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Land productivity dynamics in Socotra Island (Yemen)
Abstract
Socotra, the largest of four islands in the Socotra archipelago (Yemen), is characterized by high geo-morphological and biological diversity. Traditional management of land resources has been impacted by cultural shifts, globalization and urban expansion. In addition, the island has been affected by climate impacts, such as droughts and recent cyclones causing significant economic and environmental damage. Our study presents an analysis of the dynamics of the vegetation on the island for the period 2001-2019 and highlights the status of different landscapes. We used Earth Observation techniques and the Normalized Difference Vegetation Index to assess land productivity dynamics basing on vegetation indexes derived from average resolution satellite images. The results show that although the arid landscapes of Socotra seem resilient, over 30% of the central mountainous areas of the Hageher (hosting a unique and high biodiversity) are decreasing in productivity , whereas in the lowlands (where plant diversity is relatively lower) productivity has increased significantly for the same time period, up to 40% in some areas. Given the difference in biological diversity of the sites, this study can help prioritize conservation areas and activities, which are crucial for Socotra's terrestrial environment. The methodology applied could be replicated for continuous monitoring in the future.
... The RF classifier has increasingly drew the attention from researchers due to its generalised performance and operation speed (Belgiu and Drȃguţ, 2016). Hence, the multi-annual variations of vegetation indices, therefore can be considered an excellent proxy for semi-natural ecosystems (Rezende et al., 2020). the combination of Normalized Difference Vegetation Index (NDVI) from satellite images and the K-means algorithm has been developed likewise and adopted for the characterisation and analysis of grassland types and for monitoring vegetation changes (Edirisinghe et al., 2012;Schwieder et al., 2020). ...
Semi-natural grasslands represent a vital source of forage and fodder for livestock farming, fulfilling an essential ecological function.
This study upholded the efficacy of Sentinel-2 time series data in conjunction with ground data on aboveground biomass (AGB), ecological composition, and floristic composition for the development of a prediction model to determine AGB yield and species distribution in a semi-natural grassland. Two machine learning (ML) approaches, namely K-means clustering, and Random Forest (RF) classification were employed in a semi-natural grassland in Southern Europe. The study was subjected to a qualitative ground survey that identified two main groups. The first group (Cluster 1) was composed of nitrophilous species or nitrophilous species combined with xerophilous species and some hygrophilous species.The second group, on the other hand, consisted of only hygrophilous species or hygrophilous species associated with Ranunculus acris, Bromus hordeaceus, Brassica nigra, Lolium perenne and Trifolium sp. (Cluster 2).
Using the above-mentioned algorithms, the study identified thetwo distinctive areas based on AGB estimates in the period beginning in March (vegetative growth) and extending to the first half of May. The R2 value for K-means classification was 0.59, with a root mean square error (RMSE) value of 1 t ha−1.The R2 value for the RF classification was 0.69, with an RMSE value of 0.59 t ha−1. The integration of ground-based data and ML classification techniques enables the generation of accurate, dynamic information on grassland, core attributes that play an integral role in sustainable ecosystem management and conservation.
... The observed significant correlations between VIs and ground data on grassland biomass production confirmed a large body of literature reporting the effectiveness of these indices derived from the green-red-NIR regions in predicting forage availability (Muñoz et al., 2010;Maselli et al., 2013;Gómez-Giráldez et al., 2019;Rezende et al., 2020). The VIs proved their reliability in describing the overall biomass patterns, even if their performances can be limited due to the saturation issues, as observed by Ullah et al. (2012) using NDVI and SAVI. ...
The oversowing of legume-rich mixtures is a management practice gaining importance in Mediterranean silvopastoral farms due to enhanced forage production, quality, and ecosystem service provision. However, the oversowing of legume species can be expensive in silvopastoral farms due to the high cost of legume seeds and seeding operations and low persistence under inadequate management. The study aimed to assess the long-term impacts of legume-rich mixtures oversowing on pasture production of Mediterranean wooded grasslands with a remote sensing approach. The study was conducted on six Dehesa farms in Western Spain, where legume mixtures had been sown in different years from 2002 to 2015 in part of the farms. The effects of legume species oversowing were assessed by analyzing the variation across years of a set of derived vegetation indices in sown and unsown areas of each farm. Among all considered vegetation indices, the Simple Ratio (SR) and the Normalized Difference Vegetation Index (NDVI) showed the highest capacity in estimating grassland yield (Pearson's r = 0.58 and 0.52, P < 0.01, respectively) and N content (r = 0.52 and 0.48, P < 0.05, respectively). All normalized vegetation indices increased after the sowing and remained significantly higher than before sowing (P < 0.001) for the whole monitoring period. Furthermore, the sowing also positively affected the temporal stability of each vegetation index, being interannual variability significantly higher (P < 0.01) before the sowing than after. The study confirmed the hypothesis that the oversowing of legume-rich mixtures in Mediterranean wooded grasslands effectively improves intra- and interannual biomass production and stability. Remote sensing using Landsat images proved to be an effective tool to assess the impacts of grassland management practices in the long term in silvopastoral systems.
... Analysing the direction and magnitude of the variation in the hydro-climatic variables is important for understanding climate change and providing a basis for determining future scenarios of climate impact (Chaouche et al. 2010;Reiter et al. 2012;Unal et al. 2012;Asfaw et al. 2018;Meshram et al. 2020). Detecting the historical trend of vegetation, often expressed in normalized difference vegetation index (NDVI) and land use/cover changes, particularly improves our understanding of the changing planet and provides a clue about the productivity of lands (Tian et al. 2015;Gichenje and Godinho 2018;Frédérique et al. 2019;Rezende et al. 2020). Trend analysis of hydro-climatic variables and vegetation is particularly relevant for water resource decisionmakers as they prepare to deal with the possible effects of climate variability and change on water availability (Sahoo and Smith 2009;Oguntunde et al. 2006;Zhou et al., 2015a, b;Tehrani et al. 2019). ...
