Pub Date : 2023-12-23DOI: 10.3390/ecologies5010001
Anna M. Pieri, J. L. Harris, Mickey W. Matthews, Shawn W. Hodges, Ashley R. Rodman, Jennifer L. Bouldin, A. Christian
Historically, 23 freshwater mussel species have been documented from the Buffalo National River (BNR), a 246 km, free-flowing river in northern Arkansas. The potential threats to BNR include land use/land cover changes, eutrophication, recreation, physical habitat changes, and various climate change-related effects. Twelve quantitative mussel bed sites were established and then sampled using a stratified random sampling protocol to evaluate the long-term changes between 2006 and 2020–2021 in population and assemblage characteristics. We compared (1) overall mussel bed persistence, sampling confidence levels and study-wide relative abundances, and compared species’ size and size-frequency distributions; (2) 10 overall site assemblage variables using paired t-tests; (3) site-level mean density, richness, and diversity indices using pair-wise Mann–Whitney U statistics; and (4) assemblage composition using Non-Metric Multidimensional Scaling. The major findings included the following: (1) sampling efforts based on a targeted 80% confidence level appears relatively robust, (2) BNR mussel assemblage composition and structure were relatively stable (however, small mussel bed persistence is a concern), (3) 7 of 23 sites were outliers based on freshwater mussel composition and habitat characteristics, and (4) assemblage composition changed with three species declining (Actinonaias ligamentina, Lasmigona costata, and Ptychobranchus occidentalis) and four species increasing (Cambarunio hesperus, Cyclonaias tuberculata, Eurynia dilatata, and Venustaconcha pleasii) between monitoring events.
{"title":"Comparisons of Twelve Freshwater Mussel Bed Assemblages Quantitatively Sampled at a 15-year Interval in the Buffalo National River, Arkansas, USA","authors":"Anna M. Pieri, J. L. Harris, Mickey W. Matthews, Shawn W. Hodges, Ashley R. Rodman, Jennifer L. Bouldin, A. Christian","doi":"10.3390/ecologies5010001","DOIUrl":"https://doi.org/10.3390/ecologies5010001","url":null,"abstract":"Historically, 23 freshwater mussel species have been documented from the Buffalo National River (BNR), a 246 km, free-flowing river in northern Arkansas. The potential threats to BNR include land use/land cover changes, eutrophication, recreation, physical habitat changes, and various climate change-related effects. Twelve quantitative mussel bed sites were established and then sampled using a stratified random sampling protocol to evaluate the long-term changes between 2006 and 2020–2021 in population and assemblage characteristics. We compared (1) overall mussel bed persistence, sampling confidence levels and study-wide relative abundances, and compared species’ size and size-frequency distributions; (2) 10 overall site assemblage variables using paired t-tests; (3) site-level mean density, richness, and diversity indices using pair-wise Mann–Whitney U statistics; and (4) assemblage composition using Non-Metric Multidimensional Scaling. The major findings included the following: (1) sampling efforts based on a targeted 80% confidence level appears relatively robust, (2) BNR mussel assemblage composition and structure were relatively stable (however, small mussel bed persistence is a concern), (3) 7 of 23 sites were outliers based on freshwater mussel composition and habitat characteristics, and (4) assemblage composition changed with three species declining (Actinonaias ligamentina, Lasmigona costata, and Ptychobranchus occidentalis) and four species increasing (Cambarunio hesperus, Cyclonaias tuberculata, Eurynia dilatata, and Venustaconcha pleasii) between monitoring events.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"9 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139162383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-13DOI: 10.3390/ecologies4040050
Sam M. Driver, Cord B. Eversole, Daniel R. Unger, D. Kulhavy, Christopher M. Schalk, I-Kuai Hung
Anaxyrus microscaphus (The Arizona Toad) is an at-risk species that is endemic to the southwestern United States. Despite conservation concerns, little is known about the ecological drivers of its distribution and habitat use. We investigated the potential distribution of A. microscaphus at the range-wide scale and local scales (i.e., Zion National Park), using MaxEnt to model habitat suitability under current and future climate scenarios. Our models incorporated 12 environmental variables, including climatic, geomorphological, and remotely sensed data. The results showed good model accuracy, with temperature and elevation being the top contributing variables. Currently, 42.6% of the park’s area provides a suitable habitat for A. microscaphus, but projections for 2050 and 2070 indicate a significant reduction in suitable habitat across its range. Temperature was the most influential variable, with habitat suitability decreasing as the annual mean temperatures exceeded 10 °C. Precipitation, vegetation, and topography variables also significantly contributed to the models. The most suitable habitat within Zion National Park occurred along sloped rivers and streams and in valleys with sandy soils, emphasizing the importance of riparian habitat conservation for A. microscaphus survival and persistence. As climate change progresses, the species’ habitat is expected to become increasingly constrained across local and range-wide scales. Our models demonstrated a shift in the suitable habitat towards major river systems, indicating a potential reliance on larger permanent river systems as smaller, more ephemeral habitats decrease in size and abundance. Future management strategies should prioritize conserving and enhancing the resilience of these habitats. MaxEnt models can guide population survey efforts and facilitate the identification of priority conservation areas, saving time and resources for species of concern such as A. microscaphus. Further research, including field surveys and large-scale analyses, is necessary to further refine our understanding of this species’ distribution and how it may be impacted by climate and habitat change.
