Distinct Dry Seasons Research Articles

Literature Review on Stochastic Modeling of Wet and Dry Spells

With increasing concerns about climate change and its profound implications for water resources, stochastic modeling of wet and dry spells has emerged as a critical domain within hydrology and climatology, providing insight into the temporal patterns of precipitation and drought occurrences. This review of the literature synthesizes recent advances in the modeling of wet and dry spells using stochastic methods, focusing on publications from 2000 to 2024. The review examines various modeling approaches, including Markov chain models, mixed probability models, non-homogeneous models, and time series approaches. Key findings indicate that Markov chain models are effective in simulating the sequential occurrence of wet and dry spells, with higher-order variants addressing issues of overdispersion. Mixed probability models excel at representing heterogeneity and extremes in precipitation data, especially in regions with distinct wet and dry seasons. Non-homogeneous models are valuable for understanding the temporal dynamics and irregularities of dry spells, revealing significant shifts in their frequency and duration over time. These can be complemented by time-series methods to highlight long-term trends and seasonal variations. The review underscores the importance of regional specificity in modeling approaches to accurately capture local climatic and geographical variability. Recommendations for future research include the integration of hybrid models that combine the strengths of various approaches to improve predictive precision, focusing on the impacts of climate change, and conducting cross-regional comparisons to generalize findings and enhance the robustness of the models.

Seasonal variations and temporal instability of motorcyclist injury severity in Cambodia: Analyses based on a random parameter logit model with heterogeneity in means and variances

Motorcycles are a prevalent mode of transportation in countries like Cambodia that experience distinct rainy and dry seasons. However, the safety concerns associated with motorcycling in this region have not been thoroughly investigated. This study addresses this research gap by examining the severity of motorcyclist injuries in Cambodia, considering the potential variations across seasons and the fluctuations in contributing factors over time. Utilizing a random parameter logit model with heterogeneity in means and variances, the research analyzes motorcycle crash data from 2015 to 2017 to identify heterogeneities in the determinants of injury severity. The study confirms seasonal variations and temporal instabilities in influential factors, highlighting the need for distinct modeling for dry and rainy seasons due to varying contributing factors. Key findings include the consistent increase in fatal injury risk associated with head-on collisions and elderly rider involvement across both seasons. During the rainy season, motorcycle-to-motorcycle crashes significantly heighten the likelihood of severe injuries, with weekend crashes more likely to result in fatalities. Furthermore, more than half of speeding incidents during the rainy season consistently led to fatal injuries across all three years. In contrast, during the dry season, riders faced a greater risk of severe injuries compared to pillion riders, with crashes on national roads more likely to lead to fatal outcomes. Temporal stability tests further reveal that the influence of external variables on motorcyclist injury severity varies across years, stressing the need for tailored, season-specific approaches to effectively mitigate and prevent crashes.

Seasonal Variations in Population Dynamics of Insect Pests in Tiruvallur District, Tamil Nadu, India

Understanding the complex relationship between seasonal changes and pest dynamics is essential for establishing effective protection methods in contemporary agriculture and guaranteeing long-term agricultural sustainability and food security. The study was conducted in the Tiruvallur District of Tamil Nadu, India, which is characterized by a tropical climate with distinct wet and dry seasons [1]. Shannon-Wiener Index and Simpson's Index biodiversity indices reflected the moderate to high pest diversity of species in the region. Values for Shannon-Wiener indexes ranged between about 1.93-1.95 for different species of insect pests, and Simpson's indexes were found to range between about 0.85-0.86. All these indices indicate a well-balanced insect pest community with high species richness and even distribution, which is necessary to maintain ecological resilience. The findings enrich our understanding of pest ecology in tropical agriculture and provide valuable insights applicable to other regions facing similar issues. The observed seasonal patterns emphasize the importance of ongoing monitoring and adaptive management to tackle the challenges posed by insect pests amid climate variability and agricultural intensification. Additionally, this research offers a thorough framework for comprehending and managing insect pest populations in the Tiruvallur District.

Ecological determinants of leishmaniasis vector, Lutzomyia spp.: A scoping review.