The Nasia catchment is the reservoir with significant surface water resources in Northern Ghana and home to numerous subsistence farmers engaged in rainfed and dry season irrigation farming. Yet, there is little understanding of the hydro-climatic and land use/cover conditions of this basin. This study investigated trends, relationships and changes in hydro-climatic variables and land use/cover in addition to implications of the observable changes in the Nasia catchment over a period of 50 years. Parameters used for the study were minimum (Tmin) and maximum temperature (Tmax), wind speed (WS), sunshine duration (S), rainfall (R), relative humidity (RH), discharge (D) and potential evapotranspiration (PET) data, 15 years of remotely sensed normalized difference vegetation index (NDVI) data and 30 years of land use/cover image data. Results show that Tmin, Tmax, WS and PET have increased significantly ( p < 0.05) over time. RH and S significantly declined. R, D and NDVI have not decreased significantly ( p > 0.05). A significant abrupt change in almost all hydro-climatic variables started in the 1980s, a period that coincides with the occurrence of drought events in the region, except WS in 2001, R in 1968 and D in 1975, respectively. Also, D showed a positive significant correlation with RH, R and PET, but an insignificant positive relationship with S. D also showed a negative insignificant correlation with Tmin, Tmax and WS. Areas covered with shrubland and settlement/bare lands have increased to the disadvantage of cropland, forest, grassland and water bodies. It was concluded that climate change impact is quite noticeable in the basin, indicating water scarcity and possibilities of droughts. The analysis performed herein is a vital foundation for further studies to simulate and predict the effect of climate change on the water resources, agriculture and livelihoods in the Nasia catchment.
... The combined effects of climate variability, land use/cover changes and unsustainable water management practices have led to a significant alteration in the water balance of the river basins (Buma et al. 2016) Analysing the direction and magnitude of the variation in the hydro-climatic variables is considered valuable for understanding climate change and providing a basis for determining future scenarios of climate impact (Chaouche et al. 2010;Reiter et al. 2012;Unal et al. 2012;Asfaw et al. 2018;Meshram et al. 2020). Detecting the historical trend of vegetation, often expressed in Normalized Difference Vegetation Index (NDVI), land use/cover changes particularly improve our understanding of the changing planet and provides a clue about the productivity of lands (Tian et al. 2015;Gichenje and Godinho, 2018;Frédérique et al. 2019;Rezende et al. 2020). Trend analysis of hydro-climatic variables and vegetation is particularly relevant for water resource decision makers as they prepare to deal with the possible effects of climate variability and change on water availability (Sahoo and Smith 2009;Oguntunde et al. 2006;Tehrani et al. 2019). ...
The Nasia catchment is the reservoir for significant surface water resources in Northern Ghana and home to numerous subsistence farmers engaged in rainfed and dry season irrigation farming. Yet there is little understanding of the hydro-climatic and land use /cover conditions of this basin. We analyzed 50 years of minimum (Tmin) and maximum temperature (Tmax), wind speed (WS), sunshine duration(S), Rainfall(R), relative humidity (RH), discharge (D) and potential evapotranspiration (PET) data, 15 years of remotely sensed normalized difference vegetation index (NDVI) data and 30 years of land use/cover image data. Results show that Tmin, Tmax, WS, and PET have increased significantly (P < 0.05). RH and S significantly declined. R, D and NDVI have insignificantly decreased (P > 0.05). A significant abrupt change in almost all hydroclimatic variables started in the 1980s, a period that coincides with the occurrence of drought events in the region except WS in 2001, R in 1968 and D in 1975. Also, D showed a positive significant correlation with RH, R and PET, but insignificant positive relationship with S. D also showed negative insignificant correlation with Tmin, Tmax and WS. Areas covered with shrubland and settlement/bare lands have increased to the disadvantage of cropland, forest, grassland and water bodies. We conclude that climate change impact is quite noticeable in the basin; indicating water scarcity and possibilities of droughts. The analysis performed herein is a vital foundation for further studies to simulate and predict the effect of climate change on the water resources, agriculture and livelihood in the Nasia basin.
... In particular, the 30 × 30 m pixel resolution of the publicly available Landsat TM data (Nagendra et al., 2013) can allow for relatively fast mapping of biomass patterns, using well-known indices such as the Normalized Difference Vegetation Index (NDVI) obtained from a spectral transformation of the red and near infrared bands. NDVI showed to be well correlated to aboveground phytomass, especially in grassland ecosystems (Muñoz et al., 2010;Mangiarotti et al., 2012), hence the multi-annual variations of NDVI can be considered a good proxy to study changes in ANPP (Rezende et al., 2020). ...
The modification of precipitation regimes and the increase in summer aridity under the predicted climate change scenarios are hypothesized to have repercussions on the semi-extensive pastoral systems of Mediterranean grasslands, leading to change in forage quantity/quality, increased interannual variability in phytomass production, reduction of the carrying capacity of rangelands, and worsening of animal welfare. The research aims were to find what climatic features affect changes in the annual peak of Aboveground Net Primary Production (ANPP), and how topographic variables and management conditions influence these variations in a pastoral system of central Apennines (Italy).
We monitored Normalized Difference Vegetation Index (NDVI) variations at the peak of phytomass production using Landsat satellite images, used as a proxy for ANPP changes in the most productive phase of the growing season, when herds are carried to pastures and hay-meadows are mown, on a dataset of 10,000 randomly sampled pixels (30 × 30 m), in the years 2003, 2007, 2009, 2010, and 2013−2015. We investigated the relation between NDVI and climatic variables, topographic parameters, vegetation physiognomy, and management type, using generalized linear mixed-effects modeling, variation partitioning, and correlation analysis.
We observed an increase in average yearly temperatures and high variability in the rainfall seasonal distribution pattern, particularly of spring precipitation. Climatic fluctuations influenced the overall amount of forage production more than management and topographic conditions. The spring variation of climatic variables (precipitation in March, drought stress in April and May), the drought and cold stress intensities in the previous year and the cold stress in the preceding winter were the main drivers of NDVI change. The landform factors interacted with climate variability in determining the amplitude of NDVI changes, which were the widest in semi-flat mountain tops and flat valley bottoms and the smallest in south-facing slopes. The effect of the climatic variables on NDVI was different depending on the management condition, suggesting that grassland management partially filters the climatic drivers of changes in forage production. Based on our results, the most productive grassland communities and the areas used for grazing by domestic herbivores could be the most impacted by the predicted climate changes for the Mediterranean basin, potentially reducing the economic sustainability of semi-extensive farming in the Apennine mountains.
