Habitat loss and fragmentation in tropical regions are major threats to the persistence of endangered Malay tapir (Tapirus indicus). The Malay tapir distribution is largely constrained to fragmented habitats inside protected areas. However, it is unclear how the spatial patterns of habitat fragmentation affect its relative abundance. Here, we investigated the effects of habitat fragmentation on Malay tapir relative abundance in Thailand. We first quantified the spatial patterns of habitat fragmentation within nine of Thailand’s protected areas. Second, we assessed the relationship of fragmentation metrics and relative abundance of Malay tapirs. Third, we identified the relative importance of the fragmentation metrics in explaining relative abundance. We found that tapir abundance remained unexpectedly high in the Southern forest complex despite the fact that tapir habitats were significantly more fragmented there than in the protected area in the western forest complex (p < 0.05). Additionally, we found a significantly negative relation with clumpiness index (R2 = 0.51, p < 0.05). This suggests that other factors may also be influencing their populations, so that the Southern protected areas provide preferred habitat with higher relative proportions of moist evergreen forest, large habitat patch size, precipitation, and elevation. It highlights the importance of interconnected habitat for tapirs, and the benefit of conservation efforts in small, less recognized protected areas.
File: Suwannaphong-s2.0-S2351989424003901-main.pdf
Mapping land cover in highly heterogeneous landscapes is challenging, and classifications have inherent limitations where the spatial resolution of remotely sensed data exceeds the size of small objects. For example, classifications based on 30-m Landsat data do not capture urban or other heterogeneous environments well. This limitation may be overcome by quantifying the subpixel fractions of different land cover types. However, the selection process and transferability of models designed for subpixel land cover mapping across biomes is yet challenging. We asked to what extent (a) locally trained models can be used for sub-pixel land cover fraction estimates in other biomes, and (b) training data from different regions can be combined into spatially generalized models to quantify fractions across global biomes. We applied machine learning regression-based fraction mapping to quantify land cover fractions of 18 regions in five biomes using Landsat data from 2022. We used spectral-temporal metrics to incorporate intra-annual temporal information and compared the performance of local, spatially transferred, and spatially generalized models. Local models performed best when applied to their respective sites (average mean absolute error, MAE, 9–18%), and also well when transferred to other sites within the same biome, but not consistently so for out-of-biome sites. However, spatially generalized models that combined input data from many sites worked very well when analyzing sites in many different biomes, and their MAE values were only slightly higher than those of the respective local models. A weighted training data selection approach, preferring training data with a lower spectral distance to the image data to be predicted, further enhanced the performance of generalized models. Our results suggest that spatially generalized regression-based fraction models can support multi-class sub-pixel fraction estimates based on medium resolution satellite images globally. Such products would have great value for environmental monitoring in heterogeneous environments and where land cover varies along spatial or temporal gradients.
File: Schug-1-s2.0-S0034425724002785-main.pdf
Assemblages in seasonal ecosystems undergo striking changes in species composition and diversity across the annual cycle. Despite a long-standing recognition that seasonality structures biogeographic gradients in taxonomic diversity (e.g., species richness), our understanding of how seasonality structures other aspects of biodiversity (e.g., functional diversity) has lagged. Integrating seasonal species distributions with comprehensive data on key morphological traits for bird assemblages across North America, we find that seasonal turnover in functional diversity increases with the magnitude and predictability of seasonality. Furthermore, seasonal increases in bird species richness led to a denser packing of functional trait space, but functional expansion was important, especially in regions with higher seasonality. Our results suggest that the magnitude and predictability of seasonality and total productivity can explain the geography of changes in functional diversity with broader implications for understanding species redistribution, community assembly and ecosystem functioning.
File: Ecography-2022-Keyser-Snow-cover-dynamics-an-overlooked-yet-important-feature-of-winter-bird-occurrence-and.pdf
The Atlantic meridional overturning circulation (AMOC) has caused significant climate changes over the past 90 000 years. Prior work has hypothesized that these millennial-scale climate variations effected past and contemporary biodiversity, but the effects are understudied. Moreover, few biogeographic models have accounted for uncertainties in palaeoclimatic simulations of millennial-scale variability. We examine whether refuges from millennial-scale climate oscillations have left detectable legacies in the patterns of contemporary species richness in eastern North America. We analyse 13 palaeoclimate estimates from climate simulations and proxy-based reconstructions as predictors for the contemporary richness of amphibians, passerine birds, mammals, reptiles and trees. Results suggest that past climate changes owing to AMOC variations have left weak but detectable imprints on the contemporary richness of mammals and trees. High temperature stability, precipitation increase, and an apparent climate fulcrum in the southeastern United States across millennial-scale climate oscillations aligns with high biodiversity in the region. These findings support the hypothesis that the southeastern United States may have acted as a biodiversity refuge. However, for some taxa, the strength and direction of palaeoclimate-richness relationships varies among different palaeoclimate estimates, pointing to the importance of palaeoclimatic ensembles and the need for caution when basing biogeographic interpretations on individual palaeoclimate simulations.
Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, community-level maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992and 2019. We developed ensemble models for each species at three spatial resolutions—0.5, 2.5, and 5 km—across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-kmresolution. However, the species we could model represent only 28%–56% of species found in the conterminous US BBSs across resolutions owing to data limitations. We found that stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States and support community-level conservation when used in tandem with guild maps.
File: Ecological-Applications-2023-Carroll-Mapping-multiscale-breeding-bird-species-distributions-across-the-United-States.pdf
Temperate woodlands are biodiverse natural communities threatened by land use change and fire suppression. Excluding historic disturbance regimes of periodic groundfires from woodlands causes degradation, resulting from changes in the plant community and subsequent biodiversity loss. Restoration, through prescribed fire and tree thinning, can reverse biodiversity losses, however, because the diversity of woodland species spans many taxa, efficiently quantifying biodiversity can be challenging. We assessed whether soundscapes in an eastern North American woodland reflect biodiversity changes during restoration measured in a concurrent multitrophic field study. In five restored and five degraded woodland sites in Wisconsin, USA, we sampled vegetation, measured arthropod biomass, conducted bird surveys, and recorded soundscapes for five days of every 15-day period from May to August 2022. We calculated two complementary acoustic indices: Soundscape Saturation, which focuses on all acoustically active species, and Acoustic Complexity Index (ACI), which was developed to study vocalizing birds. We used generalized additive models to predict both indices based on Julian date, time of day, and level of habitat degradation. We found that restored woodlands had higher arthropod biomass, and higher richness and abundance of breeding birds. Additionally, soundscapes in restored sites had higher mean Soundscape Saturation and higher mean ACI. Restored woodland acoustic indices exhibited greater magnitudes of daily and seasonal peaks. We conclude that woodland restoration results in higher soundscape saturation and complexity, due to greater richness and abundance of vocalizing animals. This bio-acoustic signature of restoration offers a promising monitoring tool for efficiently documenting differences in woodland biodiversity.
File: Persche-et-al-2024_soundscapes_restored-woodlands.pdf
Protected areas are cornerstones of conservation efforts worldwide. However, protected areas do not act in isolation because they are connected with surrounding, unprotected lands. Few studies have evaluated the effects of protected areas on wildlife populations inhabiting private lands in the surrounding landscapes. The lowland tapir Tapirus terrestris is the largest terrestrial mammal of the Neotropics and is categorized as Vulnerable on the IUCN Red List. It is necessary to understand the influence of landscape characteristics on the tapir’s habitat use to enable effective conservation management for this species. Our objectives were to () determine the potential distribution of the lowland tapir’s habitat in the Southern Yungas of Argentina, and () evaluate the role of protected areas and other covariates on tapir habitat use in adjacent private lands. We used records of lowland tapirs to model the species’ potential distribution and determined habitat use with occupancy modelling. Based on the covariates found to be significant in our models, we constructed predictive maps of probability of habitat use and assessed the area of potential habitat remaining for the species. Probability of habitat use was higher in the vicinity of two national parks and small households than further away from them. We found that in % of the lowland tapir’s potential distribution the probability of habitat use is high (..). These areas are near the three national parks in the study area. The probability of detecting lowland tapirs increased with distance to roads. We conclude that national parks play a key role in the persistence of lowland tapir populations on adjacent private lands.