Leishmania spp. are zoonotic parasites transmitted by phlebotomine sand flies, including those of the Lutzomyia genus, which can cause leishmaniases in both humans and dogs. Lutzomyia spp. are established in many countries in South and Central America and some areas of the southern United States, with suspected potential of these vectors to undergo further range expansion due to climate change. A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extensions for Scoping Reviews (PRISMA-ScR) guidelines to describe the current state of knowledge on the key ecological factors associated with Lutzomyia spp. survival, reproduction and establishment. The following electronic databases were searched for eligible studies published from 1 January 1990, to the date of search, 26 April 2023: CAB Direct (CABI), MEDLINE (via Ovid), Biological Sciences Database and Environmental Sciences Database. Primary research articles that were available in English and focused on ecological factors associated with Lutzomyia spp., such as climatic and habitat factors, geographic range, seasonality and temporality, and host abundance, were eligible for inclusion in the study. Following de-duplication, a total of 167 studies were included in Level 1 screening, 64 studies were included in Level 2 screening and 31 studies met the criteria for data extraction. Study locations included Argentina, Brazil, Colombia, Peru, Venezuela, the United States, Mexico and Canada, with some studies including multiple regions. A total of 31 different Lutzomyia spp. were assessed across these studies, with most (51.6%) of the studies focused on Lutzomyia longipalpis. Eligible studies investigated factors such as seasonality (n = 5), temperature (n = 19), precipitation (n = 13), humidity (n = 2), vegetation presence or requirements (n = 13), ecotypes (n = 7), and/or community type (i.e., urban, suburban, rural) (n = 5). Lutzomyia spp. activity was found to be higher during the rainy season, and peak when temperatures were between 20 and 25°C. Lutzomyia spp. were also found to preferentially reside in tropical or subtropical forests, which are characterised by their lack of a distinct dry season and high precipitation. This scoping review summarised the current state of the literature on the ecological factors associated with the survival, activity and reproduction of Lutzomyia spp. While there appears to be some consensus in the literature regarding some ecological requirements (such as seasonality, temperature and habitat features), overall, there is a lack of published research in this topic. This poses a significant challenge for future studies, which aim to predict the future distribution of Lutzomyia spp. in the context of climate and land use changes. Additional ecological research is urgently needed on Lutzomyia spp. given their relevance to both human and animal health.

Reconstruction of the marine carbonate system at the Western Tropical Atlantic: trends and variabilities from 20 years of the PIRATA program

The Western Tropical Atlantic Ocean (WTAO) is crucial for understanding CO2 dynamics due to inputs from major rivers (Amazon and Orinoco), substantial rainfall from the Intertropical Convergence Zone (ITCZ), and CO2-rich waters from equatorial upwelling. This study, spanning 1998 to 2018, utilized sea surface temperature (SST) and sea surface salinity (SSS) data from the PIRATA buoy at 8°N 38°W to reconstruct the surface marine carbonate system. Empirical models derived total alkalinity (TA) and dissolved inorganic carbon (DIC) from SSS, with subsequent estimation of pH and fCO2 from TA, DIC, SSS, and SST data. Linear trend analysis showed statistically significant temporal trends: DIC and fCO2 increased at a rate of 0.7 µmol kg-1 year-1 and 1.539 µatm year-1, respectively, and pH decreased at a rate of -0.001 pH units year-1, although DIC did not show any trend after data was de-seasoned. Rainfall analysis revealed distinct dry (July to December) and wet (January to June) seasons, aligning with lower and higher freshwater influence on the ocean surface, respectively. TA, DIC, and pH correlated positively with SSS, exhibiting higher values during the dry season and lower values during the wet season. Conversely, fCO2 correlated positively with SST, showcasing higher values during the wet season and lower values during the dry season. This emphasizes the influential roles of SSS and SST variability in CO2 solubility within the region. Finally, we have analysed the difference between TA and DIC (TA-DIC) as an indicator for ocean acidification and found a decreasing trend of -0.93 ± 0.02 μmol kg-1 year-1, reinforcing the reduction in the surface ocean buffering capacity in this area. All trends found for the region agree with data from other stations in the tropical and subtropical Atlantic Ocean. In conclusion, the use of empirical models proposed in this study has proven to help filling the gaps in marine carbonate system data in the Western Tropical Atlantic.