... As a result of the combination of such long-term decline due to overgrazing, catalyzed by climate change, these tree species are heading towards extinction if there is no conservation intervention (Mad era et al., 2019;. A general decline of the terrestrial ecosystems over the last few decades is apparent through the analysis of satellite imagery, in particular, in the biodiversity-rich plateaus and mountain areas of Socotra Rezende et al., 2020). Urbanization around the main cities has also impacted aquatic habitats on the island, such as the coastal lagoons, which may be altered from construction works, pollution and insecticides . ...
The Socotra Archipelago contains islands of high conservation importance. Since 2003, the Socotra Archipelago is a UNESCO Man and Biosphere Reserve and since 2008 it was officially listed as a UNESCO Natural World Heritage Site. In addition, the Socotra Archipelago contains currently the only Ramsar Site of Yemen (Detwah Lagoon), and it has been declared as one of 200 WWF Global Ecoregions for its unique terrestrial ecosystems (xeric shrublands), the status indicated as critical/endangered by WWF. Even the freshwater ecosystems that harbor several endemics have been given a special status, as Socotra is recognized as one of the globally outstanding Freshwater Ecoregions of the World. Socotra is also part of the Horn of Africa Biodiversity Hotspot as recognized by Conservation International, and listed as a Centre of Plant Diversity by Plantlife International, ranked among the richest yet most threatened biodiversity areas on the Planet. The Archipelago was declared as its own Ecologically or Biologically Significant Marine Area (EBSA) at the Convention of Biological Diversity (CBD) meeting in 2016, and the same year as an Endemic Bird Area by BirdLife International, which listed several Important Bird Areas (IBAs) for the Archipelago. A number of endemic plants and vertebrates from Socotra have been included in the IUCN Red List, but updates are needed and very few of the many endemic invertebrates have been listed. However, the biodiversity of Socotra is increasingly affected by impacts that affect ecosystems globally, such as unsustainable resource use and global warming which are now visible in the islands. We discuss the main threats and list some general conservation needs in the Socotra Archipelago.
... Therefore, the declines or the disappearance of vegetation through a combination of factors, may accelerate the direct extinction of associated species in the absence of vegetation cover. Considering the rapid changes in vegetation over the last decades (Lvoncik et al. 2020; Rezende et al. 2020), the fact that some endemic reptiles have a total area of occupation of less than 10 km 2 (Fasola et al. 2020) and the presence of invasives such as rats and cats, extinction scenarios for these island endemics are realistic if there is no direct intervention. ...
The topical collection ‘Twenty years of biodiversity research and nature conservation in the Socotra Archipelago’, in short ‘Socotra biodiversity research and nature conservation’ was conceived at the 18th Friends of Socotra annual meeting and Socotra conference which took place at the Orto Botanico di Palermo, Palermo, Italy, 26–29 September, 2019. In total, 13 research papers are included in the collection, which covers a selection of the latest scientific progress on the fauna and flora of the terrestrial and aquatic environments of the Socotra Archipelago UNESCO World Heritage Site (Yemen). Topics include conservation, taxonomy, ecology, biology and biogeography. The focus is mainly on biodiversity conservation and aimed at identifying current challenges, trends and processes that may impact on local ecosystems and livelihoods, based on analysis of data collected over the last decades. With this collection, we wish to emphasise the importance of taking into account science-based conservation approaches in future strategic steps towards safeguarding the ecosystems of Socotra.
The Socotra Archipelago (Yemen) is an interesting biodiversity hotspot, with a significant proportion of endemic species that have evolved to survive in an arid subtropical environment, inscribed as a World Heritage Site by UNESCO. The terrestrial ecosystems of Socotra face several threats, including climate change, overgrazing and soil degradation. Socotra Island has four endemic species of the genus Commiphora (Burseraceae). Little is known about their local distribution and ecology, yet these trees could be useful indicator species. Our study focuses on the distribution and niche characterisation of the four endemic Commiphora species of Socotra and how climate change may affect them. The aim is to improve insights into their habitats and to provide an essential basis for future local management plans and ecological restoration. We compared the current distribution with the forecasted potential distribution under a CMIP6 (Coupled Model Intercomparison Project) climate scenario, allowing us to define target conservation areas and assess potential local extinction risks. To achieve this, we collected distribution data in the field throughout Socotra Island, covering the current distribution ranges of the four species. To assess the potential distribution of these species, we applied three models (GAM, MaxEnt, RandomForest) using bioclimatic, topographic and soil variables. Forecasts under a climate change scenario were made using bioclimatic variables from the CMCC-CESM2 climate model for two different socioeconomic pathways. The distribution of three endemic Socotran Commiphora is mainly correlated to clay content in the soil and winter precipitation, while C. socotrana is affected by seasonal precipitation and temperature. Under different potential future climate scenarios, the distribution of C. ornifolia is predicted to remain stable or increase, while C. parvifolia distribution could increase, yet C. planifrons and C. socotrana are predicted to undergo a strong reduction of suitable areas and an upward shift in the mountains. Our results highlight that it is essential to conserve the unique terrestrial ecosystems in Socotra and to preserve these endemic trees which have a wide range of ecosystem services. Updates on the predicted extinction risk assessment are fundamental to understand conservation priorities and strategize future actions to ensure the persistence of Socotran myrrh trees and other endangered endemic tree taxa on the island.
Background
In this study, we present and analyze toponyms referring to Socotra Island’s endemic dragon’s blood tree ( Dracaena cinnabari ) in four areas on the Socotra Archipelago UNESCO World Heritage site (Republic of Yemen). The motivation is the understanding of the past distribution of D. cinnabari trees which is an important part of conservation efforts by using ethnobotanical data. We assumed that dragon’s blood trees had a wider distribution on Socotra Island in the past.
