17% and 11% are relatively aware and not aware, respectively. Temperatures, rainfall, and the number of rainy days have positive effects on rice production, while sunshine hours and relative humidity have negative effects on rice production. Age, gender, education, farm size, extension contacts, and participation in workshops were significant variables influencing rice production in the state. Capital, crude implements, pests and diseases, poor soil, lack of incentives, and cultivation systems were the non-climatic factors that influenced rice cultivation in the state. Farmers were recommended to embrace climate-smart cropping systems and seek early climate change information to mitigate the adverse effects of climate change on rice cultivation.</p>

Systematic review: Climate and non-climate factors influencing wood density in the boreal zone

Wood density is a crucial factor in determining the quality of wood in boreal ecosystems within the Northern Hemisphere. Climate variables play a significant role in shaping wood density, posing challenges for forest managers and stakeholders in the wood industry to adapt amidst climate change. However, our current understanding of these effects remains incomplete. This systematic literature review explores the multifaceted influences on wood density in the boreal zone, encompassing both climate-related and non-climatic factors. The findings demonstrate that warmer temperatures can cause both increases and decreases in wood density, primarily due to their impact on tracheid lignification and cell wall thickening. Nonetheless, the outcome depends on various factors, including species type, age, soil conditions, presence of pests and diseases, fire, windstorms, and silviculture practices. The quantification of complex relationships between these factors and wood density has been insufficient in existing literature. Understanding the impacts of both climate and non-climate factors on wood density is essential for fostering a sustainable wood industry, while effectively mitigating adverse effects and maximizing benefits. Forest managers can leverage this knowledge to optimize wood production strategies, ensuring long-term ecological resilience amidst the increasingly variable climate challenges.

Differential effects of climatic and non-climatic factors on the distribution of vegetation phenology trends on the Tibetan plateau

The study of vegetation phenology changes is important because it is a sensitive indicator of climate change, affecting the exchange of carbon, energy and water fluxes between the land and the atmosphere. Previous studies have focused on the effects of climatic factors among environmental factors on vegetation phenology, thus the effects of non-climatic factors among environmental factors have not been well quantified. This study endeavors to scrutinize the spatiotemporal inconsistency in the start-of-season (SOS) and the end-of-season (EOS) on the Tibetan Plateau (TP) and to quantify the effects of environmental factors on phenology. To this end, the Moderate-resolution Imaging Spectroradiomater (MODIS) Normalized Difference Vegetation Index (NDVI) data from 2001 to 2018 and four common used methods were employed to extract SOS and EOS, and the site data was used to select the most appropriate phenology results. The Geodetector model was used to assess and measure the explanatory power of different environmental factors. The research results indicate that temperature exerts a more substantial impact on phenology than precipitation on TP. non-climatic factors such as longitude, latitude, and elevation are more influential in determining the distribution of phenological trends than climatic factors. Among these non-climatic factors, latitude has the most prominent effect on the trends of SOS. Furthermore, non-climatic factors exhibit a stronger effect on SOS, whereas EOS is more susceptible to climatic factors and less influenced by non-climatic factors. These discoveries bear great significance in comprehending the intricate outcomes of regional changes on vegetation phenology and enhancing phenology models.