Important Environmental Variables Research Articles

Simulation of potential suitable distribution of Alnus cremastogyne Burk. In China under climate change scenarios

Alnus cremastogyne is a broad-leaved tree species with fast-growing and promising nitrogen-fixing capacity. Its plantation is under steady growing due to the commercial and restoration importance in China. However, little is known about the effects of projected climate change on its adaptability and future distribution. In the present study, we simulated the ecological suitability of A. cremastogyne under three climate change scenarios (CCS) (i.e., SSP1-2.6, SSP2-4.5 and SSP5-8.5) in 2050 s and 2070 s using geographic information technology (GIS) and maximum entropy model (MaxEnt). The results demonstrated that under current climate situation, the highly suitable areas were mainly located in central and eastern Sichuan, most of Hunan, central and northern Jiangxi, central and eastern Guizhou, most of Chongqing and southeast Hubei, with a total area of 52.1 × 104 km2. The areas of the moderately and poorly suitable areas were 65.52 × 104 km2 and 92.99 × 104 km2, respectively. Under the future CCS, both the highly suitable area and the total suitable area of A. cremastogyne showed increasing trends, 1.22-fold and 1.57-fold higher for highly suitable area by 2050, 1.27-fold and 1.41-fold by 2070, respectively. While the areas of the poorly suitable areas would decline. Moreover, a northwestward migration of the geometric center of the total suitable area was projected. Annual precipitation (5.9–1314.5 mm), the minimum temperature of coldest month (-0.2–16.8 ℃) and the mean temperature of coldest quarter (0.7–11.7 ℃) were the three most important environmental variables determining the distribution of A. cremastogyne. Our results highlight the plasticity of A. cremastogyne to climate change and also the feasibility of intercropping with this species to improve soil nitrogen availability.

Exploring the determinants and distribution patterns of soil mattic horizon thickness in a typical alpine environment using boosted regression trees

Mattic horizon, grassroots intertwined surface horizon for soils in alpine meadow, is of great importance for alpine ecosystems with its thickness serving as a critical indicator for the extent of alpine meadow degradation. However, the distribution patterns and key environmental factors controlling mattic horizon thickness (MHT) remain unknown. We evaluated the potential of a boosted regression trees (BRT) based variable selection approach to identify the determinants of MHT, to reveal the predictor-response relationship, and to map the spatial distributions of MHT. Results showed that the selected six key environmental variables can reliably reflect the pedogenic processes of mattic horizon in such alpine environment. Among which, the most important environmental variables controlling MHT were modified soil-adjusted vegetation index 2 (relative importance of 31.9%), elevation (22.7%), followed by slope (13.2%), topographic wetness index (11.4%), relative slope position (10.4%), and mean annual precipitation (10.4%). Additionally, the BRT model using those six key variables for mapping MHT performed an acceptable prediction with R2 value of 0.447 (standard deviation of 0.019). The variable selection procedure dramatically reduced the number of environmental variables by 77% (from 26 to 6), which could not only improve computational efficiency but also significantly improve model performance with a 30.3% increase in R2. Our results demonstrate that the proposed BRT algorithm-based variable selection approach can reliably identify the determinants of MHT both statistically and pedologically. It can be used as a promising approach for revealing the predictor-response relationship, mapping the distribution patterns of MHT, and may provide a solution to map soil depth over large areas.

Ecological niche complexity of invasive and native cryptic species of the Bemisia tabaci species complex in China

Bemisia tabaci is an important pest affecting agricultural and horticultural crops worldwide and comprises a complex of cryptic species. In China, the introduction of the two invasive cryptic species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), has considerably affected the ecological niche of the native cryptic species. Based on occurrence records obtained through field surveys and high-resolution environmental data, using maximum entropy modelling, we established ecological niche models to predict the distribution of invasive and native cryptic species of B. tabaci in China and identified the differences in ecological niches. The results showed that the distribution range and niche breadth of the invasive cryptic species exceed that of the native cryptic species in the order of MED > MEAM1 > China1 > Asia1. There are different degrees of niche overlap and range overlap between cryptic species. Moreover, the important environmental variables affecting their distribution were different, as well as their response and adaptation to most environmental variables. Our results suggest that the B. tabaci species complex occupies a complex ecological niche in China. The findings improve our understanding of the ecological characteristics of B. tabaci species complex, which will be useful in the development of prevention and control strategies for this pest in China.

Modeling the current distribution suitability and future dynamics of Culicoides imicola under climate change scenarios.