Methods
This research was based on field surveys and interviews with the indigenous people. The place names (toponyms) were recorded in both Arabic and the indigenous Socotri language. We grouped all toponyms into five different categories according to the main descriptor: terrain, human, plant, water, and NA (unknown). Also, this study identified current and historical Arabic names of dragon’s blood trees of the genus Dracaena through literature review.
Results
A total of 301 toponyms were recorded from the four study areas in Socotra Island. Among names related to plants, we could attribute toponyms to nine different plants species, of which six toponyms referred to the D. cinnabari tree, representing 14.63% of the total phytotoponyms in the category. Three historical naming periods prior to 2000 could be identified. The most commonly used name for dragon’s blood trees ( D. cinnabari , D. serrulata , D. ombet ) appears to be “ ahrieb ” “إعريهب” and its resin “ dum al-akhawin ” “دم الأخوين,” while derived (mixed-cooked) products are called “ eda’a ” “إيدع,” while regionally different names can be found.
Conclusion
The place names that refer to D. cinnabari are herein suggested to represent remnant areas of once large populations. Therefore, the toponyms may support known hypotheses based on climate models that D. cinnabari had a wider distribution on Socotra Island in the past. This study also confirmed the historical importance of dragon’s blood.
Background
In this study, we present and analyze toponyms referring to Socotra Island’s endemic dragon’s blood tree (Dracaena cinnabari) in four areas of the Socotra Archipelago UNESCO World Heritage site (Republic of Yemen). The motivation is understanding of the past distribution of D. cinnabari trees which is an important part of conservation efforts by using ethnobotanical data. We assumed that dragon’s blood trees had a wider distribution on Socotra Island in the past.
Methods
This research was based on field surveys and interviews with the indigenous people. The place names (toponyms) were recorded in both, Arabic and indigenous Socotri language. We grouped all toponyms into five different categories according to the main descriptor: Terrain, Human, Plant, Water and NA (unknown). In addition, this study identified current and historical Arabic names of dragon’s blood trees of the genus Dracaena, through literature review.
Results
A total of 301 toponyms were recorded from the four study areas in Socotra Island. Among names related to plants, we could attribute toponyms to nine different plant species, of which six names referred to the D. cinnabari tree, representing 14.63% of total phytotoponyms in the category. Three historical naming periods prior to 2000 could be identified. The most commonly used Arabic name for dragon’s blood trees (D. cinnabari, D. serrulata. D. ombet) appears to be “ahrieb” "إعريهب", its resin “dum al-akhawin” “دم الأخوين”, while derived (mixed-cooked) products are called “edah” “إيدع”; while regionally different names can be found.
Conclusion
The place names that refer to D. cinnabari are herein suggested to represent remnant areas of once large populations. The toponyms may therefore support known hypotheses based on climate models that D. cinnabari had a wider distribution on Socotra Island in the past. This study also confirmed the historical importance of dragon’s blood
Unsustainable overgrazing is one of the most important threats to the endemic and endangered population of dragon’s blood tree (Dracaena cinnabari) on Socotra Island (Republic of Yemen). However, there is a lack of information about the exact population size and its conservation status. We estimated the population size of D. cinnabari using remote sensing data. The age structure was inferred using a relationship between crown projection area and the number of branch sections. The conservation importance of each sub-population was assessed using a specially developed index. Finally, the future population development (extinction time) was predicted using population matrices. The total population size estimated consists of 80,134 individuals with sub-populations varying from 14 to 32,196 individuals, with an extinction time ranging from 31 to 564 years. Community forestry controlled by a local certification system is suggested as a sustainable land management approach providing traditional and new benefits and enabling the reforestation of endemic tree species on Socotra Island.
Cyclone Megh, a category-3 (Saffir-Simpson scale) cyclonic storm is regarded as the worst tropical cyclone to ever strike Yemen’s island of Socotra. In this paper, we aim to investigate the wind structure of cyclone Megh using Synthetic Aperture Radar (RISAT-1 SAR) observations. An algorithm for the cyclone wind retrieval has been applied for SAR data of Nov 8, 2015 at 0238:09 UTC in the Arabian Sea. The intensity of cyclone is 30m/s with the 16.65km radius of maximum wind speed from the centre of the cyclone. The high resolution SAR data analysis bring to focus the possible presence of eyewall mesovortex in case of Megh. Recent work has shown that vorticity mixing in the tropical cyclone (TC) inner core can promote mesovortex (MV) formation and impact storm intensity. This has further been corroborated using INSAT-3D and MODIS optical band observations of clouds. Analysis of these satellite derived cloud microphysical properties shows the presence of larger hydrometeors surrounding the eye due to possible embedding of stratus and stratocumulus cloud decks. Thus, this kind of study helps in understanding the microphysical processes within a TC as well estimating their impacts on cyclone intensity and lifetime.
Cyclone Megh, a category-3 (Saffir-Simpson scale) cyclonic storm is regarded as the worst tropical cyclone to ever strike Yemen’s island of Socotra. In this paper, we aim to investigate the wind structure of cyclone Megh using Synthetic Aperture Radar (RISAT-1 SAR) observations. An algorithm for the cyclone wind retrieval has been applied for SAR data of Nov 8, 2015 at 0238:09 UTC in the Arabian Sea. The intensity of cyclone is 30m/s with the 16.65km radius of maximum wind speed from the centre of the cyclone. The high resolution SAR data analysis bring to focus the possible presence of eyewall mesovortex in case of Megh. Recent work has shown that vorticity mixing in the tropical cyclone (TC) inner core can promote mesovortex (MV) formation and impact storm intensity. This has further been corroborated using INSAT-3D and MODIS optical band observations of clouds. Analysis of these satellite derived cloud microphysical properties shows the presence of larger hydrometeors surrounding the eye due to possible embedding of stratus and stratocumulus cloud decks. Thus, this kind of study helps in understanding the microphysical processes within a TC as well estimating their impacts on cyclone intensity and lifetime.
The health and productivity of global land resources are declining, while demand for those resources is increasing. The aim of land degradation neutrality (LDN) is to maintain or enhance land-based natural capital and its associated ecosystem services. The Scientific Conceptual Framework for Land Degradation Neutrality has been developed to provide a scientific approach to planning, implementing and monitoring LDN. The Science-Policy Interface of the United Nations Convention to Combat Desertification (UNCCD) led the development of the conceptual framework, drawing in expertise from a diverse range of disciplines.
