A tool for analysis of the influence of the Earth surface soil layer temperature on the inhomogeneity of grain crops development by the Earth remote sensing data

The work is devoted to the analysis of the influence of the earth surface temperature on the inhomogeneity of the agricultural crops development. The aim of the work is to expand the object-relational model for describing the inhomogeneous spatial structure of a spatial object by including surface temperature as one of the key features that allow determining the cause of vegetation heterogeneity, along with relief features, differences in the soil chemical composition and other significant characteristics. Experimental studies are carried out at sites located in Sukhobuzimsky district of Krasnoyarsk Territory, for which agricultural crops (grains) and the their sowing dates are known a priori, which allows stating any facts of the vegetation development deviation from the normative trajectory with reference to the sequence and timing norms of phenological phase changing. Landsat-8 OLI (Operational Land Imager) TIRS (Thermal Infrared Sensor) data are used as initial data for temperature measurements. Objects of research are presented in the form of a polygon map in SHP format. The temperature values are calculated using the algorithm for estimating the earth temperature developed by Weng Q., Lu D. and Schubring J. The surface reflectance values are the NDVI vegetation index values also obtained from the Landsat-8 OLI data that underwent atmospheric correction by the DOS method. The research results are implemented in the form of a software module and integrated into the Earth remote monitoring (ERM) system of SFU Space and Information Technologies Institute (SITI). The results are used within the concept of object-oriented monitoring of spatial objects developed by the team of authors, and represent index images of the surface temperature of objects, as well as vector schematic maps.

Distribution and habitat use of the Madagascar Peregrine Falcon: first estimates for area of habitat and population size

Accurately demarcating species distributions has long been at the core of ecology. Yet our understanding of the factors limiting species range limits is incomplete, especially for tropical species in the Global South. Human-driven threats to the survival of many taxa are increasing, particularly habitat loss and climate change. Identifying distributional range limits of at-risk and data-limited species using Species Distribution Models (SDMs) can thus inform spatial conservation planning to mitigate these threats. The Madagascar Peregrine Falcon (Falco peregrinus radama) is the resident sub-species of the Peregrine Falcon complex distributed across Madagascar, Mayotte, and the Comoros Islands. Currently, there are significant knowledge gaps regarding its distribution, habitat preferences and population size. Here, we use point process regression models and ordination to identify Madagascar Peregrine Falcon environmental range limits and propose a population size estimate based on inferred habitat. From our models, the core range of the Madagascar Peregrine Falcon extends across the central upland plateau of Madagascar with a patchier range across coastal and low-elevation areas. Range-wide habitat use indicated that the Madagascar Peregrine Falcon prefers areas of high elevation and aridity, coupled with high vegetation heterogeneity and > 95 % herbaceous landcover, but generally avoids areas of > 30 % cultivated land and > 10 % mosaic forest. Based on inferred high-class habitat, we estimate this habitat area could potentially support a population size ranging between 150-300 pairs. Following International Union for Conservation of Nature Red List guidelines, we recommend this sub-species be classed as Vulnerable, due to its small population size. Despite its potentially large range, the Madagascar Peregrine has specialized habitat requirements and would benefit from targeted conservation measures based on spatial models in order to maintain viable populations.

Range-wide habitat use and Key Biodiversity Area coverage for a lowland tropical forest raptor across an increasingly deforested landscape

Quantifying habitat use is important for understanding how animals meet their requirements for survival and provides useful information for conservation planning. Currently, assessments of range-wide habitat use that delimit species distributions are incomplete for many taxa. The harpy eagle (Harpia harpyja) is a raptor of conservation concern, widely distributed across Neotropical lowland forests, that currently faces threats from increasing habitat loss and fragmentation. Here, we use a logistic regression modelling framework to identify habitat resource selection and predict habitat suitability based on a new method developed from the International Union for the Conservation of Nature Area of Habitat range metric. From the habitat use model, we performed a gap analysis to identify areas of high habitat suitability in regions with limited coverage in the Key Biodiversity Area (KBA) network. Range-wide habitat use indicated that harpy eagles prefer areas of 70-75 % evergreen forest cover, low elevation, and high vegetation heterogeneity. Conversely, harpy eagles avoid areas of >10 % cultivated landcover and mosaic forest, and topographically complex areas. Our habitat use model identified a large continuous area across the pan-Amazonia region, and a habitat corridor from the Chocó-Darién ecoregion of Colombia running north along the Caribbean coast of Central America. Little habitat was predicted across the Atlantic Forest biome, which is now severely degraded. The current KBA network covered 18 % of medium to high suitability harpy eagle habitat exceeding the target representation (10 %). Four major areas of high suitability habitat lacking coverage in the KBA network were identified in the Chocó-Darién ecoregion of Colombia, western Guyana, and north-west Brazil. We recommend these multiple gaps of habitat as new KBAs for strengthening the current KBA network. Modelled area of habitat estimates as described here are a useful tool for large-scale conservation planning and can be readily applied to many taxa.

The forest avifauna of Arabuko Sokoke Forest and adjacent modified habitats

Arabuko Sokoke Forest (ASF) is the largest area of coastal forest remaining in East Africa and a major Important Bird Area in mainland Kenya. The study analysed data from point count surveys over 15 months in three land use types; primary forest (PF), plantation forest (PL), and farmlands (FM), and compared these to the first comprehensive bird checklist for the forest, as well as recent surveys from other studies. Avifaunal diversity and abundance were compared using multivariate analysis to determine bird responses to different land use characteristics. The primary forest held a distinctive bird community, while the bird communities of farmlands and plantation forest were more similar to each other. Land use had a significant effect on overall avian diversity and abundance. The current forest avifauna was divided into forest specialists (16 species), forest generalists (26 species) and forest visitors (30 species). Seven species of forest specialist and generalists recorded prior to 1980 may no longer occur in the forest. Of 38 specialists and generalists recorded in our point counts, 19 were also recorded on farmland and 28 in plantations. One forest specialist, the Green Barbet, was most encountered outside the forest. Future research should focus on habitat use by these bird species, and the extent of movement by forest birds between the remaining patches of coastal forest. Patterns of habitat use by birds in the area suggest that vegetation heterogeneity and habitat complexity are especially significant in sustaining diverse and abundant bird populations. The management of plantations and farmland will be critical for the conservation of forest generalists and forest visitors.