{"title":"Assessing the Impacts of Climate Change on the At-Risk Species Anaxyrus microscaphus (The Arizona Toad): A Local and Range-Wide Habitat Suitability Analysis","authors":"Sam M. Driver, Cord B. Eversole, Daniel R. Unger, D. Kulhavy, Christopher M. Schalk, I-Kuai Hung","doi":"10.3390/ecologies4040050","DOIUrl":"https://doi.org/10.3390/ecologies4040050","url":null,"abstract":"Anaxyrus microscaphus (The Arizona Toad) is an at-risk species that is endemic to the southwestern United States. Despite conservation concerns, little is known about the ecological drivers of its distribution and habitat use. We investigated the potential distribution of A. microscaphus at the range-wide scale and local scales (i.e., Zion National Park), using MaxEnt to model habitat suitability under current and future climate scenarios. Our models incorporated 12 environmental variables, including climatic, geomorphological, and remotely sensed data. The results showed good model accuracy, with temperature and elevation being the top contributing variables. Currently, 42.6% of the park’s area provides a suitable habitat for A. microscaphus, but projections for 2050 and 2070 indicate a significant reduction in suitable habitat across its range. Temperature was the most influential variable, with habitat suitability decreasing as the annual mean temperatures exceeded 10 °C. Precipitation, vegetation, and topography variables also significantly contributed to the models. The most suitable habitat within Zion National Park occurred along sloped rivers and streams and in valleys with sandy soils, emphasizing the importance of riparian habitat conservation for A. microscaphus survival and persistence. As climate change progresses, the species’ habitat is expected to become increasingly constrained across local and range-wide scales. Our models demonstrated a shift in the suitable habitat towards major river systems, indicating a potential reliance on larger permanent river systems as smaller, more ephemeral habitats decrease in size and abundance. Future management strategies should prioritize conserving and enhancing the resilience of these habitats. MaxEnt models can guide population survey efforts and facilitate the identification of priority conservation areas, saving time and resources for species of concern such as A. microscaphus. Further research, including field surveys and large-scale analyses, is necessary to further refine our understanding of this species’ distribution and how it may be impacted by climate and habitat change.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"103 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.3390/ecologies4040049
N. Munyai, Abel Ramoelo, S. Adelabu, Hugo Bezuidehout, Hassan Sadiq
The relationship between plant productivity, measured according to biomass and species richness, is a fundamental focal point in community ecology, as it provides the basis for understanding plant responses or adaptive strategies. Although studies have been conducted on plant biomass and environmental factors, research concerning mountainous grassland areas is scarce. Therefore, the aim of the present study was to examine the influence of environmental factors on aboveground plant biomass in the mountainous grassland of the Mountain Zebra National Park, South Africa. Biomass distribution was uneven within the park, owing to certain species having relatively higher biomass values. These differences may be attributed to the chemical and physical properties of the soil, including carbon and nitrogen content, soil pH, and soil texture (sand, silt, and coarse fragments). A disc pasture meter was used to collect biomass data. Multiple regression analysis revealed that most environmental factors did not significantly influence plant biomass. The only environmental factor influencing plant biomass was soil pH; the influences of other factors were not statistically significant. The results of this study elucidate the interactions of environmental factors with plant biomass. Future research could investigate how environmental factors influence plant biomass, both below and above the ground in mountainous grassland.