The LDN conceptual framework focuses on the supporting processes required to deliver LDN, including biophysical and socio-economic aspects, and their interactions. Neutrality implies no net loss of the land-based natural capital relative to a reference state, or baseline. Planning for neutrality involves projecting the likely cumulative impacts of land use and land management decisions, then counterbalancing anticipated losses with measures to achieve equivalent gains. Counterbalancing should occur only within individual land types, distinguished by land potential, to ensure “like for like” exchanges. Actions to achieve LDN include sustainable land management (SLM) practices that avoid or reduce degradation, coupled with efforts to reverse degradation through restoration or rehabilitation of degraded land. The response hierarchy of Avoid > Reduce > Reverse land degradation articulates the priorities in planning LDN interventions. The implementation of LDN is managed at the landscape level through integrated land use planning, while achievement is assessed at national level.
Monitoring LDN status involves quantifying the balance between the area of gains (significant positive changes in LDN indicators) and area of losses (significant negative changes in LDN indicators), within each land type across the landscape. The LDN indicators (and associated metrics) are land cover (physical land cover class), land productivity (net primary productivity, NPP) and carbon stocks (soil organic carbon (SOC) stocks).
The LDN conceptual framework comprises five modules: A: Vision of LDN describes the intended outcome of LDN; B: Frame of Reference clarifies the LDN baseline; C: Mechanism for Neutrality explains the counterbalancing mechanism; D: Achieving Neutrality presents the theory of change (logic model) articulating the impact pathway; and E: Monitoring Neutrality presents the LDN indicators. Principles that govern application of the framework provide flexibility while reducing risk of unintended outcomes.
Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google's massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection. It is unique in the field as an integrated platform designed to empower not only traditional remote sensing scientists, but also a much wider audience that lacks the technical capacity needed to utilize traditional supercomputers or large-scale commodity cloud computing resources.
At the 12th Conference of the Parties to the UN Convention to Combat Desertification, Parties were invited to formulate voluntary targets to achieve land degradation neutrality (LDN). This “Conceptual Framework for Land Degradation Neutrality” is intended to provide a scientifically-sound basis for understanding and implementing LDN, and to inform the development of practical guidance for pursuing LDN and monitoring achievement of LDN for those UNCCD Parties that choose to pursue a LDN target. The LDN conceptual framework focuses on the goal of LDN and the supporting processes required to deliver this goal, including biophysical and socio-economic aspects, and their interactions.
The United Nations Convention to Combat Desertification (UNCCD) defines land degradation neutrality as “a state whereby the amount and quality of land resources necessary to support ecosystem functions and services and enhance food security remain stable or increase within specified temporal and spatial scales and ecosystems”.
The goal is maintaining or enhancing the land resource base - in other words, the stocks of natural capital associated with land resources and the ecosystem services that flow from them. The definition emphasises the importance of ecosystem services in achieving sustainability of food production. The objectives of LDN are:
• maintain or improve the sustainable delivery of ecosystem services;
• maintain or improve productivity, in order to enhance food security;
• increase resilience of the land and populations dependent on the land;
• seek synergies with other social, economic and environmental objectives; and
• reinforce responsible and inclusive governance of land.
Pursuit of LDN requires effort to avoid further net loss of the land-based natural capital relative to a reference state, or baseline. Planning for neutrality involves counterbalancing anticipated losses with measures to achieve equivalent gains, within individual land types, where land type is defined by land potential. Integration of planning for LDN interventions into existing land use planning is encouraged. Particular attention is paid to projecting and tracking the likely cumulative impacts of land use and land management decisions. Actions to achieve LDN include land management approaches that avoid or reduce degradation, coupled with efforts to reverse degradation through restoration or rehabilitation of land that has lost productivity. The response hierarchy of Avoid > Reduce > Reverse land degradation articulates the priorities in planning LDN interventions. The implementation of LDN is managed at the landscape scale, considering all land units of each land
type and their interactions and ecological trajectories, so that LDN interventions can be optimized among those land units, in order to maintain or exceed no net loss, per land type. Monitoring achievement of neutrality will quantify the balance between the area of gains (significant positive changes in LDN indicators =improvements) and area of losses (significant negative changes in LDN indicators=degradation), within each land type across the landscape. The LDN indicators (and associated metrics) are land cover (land cover change), land productivity (net primary production) and carbon stocks (soil organic carbon).
The LDN conceptual framework is designed to be applicable to all land uses (i.e., land managed for production – e.g., agriculture, forestry; for conservation – e.g., protected areas; and also land occupied by human settlements and infrastructure); and all types of land degradation, across the wide variety of countries’ circumstances, so that it can be implemented in a harmonized fashion by all countries that choose to pursue LDN. It helps build the bridge between the vision and the practical implementation of LDN through National Action Programmes, by defining LDN in operational terms.
It is a process framework that captures the vision of what LDN is intended to achieve, and, based on this, provides guidance on how best to assess land degradation and identify appropriate management actions, and ultimately report on progress in achieving LDN.
(SPI, UNCCD secretariat): ISBN 978-92-95110-42-7 (hard copy), 978-92-95110-41-0 (electronic copy).
Land degradation in many Pacific Island Countries (PICs) has become an emerging concern in recent years. The causes of land degradation in PICs include: deforestation, inappropriate agricultural practices, overgrazing, mining, population pressure, land tenure issues and changing climate. Deforestation and inappropriate agricultural practices especially on sloping lands often lead to soil erosion, a key process leading to land degradation. On-site effects of accelerated soil erosion include decline in soil physical properties, loss of soil organic carbon and loss of plant nutrients and subsequently low crop productivity. This threatens the environment and food security for the growing population in PICs. The PICs are embarking on sustainable land management practices to address land degradation and safeguard the resource for their future generation. However, limited resources, lack of capacity and awareness on land degradation amongst the population are serious obstacles to implementation of sustainable land use plans and management.
Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988-2008) vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI) and the recently developed passive-microwave-based Vegetation Optical Depth (VOD). The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.
The study describes main biotopes of Socotra Island. The biotopes were distinguished and described during complex field observations on more than 250 localities of Socotra between years 1999-2004. Classification of biotopes is based on differences in physiognomy, structure and species composition of the vegetation component of present biocoenoses. Groups of biotope types differ, above all, in the physiognomy and structure of vegetation. Biotope types are divided according to composition of dominant species. In this manner, 13 groups of biotopes and 39 biotope types were distinguished and described
http://www.degruyter.com/view/j/jlecol.2013.6.issue-3/jlecol-2014-0004/jlecol-2014-0004.xml?format=INT
The Socotra archipelago is an ancient continental fragment situated in the Western Indian Ocean that has been isolated for at least 18 million years (Ma). Although often described as the ‘Galapagos of the Indian Ocean’, compared to the Galapagos and other island systems, this Arabian Sea archipelago is relatively poorly studied and often overlooked in works on island biology. Nevertheless, the Socotra archipelago is characterised by relatively high floristic diversity and endemism with local adaptations and radiations , making it a good example of a system suitable for the study of island biogeography . We discuss origins, affinities, disjunctions and adaptations in the flora and explore underlying environmental and evolutionary processes that may have helped the Socotra archipelago to its present uniqueness.
Although Haiti is one of the largest Caribbean nations only 20% of the land under cultivation is appropriate for agriculture. Once covered by forest, this country has been heavily logged and now mostly deforested. The majority of the arable land is being farmed beyond their carrying capacity. The total area under agriculture production is 6 times greater than the estimated areas suitable for agriculture resulting in significant deterioration of the land. Both national and international governments have made several attempts to combat desertification but few initiatives have been successful. This research will (1) review the current literature pertaining to desertification, with special emphasis on Haiti, (2) review the impact of internal and external programs designed to reverse the effects of desertification, (3) compare the indicators of desertification that exist on the island of Hispaniola, and (4) discuss the consequences of desertification for Haiti.
Land degradation and desertification has been ranked as a major environmental and social issue for the coming decades. Thus, the observation and early detection of degradation is a primary objective for a number of scientific and policy organisations, with remote sensing methods being a candidate choice for the development of monitoring systems. This paper reviews the statistical and ecological frameworks of assessing land degradation and desertification using vegetation index data. The development of multi-temporal analysis as a desertification assessment technique is reviewed, with a focus on how current practice has been shaped by controversy and dispute within the literature. The statistical techniques commonly employed are examined from both a statistical as well as ecological point of view, and recommendations are made for future research directions. The scientific requirements for degradation and desertification monitoring systems identified here are: (I) the validation of methodologies in a robust and comparable manner; and (II) the detection of degradation at minor intensities and magnitudes. It is also established that the multi-temporal analysis of vegetation index data can provide a sophisticated measure of ecosystem health and variation, and that, over the last 30 years, considerable progress has been made in the respective research.
The ecological land scape classification (ELC) allows the identification of homogeneous land units (LUs), which are fundamental for investigation and management purposes. ELC is particularly relevant in international cooperation programmes targeting areas characterized by very scarce and scattered thematic information. In this study, three techniques are compared to find the best classification of LUs of Socotra Island (Yemen): a Self-Organizing Map neural network, the Clustering LARge Applications method and a Two-Step clustering algorithm. In this way, three LU maps of Socotra Island were produced and the relationship between LUs and plant communities, as identified by a phytosociologiacl investigation, was analysed. Based on evaluation procedures, TS method emerged as the most suitable being able to better discriminate the plant communities so as to reach a trade-off between classification complexity and class homogeneity. Even though the identification of LUs depends on the selection of the classification method and criteria, the scale adopted and the specific management and planning purposes, this study represents a contribution towards a standardization of ecological classification systems thanks also to the worldwide availability of georeferenced environmental data.
Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geo-morphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum like-lihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.
Age determination of tropical trees, and monocotyledons in general, is not an easy task. Representatives of the Dracaena genus have survived in woodlands on dry margins of the Tethys tropical forest since the Tertiary Period. Here we present analyses of Dracaena cinnabari (DC) stand dynamics via direct and indirect methods of age determination. The direct method has taken advantage of historical photographs of DC mountain woodlands from Soqotra during an Austrian scientific expedition in 1899 by comparing these with the woodland stage in 2004. A decline in the number of tree individuals is obvious, but considering the little that is known about dynamics of DC woodland, one cannot simply state that such decline means forest destruction. The results from this direct method are compared to an indirect mathematical method of age determination using data from 2003. Indirect age determination values differed only about 6.5% from those obtained with the direct method, indicating that the indirect methodology is quite precise.
The change history of vegetation cover and its relations to growing season precipitation (GSP) and average growing season temperature (AGST) in the source region of the Yellow River (SRYR) during 1990-2000 was retrieved based on the 1 km Advanced Very High-Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data and meteorological records. The results show an overall warming and drying trend of the climate and a common degradation tendency of the ecosystem, with a greening trend in higher rugged regions. The pixel-by-pixel correlations between NDVI and climate factors indicate that a decrease in GSP mainly affects ecosystems with low precipitation and worse vegetation condition, and superimposes on the effects of increasing AGST which further deteriorate the climate background of these ecosystems. However, the positive correlations between AGST and NDVI in some higher/rugged regions suggest that the raising temperature can ameliorate vegetation growth conditions in these areas. Comparison and combination of the results of three change detection algorithms, i.e. post-classification comparison (PCC), principal components analysis (PCA) and a newly developed multi-temporal image difference (MTID) method, show that the integration of different methods can give a more comprehensive understanding of vegetation changes than any single method.
