Land Cover Variables Research Articles

Rotational complexity across US counties is currently insufficient to observe yield gains in major crops

Landscape complexity promotes ecosystem services and agricultural productivity, and often encompasses aspects of compositional or configurational land cover diversity across space. However, a key agricultural diversification practice, crop rotation, extends crop land cover complexity concurrently across space and time. Long-term experiments suggest that complex crop rotations can facilitate yield increases in major crops. Using a compiled county-annual panel dataset, we examined whether yield benefits of crop rotational complexity were apparent on a landscape scale in the conterminous US for four major crops between 2008 and 2020. We found that the benefit of rotational complexity was only apparent for cotton and winter wheat, and that the benefit for wheat was driven by one region. Corn exhibited the opposite pattern, wherein higher yields were consistently obtained with lower rotational complexity, while soybean yield appeared relatively insensitive to rotational complexity. Effects of rotational complexity were sometimes influenced by agrochemical usage. Positive effects of rotational complexity were only apparent with high fertilizer for soybean and wheat, and with low fertilizer for cotton. Corn yield in high-complexity, low-yielding counties appeared to improve with high fertilizer inputs. For the overwhelming majority of acres growing these major crops, crop rotation patterns were quite simple, which when combined with the short time span of available data, may explain the apparent discrepancy between long-term experiments and nationwide data. Current demand and incentives that promote highly intensified and specialized agriculture likely hinder realization of the benefits of rotational complexity for production of key crops in the US. Increasing rotational complexity where major crops are grown thus remains an underutilized approach to mitigate landscape simplification and to promote ecosystem services and crop yields.

Role of edaphic, hydrologic, and land cover variables in determining dissolved organic carbon in Missouri (USA) reservoirs and streams

Jones JR, Graham JL, Obrecht DV, Harlan JD, Knowlton MF, Pollard C, Parris J, Thorpe AP. 2024. Role of edaphic, hydrologic, and land cover variables in determining dissolved organic carbon in Missouri (USA) reservoirs and streams. Lake Reserv Manage. 40:177–195. In Missouri, distinct geophysical gradients influence statewide patterns in water quality. Here, we quantify the spatiotemporal variability of dissolved organic carbon (DOC) in reservoirs and streams and the edaphic, hydrologic, and land cover variables that account for cross-system variation. Datasets included statewide inventories collected over decades and studies with greater temporal resolution (n = >6350 DOC measurements). Among reservoirs, the smallest DOC concentration was measured in a spring-fed system within a forested watershed, and the largest was where agricultural biosolids were applied to the land (range 1.0–15.9 mg/L, overall mean 5.8 mg/L). Reservoir values increased from the southern forested Highlands (mean 4.7 mg/L) to the northern agricultural Plains (mean 7.0 mg/L). Stream DOC was similar to reservoir values (overall mean in streams 6.3 mg/L; Highlands mean 4.0 mg/L; Plains mean 6.6 mg/L), despite differences in study design and collection period. Reservoir DOC increased in spring, indicative of allochthonous loading, with small autochthonous additions during a broad summer peak. Temporal variability in DOC was low relative to macronutrients and chlorophyll in both reservoirs and streams, indicating DOC may be a sensitive and readily detected indicator of temporal change in these systems. In regression analyses, watershed features accounted for more than 60% of overall cross-system variability in DOC in both reservoirs and streams. Driver-response relations, however, differed between regions. This analysis extends our understanding of environmental influences on surface water chemistry in Missouri and indicates DOC is nearly as predictable as macronutrients using landscape-level features.