Effects of Different Seasons on Milk Quality: A Study on Two Cattle Breeds in Rainy and Drought Contexts

The primary focus of dairy farming in the central region of Peru centers on producers. However, there is limited information on how different altitudinal zones, particularly during rainy and dry seasons, affect milk production. The present study aimed to investigate the effects of the rainy and dry seasons on the physicochemical properties of milk from Brown Swiss and Holstein cattle. A total of sixty cows were selected for the study, comprising 30 Brown Swiss and 30 Holstein. The study was conducted across two distinct seasons, including rainy and dry seasons. All animals received the same semi-intensive management and were fed ryegrass and balanced feed. Each animal provided 500 ml of milk for analysis in the morning. The milk was transported at a temperature of 2 °C, where they were analyzed with the Lactoscan equipment to evaluate protein, lactose, fat, total solids, milk density, freezing point, salts, and pH. Significant differences were observed in the interaction between Brown Swiss and Holstein breeds across different seasons, including rainy and dry periods. Significant differences were observed in protein content, showing a positive effect in the interaction “rain: Brown” a value of 3.50 ± 0.36, while “rain: Holstein” showed 3.14 ± 0.05. Statistical differences were observed in the interactions for lactose content, with rain: Brown at 4.82% and dry: Holstein at 4.37%. Similarly, there were significant differences in fat content and total solids for rain interaction of rain: Holsten, and dry: Brown. Nevertheless, no differences were observed in terms of milk density, freezing point, salts, and pH. It is concluded that there was an influence of the interaction between breed physiology and seasonal conditions on milk composition. The results also highlight the impact of season-specific environmental factors on the quality of milk.

Spatiotemporal changes of climatic disasters and population displacements in Africa

ABSTRACT Frequent global climatic disasters are posing a growing threat, especially in populous Africa. Understanding the intrinsic interactions between climatic disaster and the resulting affected population in Africa can provide a representative sample of developing countries for global governance of climate change. This study explored the spatiotemporal dynamics in climatic disasters and disaster-related displacements in Africa from a geographical perspective. The results showed that climatic disasters in Africa occurred with seasonality consistent with African climate characterized by distinct dry and rainy seasons, manifested as flood, storm, and heat wave events occurring in the rainy season, wildfire and cold wave events taking place in the dry season, and prolonged droughts spanning both dry and rainy seasons. Meanwhile, the spatial pattern and variation trend of climatic disasters and displacements varied greatly by the five African sub-regions. East Africa experienced the highest number of disasters and displacements, while Southern Africa bore the least. Flood and drought triggered a third of total displacements in the most populated West Africa. The least frequent disasters dominated by flood only affected less than 10.9% of the total in Central Africa. 6.8% of the total displacements were primarily induced by coastal flood in North Africa.

Climatic-Geomorphological Investigation of the World's Wettest Areas around Cherrapunji and Mawsynram, Meghalaya (India)

This research paper comprehensively examines the climate and geomorphological features of Cherrapunji and Mawsynram, aiming to understand the factors and environmental implications of their extreme precipitation. The study investigates climatic patterns, identifies geomorphological characteristics, and explores the factors influencing the occurrence of heavy rainfall in these areas, and displays unique rainfall patterns with high precipitation levels and notable spatio-temporal variation influenced by topographic interactions. Trend analysis reveals stable rainfall conditions over the past 122 years. The shift of the world's wettest place from Cherrapunji to Mawsynram in recent decades have been attributed to various factors such as geographical location, geomorphology-local topography, LULC-human influence, rain shadow effect, and orographic lifting effects. Cherrapunji recorded maximum rainfall of 24.55 thousand mm, while Mawsynram received 26 thousand mm of rainfall in the last century. The analysis of long-term rainfall data indicates distinct dry and wet seasons, with recent trends (2000-2020) suggesting a decline in rainfall for both locations. Furthermore, extreme value analysis techniques are employed to estimate maximum rainfall for different return periods, offering insights into extreme rainfall events. The return period of one day's highest rainfall of 1340.82 mm is about 100 years. The findings contribute to our understanding of climate change impacts, support sustainable development practices, and inform strategies for water resource management and erosion mitigation in similar geographic contexts. This research enhances our knowledge of these unique regions and their significance within the broader context of global climate systems.