File: Rivera-et-al-2021_National-Parks-influence-habitat-use-of-lowland-tapirs_Southern-Yungas-of-Argentina.pdf
Medium- and large-sized mammals play important roles in maintaining forest ecosystem functions, and these functions often diminish when mammal species are depleted by human activities. Understanding the sensitivity or tolerance of mammal species to human pressure and detecting species changes through monitoring programs can inform appropriate management decisions. The objective of our study was to identify medium- and large-sized mammal species that can be included in a monitoring programein the Southern Yungas of Argentina. We used occupancy modelling to estimate the probability of habitat use (ψ) of 13 of 25 mammal species detected by 165 camera traps placed in forests across a range of human footprint index (HFI) values. As defined by the HFI, 54% of the study area is wilderness. The probabilities of habitat use of two mammal species were significantly associated with the HFI: the lowland tapir (Tapirus terrestris; ψ = 0.33, range = 0.22–0.50) was inversely associated with HFI values, whereas the grey brocket deer (Mazama gouazoubira; ψ = 0.79, range = 0.67–0.87) was positively associated with the HFI. Monitoring the probability of habitat use of the sensitive species (lowland tapir) could help us to detect changes in areas experiencing anthropogenic impacts before they cause extirpation, whereas the high probability of the habitat use values of the tolerant species (grey brocket deer) might indicate that anthropogenic impacts are strongly influencing habitat, signaling that mitigation strategies might be warranted. The Southern Yungas retains an intact mammal fauna, and we showed that the HFI is useful for monitoring anthropogenic impacts on these mammals. There are still opportunities to develop conservation strategies to minimize threats to mammal species in the region by implementing a monitoring program with the proposed species.
File: Bardavid-et-al_2024_Identifying-mammal-species-sensitive-to-anthropogenic-impact_Environmental-Conservation.pdf
Heterogeneous vegetation supports higher species richness than homogenous vegetation, which is why efficiently identifying heterogenous vegetation can be useful for biodiversity conservation. Satellite remote-sensing data provide an opportunity to generate vegetation heterogeneity metrics and to explore the phenology of vegetation patterns. Phenoclusters are vegetation types with similar phenological characteristics, and valuable for capturing vegetation habitat heterogeneity patterns. Our goal was to map phenoclusters for Wisconsin, USA, at 10-m spatial resolution based on land surface phenology metrics from EVI (Enhanced Vegetation Index) Sentinel-2 data. We characterized each phenocluster based on landcover composition and structure, phenology timing, and environmental factors, and compared them to bird species richness. We also calculated the diversity of phenoclusters at multiple spatial extents. We identified 14 phenoclusters in Wisconsin, each with distinct landcover composition and structure, and unique phenological characteristics. Our remotely-sensed phenoclusters effectively captured environmental gradients, with elevation and temperature emerging as the most important driving variables. Furthermore, the phenoclusters successfully captured bird biodiversity patterns, especially richness of forest and grassland specialist. Our results identified phenological patterns among Wisconsin’s forests, shrublands, and grasslands, capturing phenological timing both among and within the same tree species. Phenoclusters are a valuable tool for capturing vegetation habitat heterogeneity, phenology diversity and biodiversity patterns, as well as climate change effects.
File: Silveira-et-al_2024_WisconsinPhenoclusters.pdf
The Global Deal for Nature sets an ambitious goal to protect 30% of Earth’s land and ocean by 2030. The 30×30 initiative is a way to allocate conservation resources and extend protection to conserve vulnerable and under protected ecosystems while reducing carbon emissions to combat climate change. However, most prioritization methods for identifying high-value conservation areas are based on thematic attributes and do not consider vertical habitat structure. Global tall forests represent a rare vertical habitat structure that harbors high species richness in various taxonomic groups and is associated with large amounts of aboveground biomass. Global tall forests should be prioritized when planning global protected areas toward reaching the 30×30 goals. We examined the spatial distribution of global tall forests based on the Global Canopy Height 2020 product. We defined global tall forests as areas with the average canopy height above 3 thresholds (20, 25, and30 m). We quantified the spatial distribution and protection level of global tall forests in high-protection zones, where the 30×30 goals are being met or are within reach, and low-protection zones, where there is a low chance of reaching 30×30 goals. We quantified the protection level by computing the percentage of global tall forest area protected based on the 2017 World Database on Protected Areas. We also determined the global extent and protection level of undisturbed, mature, tall forests based on the 2020 Global Intact Forest Landscapes mask. In most cases, the percentage of protection decreased as forest height reached the top strata. In the low-protection zones,<30% of forests were protected in almost all tall forest strata. In countries such as Brazil, tall forests had a higher per-centage of protection (consistently>30%) compared to forests of lower height, presenting a more effective conservation model than in countries such as the United States, where forest protection was almost uniformly<30% across height strata. Our results show an urgent need to target forest conservation in the greatest height strata, particularly in high-protection areas, where most global tall forests are found. Vegetation vertical structure can inform the decision-making process toward the 30×30 goals because it can be used to identify areas of high conservation value for biodiversity protection which also contribute to carbon sequestration.
File: Conservation-Biology-2023-Huang-Prioritizing-global-tall-forests-toward-the-30-30-goals.pdf