Examination of Current and Future Permafrost Dynamics Across the North American Taiga-Tundra Ecotone

<p>In the Arctic, the spatial distribution of boreal forest cover and soil profile transition characterizing the taiga-tundra ecological transition zone (TTE) is experiencing an alarming transformation. The SIBBORK-TTE model provides a unique opportunity to predict the spatiotemporal distribution patterns of vegetation heterogeneity, forest structure change, arctic-boreal forest interactions, and ecosystem transitions with high resolution scaling across broad domains. Within the TTE, evolving climatological and biogeochemical dynamics facilitate moisture signaling and nutrient cycle disruption, i.e. permafrost thaw and nutrient decomposition, thereby catalyzing land cover change and ecosystem instability. To demonstrate these trends, in situ ground measurements for active layer depth were collected to cross-validate below-ground-enhanced modeled simulations from 1980-2017. Shifting trends in permafrost variability (i.e. active layer depth) and seasonality were derived from model results and compared statistically to the in situ data. The SIBBORK-TTE model was then run to project future below-ground conditions utilizing CMIP6 scenarios. Upon visualization and curve-integrated analysis of the simulated freeze-thaw dynamics, the calculated performance metric associated with annual active layer depth rate of change yielded 76.19%. Future climatic conditions indicate an increase in active layer depth and shifting seasonality across the TTE. With this novel approach, spatiotemporal variation of active layer depth provides an opportunity for identifying climate and topographic drivers and forecasting permafrost variability and earth system feedback mechanisms.</p>

Short-Term Dynamics of Vegetation Diversity and Aboveground Biomass of Picea abies (L.) H. Karst. Forests after Heavy Windstorm Disturbance

Although forest disturbances have become more frequent and severe due to ongoing climate change, our understanding of post-disturbance development of vegetation and tree–herb layer interactions remains limited. An extreme windstorm, which occurred on 19 November 2004, destroyed Picea abies (L.) H. Karst dominated forests in the High Tatra Mts. Here, we studied short-term changes in diversity, species composition, and aboveground biomass of trees and herb layer vegetation, including mutual relationships that elucidate tree–herb interactions during post-disturbance succession. Assessment of species composition and tree biomass measurements were performed at 50 sample plots (4 × 4 m) along two transects 12, 14, and 16 years after the forest destruction. Heights and stem base diameters of about 730 trees were measured and subsequently used for the calculation of aboveground tree biomass using species-specific allometric relationships. Aboveground biomass of herb layer was quantified at 300 subplots (20 × 20 cm) by destructive sampling. Species richness and spatial vegetation heterogeneity did not significantly change, and species composition exhibited small changes in accordance with expected successional trajectories. While aboveground tree biomass increased by about 190%, biomass of annual herb shoots decreased by about 68% and biomass of perennial herb shoots was stable during the studied period. The contribution of trees to total aboveground biomass increased from 83% to 97%. After 16 years of forest stands recovery, tree biomass represented approximately 13% of forest biomass before the disturbance. Herb layer biomass, particularly the biomass of annual herb shoots, was more closely related to tree cover than to tree biomass and its decline could be assigned to gradual tree growth. Our study provides clear evidence that short-term successional processes in post-disturbance vegetation are much better detectable by biomass than by diversity or compositional measures and emphasized the importance of light conditions in tree–herb competitive interactions.

Seasonal and inter-annual drivers of yellow fever transmission in South America

In the last 20 years yellow fever (YF) has seen dramatic changes to its incidence and geographic extent, with the largest outbreaks in South America since 1940 occurring in the previously unaffected South-East Atlantic coast of Brazil in 2016–2019. While habitat fragmentation and land-cover have previously been implicated in zoonotic disease, their role in YF has not yet been examined. We examined the extent to which vegetation, land-cover, climate and host population predicted the numbers of months a location reported YF per year and by each month over the time-period. Two sets of models were assessed, one looking at interannual differences over the study period (2003–2016), and a seasonal model looking at intra-annual differences by month, averaging over the years of the study period. Each was fit using hierarchical negative-binomial regression in an exhaustive model fitting process. Within each set, the best performing models, as measured by the Akaike Information Criterion (AIC), were combined to create ensemble models to describe interannual and seasonal variation in YF. The models reproduced the spatiotemporal heterogeneities in YF transmission with coefficient of determination (R2) values of 0.43 (95% CI 0.41–0.45) for the interannual model and 0.66 (95% CI 0.64–0.67) for the seasonal model. For the interannual model, EVI, land-cover and vegetation heterogeneity were the primary contributors to the variance explained by the model, and for the seasonal model, EVI, day temperature and rainfall amplitude. Our models explain much of the spatiotemporal variation in YF in South America, both seasonally and across the period 2003–2016. Vegetation type (EVI), heterogeneity in vegetation (perhaps a proxy for habitat fragmentation) and land cover explain much of the trends in YF transmission seen. These findings may help understand the recent expansions of the YF endemic zone, as well as to the highly seasonal nature of YF.