The non-uniform time-lag and cumulative responses of terrestrial ecosystem water use efficiency to climate change in Lake Victoria Basin, East Africa

Revealing the response mechanisms of carbon–water cycle to maximum and minimum temperatures and daytime and nighttime warming is important for managing fragile ecosystems exposed to severe climate warming and extreme weathers. Taking water use efficiency (WUE) characterizing the coupled carbon–water cycle as the research object, and maximum and minimum temperatures as the indicators of temperature change, this study explored the response of ecosystem WUE to temperature change in Lake Victoria Basin during distinct rainy and dry seasons. The results revealed the time-lag and cumulative multiple effects of antecedent maximum and minimum temperatures on current ecosystem WUE, which marked differences between the rainy and dry seasons. The monthly average ecosystem WUE in the rainy seasons (0.99 g C kg−1 H2O) were higher than those in the dry seasons (0.83 g C kg−1 H2O) during 2001–2018. WUE were more sensitive to temperature change in the dry seasons, with significant negative correlation with minimum temperature and positive correlation with cumulative maximum temperature. In rainy seasons, WUE showed more significant time-lag and cumulative effects, with response to maximum temperature for lagging approximate 3 months, to minimum temperature for lagging 0–2 months, to cumulative maximum temperature for lagging 1 month, and to cumulative minimum temperature lagging 3–4 months, respectively. The results add new evidence for differential non-instantaneous responses of WUE to maximum and minimum temperatures under dry and wet conditions.

FACTORS MILITATING AGAINST AGRICULTURAL PRODUCTIVITY OF CROP FARMERS IN NIGER STATE, NIGERIA

Niger State has the largest landmass in Nigeria. With 8.6 million hectares of land which represents about 9.3% of the total landmass of Nigeria, the state experiences distinct dry and wet seasons with annual rainfall varying from 1,100 mm (120 days) in the northern part to 1,600 mm (150 days) in the southern part. The vegetation, soil and weather patterns are favourable to produce a wide spectrum of food and cash crops of various types. The major crops grown in the State include rice, maize, millet, sorghum, yam, potato, soybean, groundnut, cashew, benniseed and cassava. The primary aim of this study was to investigate the factors militating against agricultural productivity of farmers in production of crops in the state. Both primary and secondary data were used for the study purposes. Descriptive statistics was used on sample of 360 crop farmers. Findings from the study indicates that fertiliser, herbicides, labour, late onset rains and high interest rates are the factors militating against the production of food crops in Niger State. The study thus concluded that, the application of inappropriate agronomic practices such as untimely planting, incorrect plant spacing, wrong method of planting, poor sowing depth, delayed weeding, ineffective pest and disease control, inappropriate use of fertilizers, untimely harvesting, use of low yielding varieties and inconsistent rainfall patterns, will always significantly reduce crop yields.

Baseflow Variation in Southern Taiwan Basin

Baseflow is among the most important components of streamflow. It is the main source of streamflow from groundwater systems in the dry season and also plays an important role as a water resource in the ecological environment and for human activities. In recent years, because of climate change, the number of dry season days in Taiwan has increased, and the wet season has been delayed, resulting in fewer rainy days and increased precipitation intensity. In addition, the spatial distribution of rainfall is uneven, and rivers are short and fast-flowing. Taiwan has become a country with abundant rainfall but insufficient water resources; therefore, the assessment of baseflow is important. This study selected eight basins with distinct wet and dry seasons in southern Taiwan as the study area. The baseflow characteristics and their relationships with climate features were assessed using time series analysis, baseflow attribution analysis, and wavelet analysis. The results showed that baseflow has an increasing trend; both precipitation and evapotranspiration have a significant positive correlation with baseflow, and the impact of precipitation is greater than that of evaporation. Sensitivity analysis showed that baseflow increases with increasing evaporation and precipitation; this behavior is related to the concentration of precipitation and evaporation in the wet season. Baseflow attribution analysis showed that the contribution of climate change to baseflow (75.0%) was larger than that of human activities (−2.9%), indicating that climate change was the main factor in the increase in baseflow. Wavelet analysis showed that both the El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) are correlated with baseflow, where the PDO is more strongly correlated than the ENSO. The main timescales of the ENSO and PDO are a 4–8-year band and an 8-year band, respectively. The ENSO may have a timescale above the 8-year band, and the PDO exhibits periodic correlation changes at a 1-year band.