BackgroundAfrican horse sickness, a transboundary and non-contagious arboviral infectious disease of equids, has spread without any warning from sub-Saharan Africa towards the Southeast Asian countries in 2020. It is imperative to predict the global distribution of Culicoides imicola (C. imicola), which was the main vector of African horse sickness virus.MethodsThe occurrence records of C. imicola were mainly obtained from the published literature and the Global Biodiversity Information Facility database. The maximum entropy algorithm was used to model the current distribution suitability and future dynamics of C. imicola under climate change scenarios.ResultsThe modeling results showed that the currently suitable habitats for C. imicola were distributed in most of the southern part areas of America, southwestern Europe, most of Africa, the coastal areas of the Middle East, almost all regions of South Asia, southern China, a few countries in Southeast Asia, and the whole Australia. Our model also revealed the important environmental variables on the distribution of C. imicola were temperature seasonality, precipitation of coldest quarter, and mean temperature of wettest quarter. Representative Concentration Pathways (RCPs) is an assumption of possible greenhouse gases emissions in the future. Under future climate change scenarios, the area of habitat suitability increased and decreased with time, and RCP 8.5 in the 2070s gave the worst prediction. Moreover, the habitat suitability of C. imicola will likely expand to higher latitudes. The prediction of this study is of strategic significance for vector surveillance and the prevention of vector-borne diseases.

Testing the applicability of random forest modeling to examine benthic foraminiferal responses to multiple environmental parameters

The main environmental variables controlling benthic foraminiferal distributions were identified and used to assess their influence on ecological indices developed as predictors of Ecological Quality Status (EcoQS) in marine ecosystems. Gradient forest and random forest models were applied to assess the predictive value of a selection of abiotic (environmental) and biotic (foraminifera) variables in a costal marine area in the central Adriatic Sea (Italy). This approach yields evidence that the predictor variables sand, silt, Pollution Load Index, and TN have the greatest influence on the distribution of benthic foraminifera in this area. In addition, we identify thresholds for the most important environmental variables that influence ecological indices. These findings contribute to efforts to determine how to best improve sediment quality and environmental stability for marine conservation. Further application of these approaches represents a useful tool for policymakers to survey the diversity of marine organisms and to improve the ability to protect and restore marine ecosystems by identifying predictors of diversity and identifying key thresholds in these predictors.

A high-resolution record of coastal clouds and fog and their role in plant distributions over San Clemente Island, California

San Clemente Island (SCI), located in the Southern California Bight, is owned and operated by the U.S. Navy and is home to endemic species, including federally threatened or endangered plants and birds. The SCI ecosystem is influenced by the presence of warm season low-level clouds that shade, cool and, especially when in the form of fog, moisten the environment. We created a new cloud and fog satellite-derived albedo product for SCI at a higher resolution than previous datasets. The record spans 23 summers (1996–2018, May - Sep). The spatial resolution is ∼1 km and the temporal resolution is half hourly (nominally 0600 to 1800 PST). Using Geostationary Operational Environmental Satellite (GOES)-WEST visible band measurements, it was discovered that small (typically on the order of less than 5 km) geographical misalignment of the satellite images was common. The biological ramifications of such a shift could be significant. Thus, to provide a useful 1 km product for a narrow island such as SCI it was necessary to correct misalignments. Misalignment of albedo was easily apparent in clear sky images at the interface of land and water. This concept was used in the automated correction. The northwest coast of SCI is the cloudiest/foggiest area. June, on average, is the cloudiest month on SCI. The intra-day variability reaches ∼20% cloud albedo while interannual and monthly variability are ∼10%. To demonstrate the records’ utility in understanding ecological phenomena and patterns, we used the dataset to model plant distributions. We found monthly mean cloud albedo values, a proxy for cloud frequency and persistence, were among the most important environmental variables in understanding plant distributions. The vegetation models indicate locations with appropriate conditions, including clouds and fog during critical periods of the year, for particular vegetation types and thus, can inform restoration and management activities.