The Socotra archipelago, Yemen, in the north-west Indian Ocean, has outstanding endemic biodiversity, and was listed as a World Heritage Site in 2008. Although inhabited for 6 millennia Socotra only began to open up to the outside world in 1990. With conservation interventions starting prior to major developments, and building on centuries-old low-intensity resource management, Socotra has been in a unique position to practice pre-emptive conservation. In 1997 modern conservation started with biodiversity and socio-economic surveys, with inputs from communities and decision makers, which fed into the Conservation Zoning Plan. Approved in 2000, this has been the archipelago’s principal conservation planning and management tool. Regulations and bans on fishing practices, the collection of coral stones and export of biological materials have all been relatively well complied with by local communities and authorities. Inappropriate road construction, however, driven by non-islanders, has demonstrated the limits of the Conservation Zoning Plan, highlighting significant institutional challenges in planning and coordination. The capacity of the Socotra-based conservation institution has increased dramatically over the last decade. Its personnel are generally respected, largely because their roles include assisting local communities with development initiatives, underlining the importance of integrating conservation and development at the onset of conservation. Although the integrity of the landscape will inevitably decline, especially along the northern coastline, Socotri conservationists, backed by international support, are in a unique position to shape the archipelago’s future.
The Socotra Archipelago (Yemen) is globally recognized for its outstanding biodiversi-ty and endemism, designated on this basis a UNESCO World Heritage Site in 2008. The island underwent long geological and political isolation, ensuring preservation of unique ecosystems un-til the start of the new millennium. Now, Socotra Island is undergoing rapid development, out of balance with conservation. Major causes for biodiversity loss in other global insular ecosystems such as habitat fragmentation and degradation, pollution, invasive species and the impact of tour-ism, are becoming pressing issues that deserve close attention. Unsustainable resource use, the loss of traditional land management and illegal trade in biota are worrying phenomena that further increase the pressures on Socotra's ecosystems. We provide the first comprehensive review of potential human impacts on Socotra before the 21 st century, an updated discussion of some of the principal threats to its biodiversity in recent times, discussing local examples within a historical context of known extinction processes on islands, and underline the importance of traditional knowledge in the protection of Socotran ecosystems.
At first view, soil erosion on Socotra Island, Yemen would seem to be a minor problem. This appraisal is based on the fact
that on the one hand the island is poor in soil resources, and on the other hand research on the island has to date focussed
on biodiversity. However, results of soil investigations on Socotra showed that in the Homhil Protected Area land degradation
in terms of erosion due to soil structure deterioration and humus loss has increased drastically: within 3 years a loss of
about 40 m3 in a single gully head was estimated. Soil loss inevitably involves uprooting of trees and a decrease in soil fauna. Biodiversity
is, of course, the most important argument for protecting the unique floral and faunal richness of the island, but what would
terrestrial biodiversity be without soils? The present approach relies on a “down-to-earth” system of soil monitoring, based
on both modern and ancient knowledge and oriented towards current environmental and political objectives. It should be understood
as a first step towards conserving soils and vegetation in a Protected Area of this tropical island.
KeywordsAncient indigenous knowledge-Soil conservation-Biodiversity-Socotra island-Yemen
Remote sensing data have become very widespread in recent years, and the exploitation of this technology has gone from developments mainly conducted by government intelligence agencies to those carried out by general users and companies. There is a great deal more to remote sensing data than meets the eye, and extracting that information turns out to be a major computational challenge. For this purpose, high performance computing (HPC) infrastructure such as clusters, distributed networks or specialized hardware devices provide important architectural developments to accelerate the computations related with information extraction in remote sensing. In this paper, we review recent advances in HPC applied to remote sensing problems; in particular, the HPC-based paradigms included in this review comprise multiprocessor systems, large-scale and heterogeneous networks of computers, grid and cloud computing environments, and hardware systems such as field programmable gate arrays (FPGAs) and graphics processing units (GPUs). Combined, these parts deliver a snapshot of the state-of-the-art and most recent developments in those areas, and offer a thoughtful perspective of the potential and emerging challenges of applying HPC paradigms to remote sensing problems.
Endemism and species richness are highly relevant to the global prioritization of conservation efforts in which oceanic islands have remained relatively neglected. When compared to mainland areas, oceanic islands in general are known for their high percentage of endemic species but only moderate levels of species richness, prompting the question of their relative conservation value. Here we quantify geographic patterns of endemism-scaled richness ("endemism richness") of vascular plants across 90 terrestrial biogeographic regions, including islands, worldwide and evaluate their congruence with terrestrial vertebrates. Endemism richness of plants and vertebrates is strongly related, and values on islands exceed those of mainland regions by a factor of 9.5 and 8.1 for plants and vertebrates, respectively. Comparisons of different measures of past and future human impact and land cover change further reveal marked differences between mainland and island regions. While island and mainland regions suffered equally from past habitat loss, we find the human impact index, a measure of current threat, to be significantly higher on islands. Projected land-cover changes for the year 2100 indicate that land-use-driven changes on islands might strongly increase in the future. Given their conservation risks, smaller land areas, and high levels of endemism richness, islands may offer particularly high returns for species conservation efforts and therefore warrant a high priority in global biodiversity conservation in this century.
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Free image.
This Landsat 5 image of the southeastern corner of the Black Sea is part of the general U.S. archive that will be accessible for free under the new USGS policy.
CREDIT: BOSTON UNIVERSITY CENTER FOR REMOTE SENSING
We are entering a new era in the Landsat Program, the
Socotra Island, in the western Indian Ocean, harbors high biodiversity and endemism and makes up the largest part of the Socotra archipelago UNESCO World Heritage site. Its climatic, pedological, and geomorphological characteristics, together with the long geological isolation and inaccessibility, led to the flourishing of unique tree diversity, with great cultural and ecological value. Lately, trees on Socotra are facing new threats linked to the abandonment of traditional management practices, climate change impacts, and growing human pressure. This study assesses the relative influence of environmental factors and human activity as drivers of tree cover and density, which can be used to support land management policies for the conservation of this key local resource. Tree cover and density were assessed on a total of 3600 plots of 0.5 ha each, laid on a regular grid covering the entire area of the island through Collect Earth, a free open source software tool that allows an augmented visual interpretation of high-resolution satellite images. A total of 770,000 trees, with an average of 2.14 trees/ha, were estimated on the island. The collected data was validated by ground surveys in 26 plots. The relative influence of selected predictors (seven environmental, two anthropic) on tree cover and density was analyzed through logistic and survival regression. Tree cover and density were found to be impacted positively by steeper slopes, higher rainfall, and marked precipitation seasonality and negatively by relatively warmer temperatures and a higher sand content in the soil. Distance of each plot from the nearest road and settlement was calculated and neither of these anthropic predictors emerged as significant, indicating that the limited number of trees present are not currently as affected by anthropic pressure, but, instead, their presence is mostly limited by the harsh climatic and pedological factors. However, as human population and development increase, periods of drought rise, and extreme and random climatic events intensify, these additional stresses on the environment could negatively impact the availability of natural resources in the terrestrial environment. Lastly, potential recommendations to the existing conservation policies and Socotra Conservation Zoning Plan are discussed based on the results.