Ethnoarchaeological Study on Salt-Fermented Fish in the Upper Mun River Valley, Northeast Thailand

Salt-fermented fish is a staple food item in the traditional diets of Northeast Thailand. Rural households make fermented fish by using local salt resources to preserve seasonal fish supplies, allowing them to ferment and store surplus fish for the dry season. Evidence suggests that this food preservation strategy predates modern dietary practices, and was important in the prehistoric foodways of Northeast Thailand. Using ethnoarchaeological methods, we examine and compare contemporary fermented-fish production, which relies heavily on locally made salt, with archaeological data for these same prehistoric food items and industries. Ethnographic data is compared to archaeological data from the site of Ban Non Wat and the greater Upper Mun River Valley of Northeast Thailand during the Iron Age, which demonstrates a significant increase in the procurement and production of fish and salt resources, and rice cultivation, during the 1st millennium AD. It was also a period of significant social and environmental change, with a marked climatic shift towards distinct wet and dry seasons favoring the exploitation of and reliance on seasonal supplies of fish and salt, as is done today. From this evidence, we establish a correlation between ancient and modern fish and salt production, procurement, preparation, preservation, and consumption practices.

Source and quality of dissolved organic matter in streams are reflective to land use/land cover, climate seasonality and pCO2

Sources and quality of dissolved organic matter (DOM) in streams may be largely controlled by the landscape and season. In this study, we attempted to answer three critical questions: 1) Do land use/land cover (LULC) types affect DOM characteristics? 2) Is there a seasonal fluctuation in DOM components? 3) How do DOM quality and LULC types influence aqueous carbon dioxide partial pressure (pCO2). To achieve this, we investigated the fluorescence characteristics of DOM and its implication for pCO2 in three streams draining land with different urban intensities under distinctive dry and wet seasons. Four fluorescence components were identified, including two terrestrial humic-like components, one protein-like component and one microbial humic-like component. We found a significant positive relationship of the maximum fluorescence intensity (Fmax) of the four components and fluorescence index (FI370) with urbanization intensity in both the dry and wet seasons. The mean Fmax, biological index (BIX) and FI370 all exhibited an increasing trend from upstream to downstream in the stream with highest proportions of urban and cropland. The fluorescence characteristics were negatively related to proportion of forested land in the both seasons. The terrestrial humic-like DOM was dominating in the studied streams. Moreover, the seasonality altered the DOM composition, with protein-like component emerging only in stream waters during the dry season, while microbial humic-like component exclusively occurred during the wet season. pCO2 values were positively related to terrestrial humic-like and biological protein-like components, and urban land. The dry season had much higher pCO2 than the wet season. Results from the Partial Least Squares Path (PLS-PM) models further indicated that LULC types were important in mediating fluorescence DOM whilst pCO2 was more sensitive to the direct effect from FDOM dynamics. We conclude that DOM source and quality in streams are reflective to LULC and climate seasonality, and are good indicators of pCO2 via source tracer and quality of fluorescence components.

Iron Age plant subsistence in the Inner Congo Basin (DR Congo)

Around 400 bc, pottery- and iron-producing populations immigrated into the Inner Congo Basin (ICB) and subsequently spread upstream some major tributaries of the Congo River. Until recently, their subsistence was almost completely unknown. We present an archaeobotanical study of three sites in the ICB covering parts of the Early Iron Age (ca. 400 bc-ad 650) and of the Late Iron Age (LIA) as well as subrecent times (ca. ad 1300–2000). We studied 82 flotated samples of botanical macroremains, and 68 soil phytolith samples, recovered from the terra firme sites Iyonda and Mbandaka, and the floodplain fishing camp site of Bolondo. The EIA assemblage from Iyonda yielded domesticated Cenchrus americanus (pearl millet), Vigna unguiculata (cowpea), Canarium schweinfurthii, Elaeis guineensis (oil palm), several wild plants, and parenchyma fragments tentatively attributed to Dioscorea sp. (yams). The exploitation of these plants originated in the savannas and forest-savanna ecotones of West Africa. The presence of C. americanus in LIA contexts at Bolondo and Mbandaka, dated to ca. ad 1350–1550, indicates that its cultivation is not dependent on a seasonal climate with a distinct dry season, contrary to previous views. The role of C. americanus as a staple is difficult to assess; it might have been used for special purposes, e.g. beer brewing. In spite of extensive screening, we did not detect any banana phytoliths in the EIA samples. Musa phytoliths were only present in LIA contexts after ca. ad 1400, leaving room for the possibility that the introduction and spread of Musa spp. AAB ‘Plantain’ in the ICB was a late phenomenon.