Assessing the applicability of binary land-cover variables to species distribution models across multiple grains

ContextSpecies distribution models are widely used in ecology. The selection of environmental variables is a critical step in SDMs, nowadays compounded by the increasing availability of environmental data.ObjectivesTo evaluate the interaction between the grain size and the binary (presence or absence of water) or proportional (proportion of water within the cell) representation of the water cover variable when modeling water bird species distribution.MethodseBird occurrence data with an average number of records of 880,270 per species across the North American continent were used for analysis. Models (via Random Forest) were fitted for 57 water bird species, for two seasons (breeding vs. non-breeding), at four grains (1 km2 to 2500 km2) and using water cover as a proportional or binary variable.ResultsThe models’ performances were not affected by the type of the adopted water cover variable (proportional or binary) but a significant decrease was observed in the importance of the water cover variable when used in a binary form. This was especially pronounced at coarser grains and during the breeding season. Binary representation of water cover is useful at finer grain sizes (i.e., 1 km2).ConclusionsAt more detailed grains (i.e., 1 km2), the simple presence or absence of a certain land-cover type can be a realistic descriptor of species occurrence. This is particularly advantageous when collecting habitat data in the field as simply recording the presence of a habitat is significantly less time-consuming than recording its total area. For models using coarser grains, we recommend using proportional land-cover variables.

Bottom-up rather than top-down mechanisms determine mesocarnivore interactions in Norway.

Interactions among coexisting mesocarnivores can be influenced by different factors such as the presence of large carnivores, land-use, environmental productivity, or human disturbance. Disentangling the relative importance of bottom-up and top-down processes can be challenging, but it is important for biodiversity conservation and wildlife management. The aim of this study was to assess how the interactions among mesocarnivores (red fox Vulpes vulpes, badger Meles meles, and pine marten Martes martes) were affected by large carnivores (Eurasian lynx Lynx lynx and wolf Canis lupus), land cover variables (proportion of agricultural land and primary productivity), and human disturbance, as well as how these top-down and bottom-up mechanisms were influenced by season. We analyzed 3 years (2018-2020) of camera trapping observations from Norway and used structural equation models to assess hypothesized networks of causal relationships. Our results showed that land cover variables were more strongly associated with mesocarnivore detection rates than large carnivores in Norway. This might be caused by a combination of low density of large carnivores in an unproductive ecosystem with strong seasonality. Additionally, detection rates of all mesocarnivores showed positive associations among each other, which were stronger in winter. The prevalence of positive interactions among predators might indicate a tendency to use the same areas and resources combined with weak interference competition. Alternatively, it might indicate some kind of facilitative relationship among species. Human disturbance had contrasting effects for different species, benefiting the larger mesocarnivores (red fox and badger) probably through food subsidization, but negatively affecting apex predators (wolf and lynx) and smaller mesocarnivores (pine marten). In a human-dominated world, this highlights the importance of including anthropogenic influences in the study of species interactions.

Stream Chemistry and Forest Recovery Assessment and Prediction Modeling in Coal-Mine-Affected Watersheds in Kentucky, USA

Kentucky is one of the largest coal-producing states; surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas, vegetation change, and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age and percentage of mining, reclaimed forest, and reclaimed woods) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n = 9), summer (n = 14), and fall (n = 58) 2017 to study changes in water quality variables (SO42−, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+, Fe3+) in response to changes in land cover. Pearson correlation analyses indicated that conductivity has strong to very strong relationships with water quality variables related to coal mining (except Al3+, Fe2+, Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate regression analyses were performed, with conductivity values based on samples collected in the fall. First, conductivity responses to mining percentage, reclamation age and topographic variables were examined (adjusted R2 = 0.818, p < 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p < 0.01). Finally, reclamation age and mining percentages were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p < 0.01), with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of the mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal-Mine-Related Stream Chemistry in areas where agriculture and urban development are limited. Water quality is not suitable for various purposes due to the presence of contaminants, especially in mined sites. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining, as well as refine land reclamation practices more effectively while such practices are in action.

Investigating the dynamic nature of landslide susceptibility in the Indian Himalayan region.