Influence of temperature and relative humidity on the antifungal effect of 405 nm LEDs against Botrytis cinerea and Rhizopus stolonifer and their inactivation on strawberries and tomatoes

In recent years, photodynamic inactivation (PDI) has emerged as a promising preservation method to complement refrigeration in the fresh produce supply chain. However, due to infrastructural limitations in the supply chain, fresh produce is often exposed to environmental conditions rather than recommended storage conditions. Hence, this study aimed to investigate the influence of two important environmental variables in the fresh produce supply chain - temperature and relative humidity (RH), on the PDI of fruit spoilage molds. It also aimed to demonstrate proof-of-concept of their inactivation on fruit surfaces. In the in vitro stage, Botrytis cinerea and Rhizopus stolonifer, the two molds selected for this study, were illuminated with 405 nm LEDs on Dichloran Rose-Bengal Chloramphenicol (DRBC) agar at three levels of temperature (7, 16 and 25 °C) and relative humidity (40, 60 and 80%). Illumination under these conditions caused reductions greater than 94% in the mold populations, at all temperatures and relative humidities. Even so, a temperature of 25 °C was observed to be marginally better for the inactivation as compared to 7 and 16 °C, as it necessitated the lowest dose (6–7 kJ) for the first log reduction of both the molds. Similarly, an RH of 40% worked slightly better for the inactivation of B. cinerea, as it induced inactivation without any lag phase and required the lowest dose (8.03 kJ) for the first log reduction. When the antifungal effect was investigated on fruit surfaces, it was discovered that the illumination reduced the populations of B. cinerea and R. stolonifer on strawberries by 67% and 19%, whereas on tomatoes, the respective inactivations were 79% and 70% respectively. These results demonstrate further promise of PDI as a postharvest technology for reducing the risk of fruit spoilage. This study is also the first to demonstrate the potential of PDI to add value to supply chains where compliance to ideal storage conditions is not feasible.

Short-Term Effects of Forest Therapy on Mood States: A Pilot Study.

Immersion in forest environments was shown to produce beneficial effects to human health, in particular psychophysical relaxation, leading to its growing recognition as a form of integrative medicine. However, limited evidence exists about the statistical significance of the effects and their association with external and environmental variables and personal characteristics. This experimental study aimed to substantiate the very concept of forest therapy by means of the analysis of the significance of its effects on the mood states of anxiety, depression, anger and confusion. Seven forest therapy sessions were performed in remote areas and a control one in an urban park, with participants allowed to attend only one session, resulting in 162 psychological self-assessment questionnaires administered before and after each session. Meteorological comfort, the concentration of volatile organic compounds in the forest atmosphere and environmental coherence were identified as likely important external and environmental variables. Under certain conditions, forest therapy sessions performed in remote sites were shown to outperform the control session, at least for anxiety, anger and confusion. A quantitative analysis of the association of the outcomes with personal sociodemographic characteristics revealed that only sporting habits and age were significantly associated with the outcomes for certain psychological domains.

Impact of climate and land cover changes on the potential distribution of four endemic salamanders in Mexico

Anthropogenic changes, such as land use and climate change, are the greatest threats to biodiversity, especially for amphibians, which are the most endangered vertebrate class worldwide. Species distribution modelling was applied to assess how expected future climate and land cover change scenarios might influence the geographic distribution and habitat connectivity of four salamanders endemic to Mexico: Aquiloeurycea cephalica (Cope, 1865), Isthmura bellii (Gray, 1850), Pseudoeurycea robertsi (Taylor, 1939), and Pseudoeurycea leprosa (Cope, 1869). For this, the Community Climate System Model (CCSM4) with two Representative Concentration Pathways (RCP 45 and RCP 85) and two modelling methods (Maxent in ENMeval and an ensemble model in biomod2) were used. The most important environmental variables explaining the distribution of the target species, as well as the environmental niche overlap between them, were also determined. Abies forest cover was one of the most important variables explaining the current distribution of P. robertsi (contribution of 39%), P. leprosa (contribution of 18%), and A. cephalica (contribution of 22%) with a positive effect. The distribution of these three species was also limited by maximum temperatures, whereas the I. bellii distribution was more limited by minimum temperatures. The environmental niches of P. leprosa and A. cephalica were significantly similar (D = 0.637, I = 0.801, p-value = 0.02), as well as the environmental niches of P. robertsi and P. leprosa (D = 0.640, I = 0.797, p-value = 0.01). As expected, all salamander species were predicted to face a reduction in their potential distribution (reductions between 2.64 and 32.16%) and landscape connectivity (reductions between 4.93 and 73.92%) under future scenarios of climate and land cover change. Different models and scenarios were inconsistent in determining which species’ distribution would suffer the biggest reduction in the future. However, P. robertsi suffered the largest reduction in connectivity under both scenarios of climate change. Similarly, our results suggest that Sierra de las Cruces and Corredor Biológico Chichinautzin are very important areas in terms of connectivity. Unfortunately, great losses of Abies and Pinus forests were also predicted to occur in these areas between 2011 and 2014. According to these findings, the preservation of Abies forests of the Trans-Mexican Volcanic Belt is essential to preserve P. robertsi, P. leprosa, and A. cephalica salamanders, whereas the preservation of Corredor Biológico Chichinautzin and Sierra de las Cruces is essential to maintain landscape connectivity for P. leprosa, A. cephalica, and I. bellii. Thus, these areas should be prioritized in conservation programs.