Characteristics and Predictability of Midwestern United States Drought

AbstractCharacteristics and predictability of drought in the Midwestern United States, spanning the Great Plains to the Ohio Valley, at local and regional scales are examined during 1916-2015. Given vast differences in hydroclimatic variability across the Midwest, drought is evaluated in four regions identified using a hierarchical clustering algorithm applied to an integrated drought index based on soil moisture, snow water equivalent, and three-month runoff from land surface models forced by observed analyses. Highlighting the regions containing the Ohio Valley (OV) and Northern Great Plains (NGP), the OV demonstrates a preference for sub-annual droughts, the timing of which can lead to prevalent dry epochs, while the NGP demonstrates a preference for annual-to-multi-annual droughts. Regional drought variations are closely related to precipitation, resulting in a higher likelihood of drought onset or demise during wet seasons: March-November in the NGP and all year in the OV, with a preference for March-May and September-November. Due to the distinct dry season in the NGP, there is a higher likelihood of longer drought persistence, as the NGP is four times more likely to experience drought lasting at least one year compared to the OV. While drought variability in all regions and seasons are related to atmospheric wave trains spanning the Pacific-North American sector, longer-lead predictability is limited to the OV in December-February because it is the only region/season related to slow-varying sea surface temperatures consistent with El Niño-Southern Oscillation. The wave trains in all other regions appear to be generated in the atmosphere, highlighting the importance of internal atmospheric variability in shaping Midwestern drought.

Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts

Study regionThe Sirikit Dam in the Nan River Basin is located on a main tributary of the Chao Phraya River in Thailand. Study focusThis study investigates forecasting river flows and real-time optimization of dam release using a distributed hydrological model with ensemble weather forecasting for reservoir operations which provide hydropower and irrigation facilities in Thailand during a case study of the 2019 drought event. Medium-range ensemble precipitation forecasts were employed using a hydrological model to predict the real-time reservoir inflow. Real-time optimization of the water release strategy determined a week in advance with an effective initial condition for hydropower generation and irrigation was conducted with different scenarios using dynamic programming considering inflow predictions. New hydrological insights for the regionThe medium-range ensemble precipitation forecast conducted by the European Centre for Medium Range Weather Forecasts was used to quantify precipitation for the study basin. The ensemble precipitation forecast with the hydrological model was employed for inflow prediction of the study basin which was located in a tropical climate with a distinct wet and dry season. The initial conditions of the hydrological model largely influenced the real-time inflow forecast. To determine the initial conditions of the model, the empirical data assimilation considering a drainage area factor was utilized and observed precipitation data were used for model input forcing data during the initial analysis period. This method improved the reservoir inflow prediction and real-time reservoir optimization using dynamic programming with considering ensemble forecasts provided more efficient operating decisions than employing historical data. The resulting information will be useful for water resource management, which may be adapted to other basins in the study region.

Six‐year population dynamics of seven passalid species in a humid tropical rainforest in Borneo

AbstractPhenology of insect abundance in less seasonal tropical regions is well recognized. Even in Bornean tropical forests in Malaysia, where there is no distinct dry season, there are insect species that behave as if their environments were highly seasonal. How such seasonal dynamics are shaped and what factors determine the seasonality remains largely unresolved. To elucidate the mechanisms underlying population dynamics in relatively stable tropical environments, we classified monthly samples collected with light traps at Lambir Hills National Park, Malaysia, and generated long‐term time‐series data for the family Passalidae (Coleoptera: Scarabaeoidea), which spend nearly their entire life cycle within or beneath decayed wood. Analyses of our data (20 species and 768 individuals) revealed that there were clear abundance peaks in April and October at the community level. We analyzed the data together with climate data using a nonlinear time‐series analysis called convergent cross mapping. The causal relationship between adult population dynamics of the dominant species (Leptaulax planus) and temperature was detected, which shows that the population dynamics of L. planus are driven by cool temperatures approximately 1 month before emergence. Our study indicates that even in perpetually wet tropical rainforests in Southeast Asia, insect population dynamics respond to climatic factors and show seasonal population dynamics.