Landslide susceptibility zonation (LSZ) mapping is used to delineate areas prone to landslides and is critical for effective landslide hazard management. The existing methodologies for generating such maps tend to neglect the influence of dynamic environmental variables on landslide occurrences, which may lead to obsolete and erroneous estimates of landslide susceptibility (LS) for a concerned area. Although recent studies have started to report the effects of Land Use/ Land Cover (LULC) variation on LSZ mapping, variations in other dynamic variables like rainfall, soil moisture, and evapotranspiration apart from LULC may also influence slope stability in mountainous regions. The present study investigates the impact of variations in these four variables on the LS distribution, of a selected Indian Himalayan region between 2017 and 2021. Random Forest (RF) susceptibility models are utilized for evaluating the LS for the selected years and geospatial technologies are employed for LS change detection. The results indicate up to 19% variations in the spatial extent for some of the zones of the generated LSZ maps. The research findings of this study are crucial since they reveal the impact of dynamic behavior on LS, which has not been previously documented in the literature.

Analytical framework using remote sensing and water geochemistry to assess changes in landscapes with high ecological and social value

AbstractThe Brazilian Mata Atlântica coastal rainforest suffered a dramatic reduction in size due to agricultural and mining activities since the 1500s. Most relevant fragments are in mountainous areas assigned for environmental conservation, where there is increasing market pressure to open these areas for mining operations. In this study, we created a broader framework for water basin study on mountainous regions in tropical areas of high ecological importance. Remote sensing and hydrochemical analysis were used to create a more encompassing evaluation and a prognosis of environmental changes caused by mining operations. Our results showed that land use and land cover variations affect the physical and chemical behavior of rivers, and that seasonality plays a compounding role in their levels of particulate and chemical elements. Applying these combined techniques proved to be a good strategy in the evaluation of land cover change on the physical and chemical variations found in smaller watersheds.

Hydrological response to land use land cover and climate variability, and simulation of sediment export and water yield in the catchment Kotri Sindh Pakistan using Soil and Water Assessment tool model.

The water availability concerns have been increasing due to significant impacts of land use land cover change, and climate variability. In terms of developing countries, it is one of the biggest challenges to overcome and manage sustainability in the present and future. This study aims to evaluate the change in hydrological components and simulation of sediment yield and water yield on the large-scale basin of Kotri barrage with a change in runoff due to a change in land use land cover. This study has been done on the watershed as well as the sub-watershed level to have an accurate estimation and simulation by finding the response of hydrological components toward its natural and human-induced factors using the Soil and Water Assessment tool with high-resolution geospatial-temporal inputs over the Kotri catchment. The sediment and water yield were quantified using 42 years of simulation (1981-2022) on the sub-basin level, projected to land use land cover 1990, 2000, 2010, and 2022. The increase in deforestation, agriculture, and settlement areas resulted increase in sediment load in the catchment. The sub-basins 14, 11, 12, and 13, with a high elevation and slope and with less vegetation showed higher sediment load and water yield than the sub-basins with gentle slope and with high natural vegetation cover. The sub-basins 10, 4, and 1 showed high water yield availability compared to basins 2, 3, 5, 6, 7, 8, 9. This may be the result of vegetation differences. However, contained less sediment load than basins 14, 11, 12, and 13. The main objective was to quantify the significant changes affecting catchment and sub-catchment areas, to have a better understanding of the management plan regarding land use land cover. The simulated data was further projected to prediction using machine algorithms (autoregressive integrated moving average) model for precipitation prediction, and (seasonal autoregressive integrated moving average with exogenous factors) model to predict the sediment yield and water yield in the catchment to 2060.

Determining abundance predictors of the European Hare (Lepus europaeus), a global invader in southeastern Brazil