Changes in the Habitat Preference of Crested Ibis (Nipponia nippon) during a Period of Rapid Population Increase.

Simple SummaryIn 1981, the crested ibis (Nipponia nippon) was a critically endangered bird with only two pairs left in the world. Now, numbers have increased, and it has been reintroduced to many places in China, Japan, and Korea. In the breeding season, the crested ibis has high food needs (fish, freshwater invertebrate, etc.) to feed nestlings, and it prefers areas with rice paddies and waterbodies near to trees for nesting. We compared nest site preference from 1981 to 2019, and found that nest sites moved closer to houses of local farmers. In the 1980s, crested ibises only lived in remote mountain areas, where the farmers were too poor to afford pesticide and fertilizer, and consequently rice paddies contained substantial fish populations. In the meantime, the massive use of pesticides in more populated areas had caused the collapse of fish populations. A pesticide ban was enforced from 1981 on, when the crested ibis was rediscovered, and the freshwater biodiversity gradually recovered. The crested ibis returned to lower and more populated areas containing their ancestral habitats with large areas of wetlands.The number of breeding pairs of crested ibis (Nipponia nippon) in Hanzhong, China has recovered remarkably from 2 to 511 from 1981 to 2019. Although the crested ibis has been closely monitored, the habitat preference of the bird has not been well studied despite the extensive increase in abundance. We used nest site data from the past 39 years and 30 environmental variables to develop species distribution models for each year. We applied random forest to select important environmental variables, and used logistic regressions to quantify the changes in habitat preferences in 39 years, taking into account the effects of interaction and quadratic terms. We found that six variables had strong impacts on nest site selection. The interaction term of rice paddies and waterbodies, and the quadratic term of precipitation of the wettest quarter of the year were the most important correlates of nest presence. Human impact at nest sites changed from low to high as birds increased their use of ancestral habitats with abundant rice paddies. We concluded that during the population recovery, the crested ibises retained their dependence on wetlands, yet moved from remote areas to populated rural regions where food resources had recovered due to the ban of pesticide use.

Evaluation of Classification Algorithms to Predict Largemouth Bass (Micropterus salmoides) Occurrence

This study aimed to evaluate classification algorithms to predict largemouth bass (Micropterus salmoides) occurrence in South Korea. Fish monitoring and environmental data (temperature, precipitation, flow rate, water quality, elevation, and slope) were collected from 581 locations throughout four major river basins for 5 years (2011–2015). Initially, 13 classification models built in the caret package were evaluated for predicting largemouth bass occurrence. Based on the accuracy (>0.8) and kappa (>0.5) criteria, the top three classification algorithms (i.e., random forest (rf), C5.0, and conditional inference random forest) were selected to develop ensemble models. However, combining the best individual models did not work better than the best individual model (rf) at predicting the frequency of largemouth bass occurrence. Additionally, annual mean temperature (12.1 °C) and fall mean temperature (13.6 °C) were the most important environmental variables to discriminate the presence and absence of largemouth bass. The evaluation process proposed in this study will be useful to select a prediction model for the prediction of freshwater fish occurrence but will require further study to ensure ecological reliability.

Through the Boundaries: Environmental Factors Affecting Reef Benthic Cover in Marine Protected Areas in the Philippines

Philippine coral reefs have been on the decline since the 1970s, and this degradation has posed a risk to biodiversity, food security, and livelihood in the country. In an effort to arrest this degradation, marine protected areas (MPAs) were established across the country. MPAs are known to improve fish biomass, but their effect on live coral cover and other benthos is not yet well documented and understood. In this study, 28 MPAs across the Philippines were surveyed comparing benthic cover and indices between protected reefs and adjacent unprotected reefs. No consistent differences were found between reefs inside and outside MPAs through all the benthic categories and reef health indices considered that are indicative of protection effects or recovery within MPAs. However, there were notable site-specific differences in benthic cover across the study MPAs-suggesting that factors other than protection play important roles in influencing benthic cover inside and outside of MPAs. Storm frequency and proximity to rivers, as a proxy for siltation, were the strongest negative correlates to live coral cover. Also, high coastal population, a proxy for pollution, and occurrence of blast and poison fishing positively correlated with high dead coral cover. The lack of significant difference in benthic cover between reefs inside and outside MPAs suggests that protection does not necessarily guarantee immediate improvement in benthic condition. Correlations between benthic condition and storm frequency, siltation, and pollution suggest that it is necessary to augment MPAs with other management strategies that will address the multiple stressors that are usually indiscriminate of MPA boundaries. Supplementing long-term and systematic monitoring of benthic cover and biodiversity inside and outside of MPAs with data on other important environmental and human impact variables will help improve understanding of benthic cover and biodiversity dynamics inside and outside of MPA boundaries.