Predictability of temporal variation in climate and the evolution of seasonal polyphenism in tropical butterfly communities

Phenotypic plasticity in heterogeneous environments can provide tight environment-phenotype matching. However, the prerequisite is a reliable environmental cue(s) that enables organisms to use current environmental information to induce the development of a phenotype with high fitness in a forthcoming environment. Here, we quantify predictability in the timing of precipitation and temperature change to examine how this is associated with seasonal polyphenism in tropical Mycalesina butterflies. Seasonal precipitation in the tropics typically results in distinct selective environments, the wet and dry seasons, and changes in temperature can be a major environmental cue. We sampled communities of Mycalesina butterflies from two seasonal locations and one aseasonal location. Quantifying environmental predictability using wavelet analysis and Colwell's indices confirmed a strong periodicity of precipitation over a 12-month period at both seasonal locations compared to the aseasonal one. However, temperature seasonality and periodicity differed between the two seasonal locations. We further show that: (a) most females from both seasonal locations synchronize their reproduction with the seasons by breeding in the wet season but arresting reproduction in the dry season. In contrast, all species breed throughout the year in the aseasonal location and (b) species from the seasonal locations, but not those from the aseasonal location, exhibited polyphenism in wing pattern traits (eyespot size). We conclude that seasonal precipitation and its predictability are primary factors shaping the evolution of polyphenism in Mycalesina butterflies, and populations or species secondarily evolve local adaptations for cue use that depend on the local variation in the environment.

Climatic factors and population demography in big-eared woodrat,Neotoma macrotis

AbstractChanges in temperature and rainfall patterns can have marked impacts on small mammal populations that inhabit environments with highly fluctuating water availability. With projected increases in droughts and fewer but more intense rainfall events in the Southwestern United States, the persistence of many wildlife populations may be threatened. Our goal was to assess how temperature and rainfall during distinct dry and wet seasons influenced the dynamics of a population of big-eared woodrats (Neotoma macrotis) in a mixed oak woodland of coastal central California. We applied Pradel’s temporal symmetry models to our 21-year biannual capture–mark–recapture data set (1993–2014) to determine the effects of climatic factors on the woodrats’ apparent survival (Φ) and recruitment rate (f). Monthly Φ averaged 0.945 ± 0.001 and varied with season. Monthly f was 0.064 ± 0.001 in the wet season (f was fixed to 0 in the dry season). Monthly population growth rate (λ) varied from 0.996 ± 0.001 during the dry season to 1.001 ± 0.001 during the wet season, which indicated a stable population (0.999 ± 0.001). Total rainfall from the previous season and mean temperature during the same season positively influenced Φ and f. By contrast, Φ and f were negatively influenced by mean temperature from the previous season and total rainfall in the same season. The resulting λ fluctuated with total rainfall, particularly in the wet season. Our results suggest that the big-eared woodrat population may not be substantially affected by warm temperatures per se, potentially because of the microclimate provided by its stick houses. We also discuss its adaptability to local food resources and relatively slow life history relative to other cricetids, and propose that the big-eared woodrat population may be equipped to cope with future climate change.

Assessing the impacts of climate change on irrigation diversion water requirement in the Philippines

This study assessed the impacts of climate change on diversion water requirements for irrigation system planning and development in the Philippines. Representative sites with high potential for irrigation development were selected from each of the four climatic types in the country. Cropping calendars were developed based on evapotranspiration and rainfall patterns. The CROPWAT program was used to determine the net irrigation requirement, from which the irrigation diversion requirements were derived based on estimated irrigation efficiencies. Recently published climate projections using the representative concentration pathways were used as climate change scenarios. Results of this study showed that the CROPWAT estimates of evapotranspiration were satisfactorily calibrated and validated using the eddy covariance methods. Climate change could lead to a significant increase in diversion water requirement. The increase in diversion water requirement was projected to reach + 43% during dry years, + 32% during normal years, and + 42% during wet years. A favorable reduction in diversion water requirement due to timely occurrence of rainfall was however observed at the site with distinct wet and dry season during dry years (up to − 7%), normal years (up to − 11%), and wet years (up to − 12%). The cropping patterns varied within and across climate types. The projected estimates of diversion water requirements generated in this study could be used for irrigation system planning and development particularly for assessing water storage requirements and design irrigable areas. Results could also be used as part of planning and design criteria for dams and reservoirs and thereby contribute to climate proofing of irrigation systems. The application of methods developed in this study for estimating diversion water requirements with the incorporation of climate change may be extended to other parts of the country and in other parts of the world for a more climate-resilient water resources planning.