{"title":"Effects of Environmental Factors on Plant Productivity in the Mountain Grassland of the Mountain Zebra National Park, Eastern Cape, South Africa","authors":"N. Munyai, Abel Ramoelo, S. Adelabu, Hugo Bezuidehout, Hassan Sadiq","doi":"10.3390/ecologies4040049","DOIUrl":"https://doi.org/10.3390/ecologies4040049","url":null,"abstract":"The relationship between plant productivity, measured according to biomass and species richness, is a fundamental focal point in community ecology, as it provides the basis for understanding plant responses or adaptive strategies. Although studies have been conducted on plant biomass and environmental factors, research concerning mountainous grassland areas is scarce. Therefore, the aim of the present study was to examine the influence of environmental factors on aboveground plant biomass in the mountainous grassland of the Mountain Zebra National Park, South Africa. Biomass distribution was uneven within the park, owing to certain species having relatively higher biomass values. These differences may be attributed to the chemical and physical properties of the soil, including carbon and nitrogen content, soil pH, and soil texture (sand, silt, and coarse fragments). A disc pasture meter was used to collect biomass data. Multiple regression analysis revealed that most environmental factors did not significantly influence plant biomass. The only environmental factor influencing plant biomass was soil pH; the influences of other factors were not statistically significant. The results of this study elucidate the interactions of environmental factors with plant biomass. Future research could investigate how environmental factors influence plant biomass, both below and above the ground in mountainous grassland.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":" 924","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138610440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-23DOI: 10.3390/ecologies4040048
T. Marler
Translocation of endangered plant species and facilitating in situ regeneration require knowledge of the factors that define suitable habitat characteristics. Four approaches were employed to define how antecedent and contemporary plant identity influenced Cycas seedling growth and survival in Guam, Yap, and the Philippines. Cycas micronesica K.D. Hill or Cycas nitida K.D. Hill & A. Lindstr. seedlings growing beneath the canopy of the maternal parent tree reached 100% mortality in 4 to 8 year. Cycas micronesica seedlings planted beneath a conspecific male adult tree reached 68% mortality in two years while seedlings planted away from a conspecific individual exhibited 100% survival. Cycas micronesica seedlings planted beneath monostands of invasive Leucaena leucocephala (Lam.) de Wit or Vitex parviflora Juss. reached 40% mortality in two years while seedlings planted in adjacent native forest cover exhibited 100% survival. Cycas micronesica seedlings planted in soil conditioned for 9 months by conspecifics, heterospecific native species, Carica papaya L., L. leucocephala, or V. parviflora exhibited the greatest growth in the soils conditioned by heterospecific natives and the least growth in the soils conditioned by the three invasive species. The seedlings growing in soil conditioned by conspecifics exhibited the most coralloid roots and the greatest shoot:root ratio. These studies confirmed that the identity of antecedent and competitive plants strongly influenced the longevity and growth of Cycas seedlings. Conservationists may improve outcomes by avoiding degraded forests that have experienced invasive plant species when positioning translocation projects. Planting Cycas seedlings in biodiverse native forest but away from a conspecific individual may lead to the greatest success in population recovery.