Abstract European Hare (Lepus europaeus), like many invasive species, have declined in much of their native range but flourished in non-native regions (e.g. South America). Previous studies suggested that loss of farmland heterogeneity due to agricultural intensification is the main driver of the species decline in its native range in Europe. Yet, little is known about the role of spatial and temporal heterogeneity and land cover types as predictors of European Hare local abundance in Neotropical agricultural landscapes. We hypothesized that spatial and temporal heterogeneity, rather than land cover types, would be the most influential predictors of hare local abundance in intensively managed Neotropical agricultural landscapes. We sampled 55 sites embedded within agricultural-dominated landscapes from southeastern Brazil with camera traps and transect surveys. Sites were selected along an uncorrelated gradient of native vegetation cover and compositional heterogeneity. We estimated the relative abundance of European hares using an occupancy model that accounts for imperfect detection of species induced primarily by variation in local abundance. We found that land cover diversity, sugarcane, and savanna cover were the best predictors of European Hare relative abundance. Hare relative abundance estimates were low and did not vary dramatically among sites, suggesting that this invader has not yet attained high local density in our study region. European Hare attained the highest relative abundance in agricultural landscapes that locally combine higher compositional heterogeneity, including sugarcane crops, and little to no native savanna. Areas with these combined features may represent the most important nascent foci, fostering ongoing northward spread of this invasive species in the Neotropics.

Environmental filtering and landscape composition drive multifaceted diversity of bird assemblages in vineyards

Abstract Agricultural landscapes are productive areas with high biodiversity potential, but their conversion to monocultures and intensification of practices are recognised drivers of bird biodiversity loss worldwide. This challenges the compatibility of agricultural land use with bird conservation, as landscape composition affects both the diversity of bird species and traits and the assembly of bird communities. We address the underlying mechanisms of avian community assembly in vineyards at the plot and landscape levels in relation to landscape composition in one of the major wine producing regions of France. We jointly analyse how the taxonomic, functional, and phylogenetic facets of bird alpha and beta diversity respond to a gradient of landscape heterogeneity and test for a non‐random assembly rule. We found that birds tended to avoid vineyard monocultures. There was consistent support for the co‐occurrence of both closely related species and similar functional traits within vineyard plots (namely, phylogenetic and functional clustering, respectively). Landscape composition, both within plots and on a large scale (1000 m), was critical in explaining the occurrence of species and traits within plots. Landscape composition determined a nested pattern of functional and phylogenetic beta diversity from vineyard monoculture to more complex landscapes with increasing seminatural land cover. Synthesis and applications. Landscape composition in seminatural vegetation features significantly influenced both the alpha and beta bird diversity in vineyard‐dominated agricultural landscapes. Interspersed shrubs and woodland can help increase bird abundance and species richness in vineyards, while large‐scale land cover diversity might help promote functional and phylogenetic bird diversity.

Fuzzy logic as a novel approach to predict biological condition gradient of various streams in Ceyhan River Basin (Turkey)

Creating a method to categorize the ecological status of streams according to their biological conditions and establishing scientifically defensible nutrient criteria to protect their biotic integrity poses significant challenges. Biomonitoring of least disturbed areas is an important issue to accurately assess the ecological status of surface waters and ensure their sustainability. The fuzzy logic as a novel approach was firstly applied to evaluate the biological condition gradient of 44 sampled streams in the Ceyhan River Basin, utilizing two diatom indices, total phosphorus (TP), electrical conductivity (EC), and CORINE data. The fuzzy logic was employed to examine variations in the diatom compositions and land cover based on biological condition gradients (BCGs) of various streams and to assess the suitability of BCG in evaluating the health of studied stream systems. A three-layer fuzzy logic was constructed to predict BCGs of steams based on input data, with diatom metrics, TP, and EC representing BCGdia and land cover variables contributing to BCGland. The effects of operating variables were studied to optimize BCG results. The highest BCG score (0.85) was determined in Aksu Spring Brook in the spring, whereas the lowest value (0.05) was calculated in Erkenez Stream3 in the summer. BCGs showed strong relationships with nutrients, altitude, and EC. Results of BCGs indicated that sampling stations have various ecological statuses ranging from bad to high in the Ceyhan River Basin. The BCGdia and BCGland made important contributions to determine the ecological status of streams in the Ceyhan River Basin. Results showed that the BCG approach allows a more reliable way to determine the ecological status of streams in the Ceyhan River Basin by combining biological and chemical assessments for the sustainability of the environment. It is recommended that the BCG will be applied and evaluated in future research studies across various river basins, both within and outside of Turkey.