Predicting the potential habitat of Russian-Olive (Elaeagnus angustifolia) in urban landscapes

Russian-olive (Elaeagnus angustifolia) is a species native to southern Europe and central and eastern Asia. This species plays an important role in urban landscape design because of its rapid growth, resistance in harsh climates and tolerance to human-caused pressure. Understanding its potential dispersal and restricting parameters are the first steps toward the sustainable use of this species. Here, we used Species Distribution Models to predict the potential distribution of Russian-olive in Iran climate and estimate the possible limiting factors for its spread. Our results highlighted the importance of environmental variables including climatic factors, soil, and lithology in the distribution of this species throughout the country. According to these results, suitable habitats for Russian-olive are located in the north of Iran along the Alborz and Koppeh-Dagh mountain ranges. Therefore, the suitable habitats for this species are limited to only nine percent of the country. A habitat suitability map can be used to evaluate future developments in urban areas and predict the dispersal range of Russian-olive in Iran. Our results show that Russian-olive can be used to create new green spaces in urban climates in the northern regions of Iran.

Potential impact of climate change on the distribution of some selected legumes in Cameroon and adjoining Nigeria border

AbstractOrganismal response to climate change may affect long‐term conservation plans. However, how climate change affects the distribution and conservation status of some plant species is still being debated. To test this, we selected four economically important legume species (Adenocarpus mannii, Afzelia bella, Afzelia bipindensis and Baphia nitida) from the Nigeria–Cameroon border in West Africa. The link between climate change and the species distribution range was predicted using the ensemble species distribution model (ESDM). Our analyses revealed the precipitation of the coldest period (50%) and precipitation of the driest period (40%) as the most important environmental variables influencing the distribution of the studied species. The projection shows independent habitat shifts (gain/loss) of the species consequent to climate change in the future (2050 and 2070). Despite the restricted coverage of occupancy for the selected species, our estimated species distribution range from the ESDM agrees with the current IUCN conservation status (least concern) for A. mannii. Hence, our results suggest that species distribution modelling at local habitats could yield insights into global species conservation assessments. Our findings highlighted the need for conservation through regulated land use in Dibombari highland, Cameroon Mountain (Cameroon) and the forests around Oban hills in Nigeria due to projected high species loss consequent to climate change. Thus, we recommend ecological niche modelling with extensive field surveys across the entire geographic range of these species for robust inferences that allow comparisons with the IUCN status.

Modelling European turtle dove (Streptopelia turtur L. 1758) distribution in the south eastern Iberian Peninsula

The European turtle dove population and breeding range has declined sharply in Spain. This study reanalyses data from the Atlas of Breeding Birds in Alicante (SE Spain), aiming to identify the main variables related to its occurrence and abundance. We used hierarchical partitioning analysis to identify important environmental variables associated with natural vegetation, farming, hydrological web, anthropic presence, climate, and topography. Analysis combining the most explicative variables of each group identified the mixture of pines and scrubland in the semiarid areas and the length of unpaved roads as the most important variables with a positive effect on occurrence, while herbaceous crops and scrublands in dry ombrotype climate areas had the most important negative effect. Abundance was related only to the availability of water points. We discuss the implications of these findings for habitat management in conservation of this species.

Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models

Habitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.