迁移濒危植物物种和促进就地再生需要了解确定适宜栖息地特征的因素。我们采用了四种方法来确定关岛、雅浦和菲律宾的前世和当代植物特征如何影响苏铁幼苗的生长和存活。在母本树冠下生长的苏铁小乔木（Cycas micronesica K.D. Hill）或苏铁大乔木（Cycas nitida K.D. Hill & A. Lindstr.种植在同种雄性成年树下的苏铁幼苗在两年内的死亡率为68%，而种植在远离同种个体的地方的幼苗的存活率为100%。栽种在外来入侵的 Leucaena leucocephala (Lam.) de Wit 或 Vitex parviflora Juss.单株树下的苏铁树苗，两年内死亡率达到 40%，而栽种在邻近原生林覆盖物上的树苗存活率为 100%。在同种、异种本地物种、木瓜（Carica papaya L.）、白花蛇舌草（L. leucocephala）或西洋牡荆（Vitex parviflora Juss）调节过的土壤中种植 9 个月的苏铁幼苗，在异种本地物种调节过的土壤中生长最快，而在三种入侵物种调节过的土壤中生长最慢。在同种土壤中生长的幼苗表现出最多的珊瑚状根和最大的芽根比。这些研究证实，前生植物和竞争植物的身份对苏铁幼苗的寿命和生长有很大影响。保护主义者在定位迁移项目时，可以避开曾遭受入侵植物物种侵袭的退化森林，从而改善结果。在生物多样性丰富的原生林中种植苏铁幼苗，但远离同种个体，可能会在种群恢复方面取得最大成功。
{"title":"Soil Conditioning and Neighbor Identity Influence on Cycas Seedling Performance","authors":"T. Marler","doi":"10.3390/ecologies4040048","DOIUrl":"https://doi.org/10.3390/ecologies4040048","url":null,"abstract":"Translocation of endangered plant species and facilitating in situ regeneration require knowledge of the factors that define suitable habitat characteristics. Four approaches were employed to define how antecedent and contemporary plant identity influenced Cycas seedling growth and survival in Guam, Yap, and the Philippines. Cycas micronesica K.D. Hill or Cycas nitida K.D. Hill & A. Lindstr. seedlings growing beneath the canopy of the maternal parent tree reached 100% mortality in 4 to 8 year. Cycas micronesica seedlings planted beneath a conspecific male adult tree reached 68% mortality in two years while seedlings planted away from a conspecific individual exhibited 100% survival. Cycas micronesica seedlings planted beneath monostands of invasive Leucaena leucocephala (Lam.) de Wit or Vitex parviflora Juss. reached 40% mortality in two years while seedlings planted in adjacent native forest cover exhibited 100% survival. Cycas micronesica seedlings planted in soil conditioned for 9 months by conspecifics, heterospecific native species, Carica papaya L., L. leucocephala, or V. parviflora exhibited the greatest growth in the soils conditioned by heterospecific natives and the least growth in the soils conditioned by the three invasive species. The seedlings growing in soil conditioned by conspecifics exhibited the most coralloid roots and the greatest shoot:root ratio. These studies confirmed that the identity of antecedent and competitive plants strongly influenced the longevity and growth of Cycas seedlings. Conservationists may improve outcomes by avoiding degraded forests that have experienced invasive plant species when positioning translocation projects. Planting Cycas seedlings in biodiverse native forest but away from a conspecific individual may lead to the greatest success in population recovery.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"125 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139243107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.3390/ecologies4040047
Tamirat Solomon, Vaishali Gupta, Chris Major Ncho
Livestock production, as one of the oldest and most significant human activities, plays a vital role in fulfilling the global demand for human nutrition and other animal-related products while contributing to poverty reduction. However, it is also important to address the environmental impact of livestock animals. Over 60% of the global biomass harvested annually to support human activity is directed towards this sector, raising concerns about its sustainability. In addition to substantial water and fertilizer usage reported in recent years, it is estimated that 14.5% of global greenhouse gas emissions are generated by the livestock sector. Furthermore, the increasing amount of manure resulting from intensive animal farming raises concerns about its disposal and potential water pollution. The degradation of pasture and rangeland is another significant contributor to soil erosion. Multiple approaches are being studied to reduce the environmental impact of livestock production, but a sustainable alternative may be through forestry. Forests play a vital role in countering livestock emissions by absorbing billions of tons of carbon dioxide each year, and they act as a crucial carbon sink. Furthermore, the diversity and age of forests impact the carbon sequestration process. Forests also help to combat climate change by reducing soil erosion and regulating the water cycle. As such, sustainable forest management is essential as forests provide multiple benefits, including economic, environmental, and social benefits, while also sequestering carbon. In this review, the current impact of modern livestock production is described, along with the potential for mitigating it through forestry-based solutions.