Greenspace and Land Cover Diversity During Pregnancy in a Rural Region, and Associations With Birth Outcomes.

Beneficial effects on health outcomes have been observed from exposure to spaces with substantial green vegetation ("greenspace"). This includes studies of greenspace exposure on birth outcomes; however, these have been conducted largely in urban regions. We characterized residential exposure to greenspace and land cover diversity during pregnancy in rural northern New England, USA, investigating whether variation in greenspace or diversity related to newborn outcomes. Five landscape variables (greenspace land cover, land cover diversity, impervious surface area, tree canopy cover, and the Normalized Difference Vegetation Index) were aggregated within six circular zones of radii from 100 to 3,000m around residential addresses, and distance to conservation land was measured, providing a total of 31 greenspace and diversity metrics. Four birth outcomes along with potentially confounding variables were obtained from 1,440 participants in the New Hampshire Birth Cohort Study. Higher greenspace land cover up to 3,000m was associated with larger newborn head circumference, while impervious surface area (non-greenspace) had the opposite association. Further, birth length was positively associated with land cover diversity. These findings support beneficial health impacts of greenspace exposure observed in urban regions for certain health outcomes, such as newborn head circumference and length but not others such as birthweight and gestational age. Further our results indicate that larger radius buffer zones may be needed to characterize the rural landscape. Vegetation indices may not be interchangeable with other greenspace metrics such as land cover and impervious surface area in rural landscapes.

Thirty Years of Climate and Land-Cover Change and its Effects on Tourism Resources in Valley of Flower National Park

This study investigates how the physical and scenic components of trekking in Vally of Flower National Park are affected by observed variations in rainfall, temperature, and land cover. The impact analysis is structured on a hazard-activity pairs method, which combines factors of environmental change (such as greater temperatures) with tourism activities (like trekking and sightseeing). The findings imply that warmer temperatures and less rain have decreased the chances of landslides, rock falls, and mountain sickness, and also enhanced the physical conditions for trekking. It is now possible to enjoy more flowers and greenery while witnessing fewer animals, waterfalls, and snow due to changes in land cover. In the short term, the melting snow may encourage “last chance tourism,” boosting travel, but over time, the disappearance of the snow and the destruction of the forest will probably lead to a decline in tourism. The research concludes that the most viable strategy for reducing losses is the efficient management of the attractions in the developing heathlands.

Mapping land use land cover (LUCL) and its influence on land surface temperature (LST): A case study in Dau Tieng district at Binh Duong province

At present, land surface temperature (LST) is an important index in monitoring the urban heat is-land phenomenon and changes in local climate, as well as global climate. By analyzing the variation in land use land cover (LULC), we can see how changes in LULC will lead to changes in LST and understand the expansion of urbanization related to LST. This study used Landsat 8’s thermal infrared band to extract and calculate LST values in DauTieng district in the period 2015-2022. In addition, this study also classified LULC by using the Support Vector Machine algorithm, then evaluated changes in LST on cropland, forest, water surface, and impervious surface areas. The results showed that in places with dense vegetation cover, LST value was low, whereas when moving to areas with low density of vegetation and residential areas, industrial parks,… LST value gradually increased. In general, changes in LULC are important factors that cause LST to increase or decrease, thereby suggesting solutions to minimize high-temperature areas

Modelling Impact of Land Use Changes and Climate on Soil Erosion in the Uma Oya River Basin, Sri Lanka

Soil erosion is a significant environmental issue in most mountainous areas and is further exacerbated due to ongoing climatic changes and anthropogenic activities. Soil erosion not only triggers natural disasters like landslides but also degrades the fertile topsoil layers. Therefore, modeling and evaluation of soil erosion in mountainous areas and river basins are highly important. The Uma Oya River Basin (UORB), Sri Lanka is an area with rich biodiversity and is also important for agricultural production. Moreover, this area is frequently discussed due to the ongoing developments of the Uma Oya Project. This paper presents a comprehensive evaluation of soil erosion in the UORB and results are compared for two decades from 2000 to 2020. The Revised Universal Soil Loss Equation (RUSLE) was used to determine the annual soil erosion rates. In addition, the spatial-temporal variation of land use and land cover was assessed in the UORB. Results revealed that extreme soil erosion scenarios occur when forests and other vegetation lands are converted to agricultural lands and farmlands. We found that soil loss in the area largely happened due to steep slopes, reduction of vegetation and forest covers, and growth of cultivation lands. Erosion-prone areas in the river basin are identified and conservation strategies are discussed. In addition, the impact of the ongoing climate change on the UORB is highlighted.