Mapping soil erodibility in southeast China at 250 m resolution: Using environmental variables and random forest regression with limited samples

Soil erodibility (K factor) mapping has been accomplished mainly by soil map-linked or geo-statistical interpolation. However, the resulting maps usually have coarse spatial resolution at a regional scale. The objectives of this study were a) to map the K factors using a set of environmental variables and random forest (RF) model, and b) to identify the important environmental variables in the predictive mapping on a regional scale. We collected 101 surface soil samples across southeast China in the summer of 2019. For each sample, we measured the particle size distribution and organic matter content, and calculated the K factors using the nomograph equation. The hyperparameters of RF were optimized through 5-fold cross validation (mtry = 2, ntree = 500, p = 63), and a digital map with 250 m resolution was generated for the K factor. The lower and upper limits of a 90% prediction interval were also produced for uncertainty analysis. It was found that the important environmental variables for the K factor prediction were relief, climate, land surface temperature and vegetation indexes. Since the existing K factor map has an average polygonal area of 6.8 km2, our approach dramatically improves the spatial resolution of the K factor to 0.0625 km2. The new method captures more distinct differences in spatial details, and the spatial distribution of the K factor derived from RF prediction followed a similar pattern with kriging interpolation. This suggests the presented approach in this study is effective for mapping the K factor with limited sampling data.

Seasonal variation of morphological traits, wood formation, and soil properties differs between Quercus robur L. and Robinia pseudoacacia L. saplings

ABSTRACT Climate seasonality is one of the important environmental variables that can drive changes in many properties of trees. However, how different tree species regulate their growth and development during changes of the growing period particularly at sapling stage is little known. This study, therefore, evaluated how morphological, anatomical, and soil properties differed in two growing season periods (March vs. September) between oak and black locust saplings across one growing season. Wood cell anatomical properties and soil characteristics were considerably influenced by seasonality. Each species showed greater wood cell anatomical characteristics in March than in September. Soil physical and chemical properties also showed great variance between March and September: soil pH, amount of Mg and Al concentrations in soil were higher in March while organic matter and total N concentration in soil showed greater values in September. Growth and development performance were also compared between two species. We found fibre cell characteristics, stem height, stem diameter and node number were to be greater in oak than in black locust for both early- and late growing periods. The results suggested that oak showed better adaptation to their local environments than black locust.

Patterns of rare moss diversity and distribution in Alberta

Rare moss diversity and distribution patterns are described for the province of Alberta. Multivariate analyses were used to elucidate the distribution patterns of the rare mosses in relation to environmental factors, in comparison with those of the common mosses. Hierarchical clustering of species occurrence among Alberta ecoregions resulted in 11 species groups having similar distributions and four ecoregion groups with similar species composition. Rare and common mosses show comparable distributions at the geographic scale of ecoregions; the analyses did not provide support that rare mosses respond to environment factors differently than common mosses. The rare mosses are more narrowly distributed among the species and ecoregion groups than are common species. The most important environmental variables determining species distributions are mean annual temperature and growing degree days. Other important factors determining moss distribution are mean elevation, annual rainfall, and mountain landscape. Diversity patterns are shown to vary widely among the ecoregions and to differ between rare and common species. Rare species are especially diverse in the Rocky Mountains, which support 81% of the province’s known rare moss flora and reflect a complex of diverse landscapes for moss colonization. Only 40% of known rare species in Alberta are found in nonmountainous regions.

MaxEnt Modeling Based on CMIP6 Models to Project Potential Suitable Zones for Cunninghamia lanceolata in China

Cunninghamia lanceolata (Lamb.) Hook. (Chinese fir) is one of the main timber species in Southern China, which has a wide planting range that accounts for 25% of the overall afforested area. Moreover, it plays a critical role in soil and water conservation; however, its suitability is subject to climate change. For this study, the appropriate distribution area of C. lanceolata was analyzed using the MaxEnt model based on CMIP6 data, spanning 2041–2060. The results revealed that (1) the minimum temperature of the coldest month (bio6), and the mean diurnal range (bio2) were the most important environmental variables that affected the distribution of C. lanceolata; (2) the currently suitable areas of C. lanceolata were primarily distributed along the southern coastal areas of China, of which 55% were moderately so, while only 18% were highly suitable; (3) the projected suitable area of C. lanceolata would likely expand based on the BCC-CSM2-MR, CanESM5, and MRI-ESM2-0 under different SSPs spanning 2041–2060. The increased area estimated for the future ranged from 0.18 to 0.29 million km2, where the total suitable area of C. lanceolata attained a maximum value of 2.50 million km2 under the SSP3-7.0 scenario, with a lowest value of 2.39 million km2 under the SSP5-8.5 scenario; (4) in combination with land use and farmland protection policies of China, it is estimated that more than 60% of suitable land area could be utilized for C. lanceolata planting from 2041–2060 under different SSP scenarios. Although climate change is having an increasing influence on species distribution, the deleterious impacts of anthropogenic activities cannot be ignored. In the future, further attention should be paid to the investigation of species distribution under the combined impacts of climate change and human activities.