{"title":"Balancing Livestock Environmental Footprints with Forestry-Based Solutions: A Review","authors":"Tamirat Solomon, Vaishali Gupta, Chris Major Ncho","doi":"10.3390/ecologies4040047","DOIUrl":"https://doi.org/10.3390/ecologies4040047","url":null,"abstract":"Livestock production, as one of the oldest and most significant human activities, plays a vital role in fulfilling the global demand for human nutrition and other animal-related products while contributing to poverty reduction. However, it is also important to address the environmental impact of livestock animals. Over 60% of the global biomass harvested annually to support human activity is directed towards this sector, raising concerns about its sustainability. In addition to substantial water and fertilizer usage reported in recent years, it is estimated that 14.5% of global greenhouse gas emissions are generated by the livestock sector. Furthermore, the increasing amount of manure resulting from intensive animal farming raises concerns about its disposal and potential water pollution. The degradation of pasture and rangeland is another significant contributor to soil erosion. Multiple approaches are being studied to reduce the environmental impact of livestock production, but a sustainable alternative may be through forestry. Forests play a vital role in countering livestock emissions by absorbing billions of tons of carbon dioxide each year, and they act as a crucial carbon sink. Furthermore, the diversity and age of forests impact the carbon sequestration process. Forests also help to combat climate change by reducing soil erosion and regulating the water cycle. As such, sustainable forest management is essential as forests provide multiple benefits, including economic, environmental, and social benefits, while also sequestering carbon. In this review, the current impact of modern livestock production is described, along with the potential for mitigating it through forestry-based solutions.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":" 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial light at night (ALAN) demonstrated a new ecological factor that influences organisms through a multi-approach. Yet, the impacts of ALAN on understory plants remain largely unknown. We evaluated whether ALAN would affect the leaf mass per area (LMA) of understory plants through a two-year field light experiment in a tropical rubber plantation in south China. We hypothesized that ALAN could impact the understory in two ways: by directly supplementing light to aboveground plant parts (which increases LMA) and indirectly affecting soil nutrient composition by attracting insects (which decreases LMA). We selected two species: Colocasia gigantea, representing shade-tolerant species, and Melastoma candidum, representing light-demanding species. We measured canopy openness, LMA, soil nutrients, and individual distance away from light resources. Our Bayesian linear mixed model showed a negative relationship between LMA and the strength of ALAN, indicating that ALAN may influence LMA more indirectly by enhancing soil nutrient availability rather than directly acting as a light resource. This relationship was significant for Colocasia gigantea but not for Melastoma candidum. These results suggest that ALAN might have complex and species-specific impacts on the understory ecosystem. Our study underscores the need for continued research and informed management of anthropogenic ecosystems.
{"title":"Artificial Light at Night (ALAN) Influences Understory Plant Traits through Ecological Processes: A Two-Year Experiment in a Rubber Plantation in China","authors":"Cong Zhou, Akihiro Nakamura, Xiaoyang Song, Masatoshi Katabuchi","doi":"10.3390/ecologies4040046","DOIUrl":"https://doi.org/10.3390/ecologies4040046","url":null,"abstract":"Artificial light at night (ALAN) demonstrated a new ecological factor that influences organisms through a multi-approach. Yet, the impacts of ALAN on understory plants remain largely unknown. We evaluated whether ALAN would affect the leaf mass per area (LMA) of understory plants through a two-year field light experiment in a tropical rubber plantation in south China. We hypothesized that ALAN could impact the understory in two ways: by directly supplementing light to aboveground plant parts (which increases LMA) and indirectly affecting soil nutrient composition by attracting insects (which decreases LMA). We selected two species: Colocasia gigantea, representing shade-tolerant species, and Melastoma candidum, representing light-demanding species. We measured canopy openness, LMA, soil nutrients, and individual distance away from light resources. Our Bayesian linear mixed model showed a negative relationship between LMA and the strength of ALAN, indicating that ALAN may influence LMA more indirectly by enhancing soil nutrient availability rather than directly acting as a light resource. This relationship was significant for Colocasia gigantea but not for Melastoma candidum. These results suggest that ALAN might have complex and species-specific impacts on the understory ecosystem. Our study underscores the need for continued research and informed management of anthropogenic ecosystems.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":" 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-28DOI: 10.3390/ecologies4040045