Application of Satellite Images and Artificial Intelligence to Monitor Land Cover Changes in Hanoi Area During 2013-2023 Period

Artificial intelligence (AI) and remote sensing technology have now increasingly improved their efficiency and reliability in monitoring the changes in land cover. With the amendment of the Vietnamese Law on Land in 2013 and the administrative boundary expansion of Hanoi, Hanoi experiences significant changes in land use and land cover for the last ten years. To monitor the actual land use changes in the area, this study used the Random Forest (RF) machine learning algorithm to classify the basic land covers, monitor, and analyze the spatial variation of land use and land cover in the 2013 to 2023 period. The study findings indicate a relatively high rate of expansion of construction zone area and a decrease in land cover related to water bodies and vegetated area. Water bodies decrease by an average of 0.8% annually, whereas the construction zone area increased by 7% of the total area.

Unveiling the presence of endocrine disrupting chemicals in northern French soils: Land cover variability and implications

Endocrine disrupting chemicals (EDCs) are chemicals that can be found in the environment and have adverse effects on human health by mimicking, perturbing and blocking the function of hormones. They are commonly studied in water surfaces, rarely in soils, although it can be an important source of their presence in the environment. Their detection in soils is analytically challenging to quantify, hence the lack of known background concentrations found in the literature. This scientific research aimed to detect EDCs in soils by analyzing 240 soil samples using an optimized protocol of double extraction and analysis using liquid chromatography coupled to mass spectrometry. The optimized protocol allowed for very sensitive detection of the targeted compounds. The results showed a high concentration of 29.391 ng/g of 17β-estradiol in soils and 47.16 ng/g for 17α-ethinylestradiol. Testosterone and Progesterone were detected at a highest of 1.02 and 6.58 ng/g, respectively. The ∑EDCs which included estrogens, progesterone, testosterone and Bisphenol A was found at an average of 22.72 ± 35.46 ng/g in the study area. The results of this campaign showed a heterogeneous geographic distribution of the EDCs compounds in the different zones of study. Additionally, the study conducted a comparison of the concentration of EDCs in different land covers including urban areas, agricultural lands, grasslands and forests. We observed a significant difference between forests and other land covers (p < 0.0001) for 17α-ethinylestradiol, estriol, and progesterone. This presence of EDCs in forest lands is not yet understood and requires further studies concerning its origins, its fate and its effect on human health. This study is the first large-scale sampling campaign targeting EDCs in soils in Europe and the second in the world. It is also the first to assess the concentrations of these compounds based on different land covers.

How does urbanization affect the fauna of the largest urban forest in Mexico?

Animals in urban forests provide ecological and cultural services, but the quality of these services often depends on floral diversity and animal diversity. In turn, animal diversity in urban forests is influenced by various aspects of habitat quality, in spatial scale- and taxon-dependent ways. Understanding the effect of individual habitat factors on different animal groups can provide valuable information for urban forest management. We estimated the relationships of 25 environmental, vegetation, land cover and anthropogenic perturbation variables to the fauna of Chapultepec Forest within Mexico City, Mexico. We included flower-visiting flies (Diptera: Bombyliidae, Syrphidae), bees (Hymenoptera: Apoidea), butterflies (Lepidoptera: Papilionoidea), birds, and reptiles (Squamata and Testudines). Insect populations were more strongly affected by herb and flower variables, while variables related to trees and shrubs were more important to vertebrate taxa. In general, human density, buildings cover and pavement cover were the most relevant anthropogenic perturbation factors. Birds and butterflies were more tolerant of urbanization than the other groups. Effects for each taxon are discussed. Our results suggest that urban park management plans should focus on enhancing habitat heterogeneity and vegetation structure complexity. Specifically, maintaining herb and tree diversity would likely promote animal diversity and ecosystem services in the Chapultepec Forest.