Tiago Monteiro Condé, Niro Higuchi, Adriano José Nogueira Lima, Moacir Alberto Assis Campos, Jackelin Dias Condé, André Camargo de Oliveira, Dirceu Lucio Carneiro de Miranda
Forest phytophysiognomies have specific spatial patterns that can be mapped or translated into spectral patterns of vegetation. Regions of spectral similarity can be classified by reference to color, tonality or intensity of brightness, reflectance, texture, size, shape, neighborhood influence, etc. We evaluated the power of accuracy of supervised classification algorithms via per-pixel (maximum likelihood) and geographic object-based image analysis (GEOBIA) for distinguishing spectral patterns of the vegetation in the northern Brazilian Amazon. A total of 280 training samples (70%) and 120 validation samples (30%) of each of the 11 vegetation cover and land-use classes (N = 4400) were classified based on differences in their visible (RGB), near-infrared (NIR), and medium infrared (SWIR 1 or MIR) Landsat 8 (OLI) bands. Classification by pixels achieved a greater accuracy (Kappa = 0.75%) than GEOBIA (Kappa = 0.72%). GEOBIA, however, offers a greater plasticity and the possibility of calibrating the spectral rules associated with vegetation indices and spatial parameters. We conclude that both methods enabled precision spectral separations (0.45–1.65 μm), contributing to the distinctions between forest phytophysiognomies and land uses—strategic factors in the planning and management of natural resources in protected areas in the Amazon region.
{"title":"Spectral Patterns of Pixels and Objects of the Forest Phytophysiognomies in the Anauá National Forest, Roraima State, Brazil","authors":"Tiago Monteiro Condé, Niro Higuchi, Adriano José Nogueira Lima, Moacir Alberto Assis Campos, Jackelin Dias Condé, André Camargo de Oliveira, Dirceu Lucio Carneiro de Miranda","doi":"10.3390/ecologies4040045","DOIUrl":"https://doi.org/10.3390/ecologies4040045","url":null,"abstract":"Forest phytophysiognomies have specific spatial patterns that can be mapped or translated into spectral patterns of vegetation. Regions of spectral similarity can be classified by reference to color, tonality or intensity of brightness, reflectance, texture, size, shape, neighborhood influence, etc. We evaluated the power of accuracy of supervised classification algorithms via per-pixel (maximum likelihood) and geographic object-based image analysis (GEOBIA) for distinguishing spectral patterns of the vegetation in the northern Brazilian Amazon. A total of 280 training samples (70%) and 120 validation samples (30%) of each of the 11 vegetation cover and land-use classes (N = 4400) were classified based on differences in their visible (RGB), near-infrared (NIR), and medium infrared (SWIR 1 or MIR) Landsat 8 (OLI) bands. Classification by pixels achieved a greater accuracy (Kappa = 0.75%) than GEOBIA (Kappa = 0.72%). GEOBIA, however, offers a greater plasticity and the possibility of calibrating the spectral rules associated with vegetation indices and spatial parameters. We conclude that both methods enabled precision spectral separations (0.45–1.65 μm), contributing to the distinctions between forest phytophysiognomies and land uses—strategic factors in the planning and management of natural resources in protected areas in the Amazon region.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"36 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136160518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wildlife communities are positively affected by ecological restoration and reforestation. Understanding the dynamics of mammal communities along a gradient of a human-dominated habitat to a protected habitats, right up to a reforestation habitat, is crucial for assessing the effects of reforestation on conservation biology and disease ecology. We used data obtained from a set of camera traps and live traps implemented in the “Spillover Interface” project. A network analysis showed that the reforested area was central in the sharing of mammal species between human-dominated habitats, such as plantations, and the protected area. A network analysis also confirmed the centrality of the domestic dog and the rodent Rattus tanezumi (R. tanezumi) in shared habitats and the co-occurrence with other mammal species. This rodent species was previously mentioned as a bridge species between habitats favouring disease transmission. This study is a first step to identify potential reservoirs and habitat interfaces associated with the risk of zoonotic diseases and pathogen spillover.
野生动物群落受到生态恢复和再造林的积极影响。了解哺乳动物群落从人类主导的栖息地到受保护的栖息地，再到重新造林的栖息地的动态变化，对于评估重新造林对保护生物学和疾病生态学的影响至关重要。我们使用了从“溢出接口”项目中实施的一组相机陷阱和活动陷阱中获得的数据。网络分析表明，在以人类为主导的栖息地(如人工林)和保护区之间，再造林地区是哺乳动物物种共享的中心。网络分析还证实了家犬和鼠类黄胸鼠(Rattus tanezumi, R. tanezumi)在共有生境中居中心地位，并与其他哺乳动物共生。这种啮齿类动物以前被认为是有利于疾病传播的栖息地之间的桥梁物种。这项研究是确定与人畜共患疾病和病原体溢出风险相关的潜在水库和栖息地界面的第一步。
{"title":"From Protected Habitat to Agricultural Land: Dogs and Small Mammals Link Habitats in Northern Thailand","authors":"Chuanphot Thinphovong, Anamika Kritiyakan, Ronnakrit Chakngean, Yossapong Paladsing, Phurin Makaew, Morgane Labadie, Christophe Mahuzier, Waraphon Phimpraphai, Serge Morand, Kittipong Chaisiri","doi":"10.3390/ecologies4040044","DOIUrl":"https://doi.org/10.3390/ecologies4040044","url":null,"abstract":"Wildlife communities are positively affected by ecological restoration and reforestation. Understanding the dynamics of mammal communities along a gradient of a human-dominated habitat to a protected habitats, right up to a reforestation habitat, is crucial for assessing the effects of reforestation on conservation biology and disease ecology. We used data obtained from a set of camera traps and live traps implemented in the “Spillover Interface” project. A network analysis showed that the reforested area was central in the sharing of mammal species between human-dominated habitats, such as plantations, and the protected area. A network analysis also confirmed the centrality of the domestic dog and the rodent Rattus tanezumi (R. tanezumi) in shared habitats and the co-occurrence with other mammal species. This rodent species was previously mentioned as a bridge species between habitats favouring disease transmission. This study is a first step to identify potential reservoirs and habitat interfaces associated with the risk of zoonotic diseases and pathogen spillover.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135758532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-05DOI: 10.3390/ecologies4040043
Lingling Li, Hongqi Wu, Yimin Gao, Sance Zhang
Cultivating cotton and sustaining its productivity are challenging in temperate arid regions around the globe. Exploring suitable cotton cultivation areas to improve productivity in such climatic regions is essential. Thus, this study explores the ecologically suitable areas for cotton cultivation using the MaxEnt model, having 375 distribution points of long-staple cotton and various factors, including 19 climatic factors, 2 terrain factors, and 6 soil factors in Xinjiang. The area under the curve (AUC) of the predicted results was greater than 0.9, indicating that the model’s predictions had fairly high accuracy. However, the main environmental factors that affected the cotton’s growth were the lowest temperature in the coldest month, the hottest month, the precipitation in the driest season, and the monthly average temperature difference. Further, the temperature factors contributed 71%, while the contribution ratio of terrain and soil factors was only 22%. The research indicated that the current planting area was consistent with the predicted area in many areas of the study. Still, some areas, such as the Turpan region northwest of Bayingolin Mongol Autonomous Prefecture, are supposed to be suitable for planting cotton, but it is not planted. The current potential distribution area of long-staple cotton is mainly located in Aksu Prefecture and the northern part of the Kashgar Prefecture region. The climatic prediction shows that the growing area of long-staple cotton may expand to southern Altay, central Aksu, and Bortala Mongol Autonomous Prefecture. This study will be helpful for cotton cultivation suitability areas in Xinjiang and other regions with similar environments.