Effect of landscape attributes on the occurrence of the endangered golden-headed lion tamarin in southern Bahia, Brazil.

The golden-headed lion tamarin (Leontopithecus chrysomelas) is an endangered primate that occurs exclusively in the Atlantic Forest of southern Bahia, Brazil. Its geographic range has been severely reduced by deforestation and its populations are restricted to a human-modified landscape consisting primarily of Atlantic forest fragments and shade cacao (Theobroma cacao) agroforestry, locally known as cabrucas. In the last 30 years, there has been a 42% reduction in the geographic range and a 60% reduction in the population size of L. chrysomelas, with only 8% of its habitat represented by protected areas. Thus, we investigated the occurrence of L. chrysomelas in forest fragments and cabrucas based on interviews and using playback census, and evaluated the influence of landscape attributes on its occurrence. The occurrence was measured using a Generalized Linear Model using a set of 12 predictor variables, including fragment size and elevation. L. chrysomelas inhabited 186 (38%) of the 495 forest fragments and cabrucas. Most inhabited habitat patches (n = 169, 91%) are in the eastern portion (ca. 70 km wide region from the Atlantic coast to inland) of its geographic range. The remaining (n = 17, 9%) are in the western portion of the distribution, between 70 and 150 km from the Atlantic coast. Our models indicate a higher occurrence of L. chrysomelas in the eastern portion of its geographic range, where the landscape exhibits lower land cover diversity, greater functional connectivity, lower altitudes (<400 m), and is primarily composed of forest fragments and cabrucas with a higher core percentage. In contrast, we observed a lower occurrence of L. chrysomelas in the western portion, where the landscape is more diverse and heterogeneous due to anthropogenic activities, such as agriculture and livestock. We urge the establishment of ecological corridors via reforestation of degraded areas in the western portion of the range. This increase in habitat availability and suitability in the west together with the protection of the forests and cabrucas in the east would increase our chances of saving L. chrysomelas from extinction.

Climate change causes declines and greater extremes in wetland inundation in a region important for wetland birds.

Wetland ecosystems are vital for maintaining global biodiversity, as they provide important stopover sites for many species of migrating wetland-associated birds. However, because weather determines their hydrologic cycles, wetlands are highly vulnerable to effects of climate change. Although changes in temperature and precipitation resulting from climate change are expected to reduce inundation of wetlands, few efforts have been made to quantify how these changes will influence the availability of stopover sites for migratory wetland birds. Additionally, few studies have evaluated how climate change will influence interannual variability or the frequency of extremes in wetland availability. For spring and fall bird migration in seven ecoregions in the south-central Great Plains of North America, we developed predictive models associating abundance of inundated wetlands with a suite of weather and land cover variables. We then used these models to generate predictions of wetland inundation at the end of the century (2069-2099) under future climate change scenarios. Climate models predicted the average number of inundated wetlands will likely decline during both spring and fall migration periods, with declines being greatest in the eastern ecoregions of the southern Great Plains. However, the magnitude of predicted declines varied considerably across climate models and ecoregions, with uncertainty among climate models being greatest in the High Plains ecoregion. Most ecoregions also were predicted to experience more-frequent extremely dry years (i.e., years with extremely low wetland abundances), but the projected change in interannual variability of wetland inundation was relatively small and varied across ecoregions and seasons. Because the south-central Great Plains represents an important link along the migratory routes of many wetland-dependent avian species, future declines in wetland inundation and more frequent periods of only a few wetlands being inundated will result in an uncertain future for migratory birds as they experience reduced availability of wetland stopover habitat across their migration pathways.