{"title":"Predicting Ecologically Suitable Areas of Cotton Cultivation Using the MaxEnt Model in Xinjiang, China","authors":"Lingling Li, Hongqi Wu, Yimin Gao, Sance Zhang","doi":"10.3390/ecologies4040043","DOIUrl":"https://doi.org/10.3390/ecologies4040043","url":null,"abstract":"Cultivating cotton and sustaining its productivity are challenging in temperate arid regions around the globe. Exploring suitable cotton cultivation areas to improve productivity in such climatic regions is essential. Thus, this study explores the ecologically suitable areas for cotton cultivation using the MaxEnt model, having 375 distribution points of long-staple cotton and various factors, including 19 climatic factors, 2 terrain factors, and 6 soil factors in Xinjiang. The area under the curve (AUC) of the predicted results was greater than 0.9, indicating that the model’s predictions had fairly high accuracy. However, the main environmental factors that affected the cotton’s growth were the lowest temperature in the coldest month, the hottest month, the precipitation in the driest season, and the monthly average temperature difference. Further, the temperature factors contributed 71%, while the contribution ratio of terrain and soil factors was only 22%. The research indicated that the current planting area was consistent with the predicted area in many areas of the study. Still, some areas, such as the Turpan region northwest of Bayingolin Mongol Autonomous Prefecture, are supposed to be suitable for planting cotton, but it is not planted. The current potential distribution area of long-staple cotton is mainly located in Aksu Prefecture and the northern part of the Kashgar Prefecture region. The climatic prediction shows that the growing area of long-staple cotton may expand to southern Altay, central Aksu, and Bortala Mongol Autonomous Prefecture. This study will be helpful for cotton cultivation suitability areas in Xinjiang and other regions with similar environments.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135435010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.3390/ecologies4040042
Amanda Hathaway, Marco Campera, Katherine Hedger, Marianna Chimienti, Esther Adinda, Nabil Ahmad, Muhammed Ali Imron, K. A. I. Nekaris
Accelerometers are powerful tools for behavioral ecologists studying wild animals, particularly species that are difficult to observe due to their cryptic nature or dense or difficult to access habitats. Using a supervised approach, e.g., by observing in detail with a detailed ethogram the behavior of an individual wearing an accelerometer, to train a machine learning algorithm and the accelerometer data of one individual from a wild population of Javan slow lorises (Nycticebus javanicus), we applied a Random Forest model (RFM) to classify specific behaviors and posture or movement modifiers automatically. We predicted RFM would identify simple behaviors such as resting with the greatest accuracy while more complex behaviors such as feeding and locomotion would be identified with lower accuracy. Indeed, resting behaviors were identified with a mean accuracy of 99.16% while feeding behaviors were identified with a mean accuracy of 94.88% and locomotor behaviors with 85.54%. The model identified a total of 21 distinct combinations of six behaviors and 18 postural or movement modifiers in this dataset showing that RFMs are effective as a supervised approach to classifying accelerometer data. The methods used in this study can serve as guidelines for future research for slow lorises and other ecologically similar wild mammals. These results are encouraging and have important implications for understanding wildlife responses and resistance to global climate change, anthropogenic environmental modification and destruction, and other pressures.
{"title":"Analysis of Accelerometer Data Using Random Forest Models to Classify the Behavior of a Wild Nocturnal Primate: Javan Slow Loris (Nycticebus javanicus)","authors":"Amanda Hathaway, Marco Campera, Katherine Hedger, Marianna Chimienti, Esther Adinda, Nabil Ahmad, Muhammed Ali Imron, K. A. I. Nekaris","doi":"10.3390/ecologies4040042","DOIUrl":"https://doi.org/10.3390/ecologies4040042","url":null,"abstract":"Accelerometers are powerful tools for behavioral ecologists studying wild animals, particularly species that are difficult to observe due to their cryptic nature or dense or difficult to access habitats. Using a supervised approach, e.g., by observing in detail with a detailed ethogram the behavior of an individual wearing an accelerometer, to train a machine learning algorithm and the accelerometer data of one individual from a wild population of Javan slow lorises (Nycticebus javanicus), we applied a Random Forest model (RFM) to classify specific behaviors and posture or movement modifiers automatically. We predicted RFM would identify simple behaviors such as resting with the greatest accuracy while more complex behaviors such as feeding and locomotion would be identified with lower accuracy. Indeed, resting behaviors were identified with a mean accuracy of 99.16% while feeding behaviors were identified with a mean accuracy of 94.88% and locomotor behaviors with 85.54%. The model identified a total of 21 distinct combinations of six behaviors and 18 postural or movement modifiers in this dataset showing that RFMs are effective as a supervised approach to classifying accelerometer data. The methods used in this study can serve as guidelines for future research for slow lorises and other ecologically similar wild mammals. These results are encouraging and have important implications for understanding wildlife responses and resistance to global climate change, anthropogenic environmental modification and destruction, and other pressures.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136344129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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