Cyclones cause significant loss of life and damage to properties, ecosystems and marine structures and facilities. Cyclone modelling results are used for deriving robust design conditions for coastal and marine structures and facilities. The results are also used for emergency planning and decision-making to estimate potential loss of life, damage to properties and marine facilities and to develop rescue and mitigation measures and plan clean-up operations. Royal HaskoningDHV (hereafter RHDHV) has set up regional tidal hydrodynamic and wave models covering the Arabian Sea to provide data to address the above issues. Over the course of a number of studies a total of 30 major cyclones have been identified in the Arabian Sea since 1945. Cyclone Chapala (28 October – 4 November 2015) was found to be the second strongest cyclone event since 1945 (the strongest being Cyclone Gonu in 2007). As less information is available on Cyclone Chapala, this paper has concentrated on this event to illustrate the use of numerical modelling to simulate waves and surge generated by cyclones. The MIKE21 model suite has been used to investigate this cyclone and sample results from the wave and surge modelling are presented in this paper for illustration purposes. The models could be used to simulate any cyclone generated within the Arabian Sea. The methodology described in this paper for modelling waves and surge in the Arabian Sea could also be applied to simulate this type of events at other sites around the world.
As we have entered an era of high resolution earth observation, the RS data are undergoing an explosive growth. The proliferation of data also give rise to the increasing complexity of RS data, like the diversity and higher dimensionality characteristic of the data. RS data are regarded as RS “Big Data”. Fortunately, we are witness the coming technological leapfrogging. In this paper, we give a brief overview on the Big Data and data-intensive problems, including the analysis of RS Big Data, Big Data challenges, current techniques and works for processing RS Big Data.
In Europe, the most susceptible areas to land degradation and desertification (LDD) are found in the Mediterranean region. The present study focuses on the island of Lesvos (Greece) and maps the environmental sensitivity of the island to LDD between the years 1990 and 2000. Sensitivity is estimated with a modification of the MEDALUS Environmentally Sensitive Area Index (ESAI) approach, employing 21 quantitative parameters divided in five main quality indices: climate, vegetation, soils, groundwater and socio-economic quality. Parameterisation of these indices is achieved via remote sensing and ancillary data in a GIS. Results show that ~85% of the island is fragile or critically sensitive in both epochs. Fragile areas are on the increase, covering an estimated 72% of the island in 1990 and 77% in 2000, while critically sensitive areas decrease from 214km2 to 113km2. By modifying the ESAI to include 10 additional parameters related to soil erosion, groundwater quality, demographic as well as grazing pressure, and by applying the modified ESAI in two -rather than one- periods this study was able to identify that, contrary to previous belief, critically sensitive areas are also found in the eastern side of the island mainly due to human-related factors. It is concluded that the proposed methodology is a useful tool for regional scale trend analyses of environmental sensitivity and the identification of LDD hot-spots in Mediterranean environments. This article is protected by copyright. All rights reserved.
This paper demonstrates a simulation approach for testing the sensitivity of linear and non-parametric trend analysis methods applied to remotely sensed vegetation index data for the detection of land degradation. The intensity, rate and timing of reductions in seasonally-summed NDVI are systematically varied on sample data to simulate land degradation, after which the trend analysis was applied and its sensitivity evaluated. The study was based on a widely-used, 1 km2 AVHRR data set for a test area in southern Africa. The trends were the most negative and significant when the degradation was introduced rapidly (over a period of 2–5 years) and in the middle of a 16-year time series. The seasonally-summed NDVI needs to be reduced by 30–40% before a significant negative linear slope or Kendall's correlation coefficient was apparent, given an underlying positive trend caused by rainfall. The seasonally-summed data were reordered to remove this underlying positive trend, before simulating degradation again. With no underlying positive trend present, degradation of 20% resulted in significant negative trends. Since areas widely agreed to be degraded show only 10–20% reductions compared to non-degraded areas, this raises doubts over the ability of trend analyses to detect degradation in a timely way in the presence of underling environmental trends. Residual Trends Analysis (RESTREND) was applied in an attempt to correct for variability and trends in rainfall. However, a simulated degradation intensity ≥ 20% caused the otherwise strong relationship between NDVI and rainfall to break down, making the RESTREND an unreliable indicator of land degradation. The results of such analyses will vary between different environments and need to be tested for sample areas across regions. Although the paper does not claim to solve the challenge of detecting land degradation amidst rainfall variability, it introduces a method of assessing the sensitivity of land degradation monitoring using remote sensing data.
Present study has produced first detailed land‐cover map of Socotra Island. A Landsat 7 ETM+ dataset was used as a main source of remotely sensed data. From numerous reference points (more than 250) coming from the ground data verification the set of training fields and the set of evaluation fields were digitised. As a classification method the supervised maximum likelihood classification without prior probabilities was used in combination with rule‐based post‐classification sorting, providing results of sufficient accuracy and subject resolution. Estimates of the area and degree of coverage of particular land‐cover classes within Socotra Island have brought excellent overview on state of island biotopes. Overall accuracy of the map achieved is more than 80%, 19 terrestrial land‐cover classes (including three types of Shrublands, three types of Woodlands, two types of Forests and Mangroves) have been distinguished. It consequently allows estimates of the current and potential occurrence of endemic plant populations, proposals of management and conservation plans and agro‐forestry planning.
The potential impact of climate change on Dracaena cinnabari, a spectacular relict of the Mio-Pliocene Laurasian subtropical forest in Socotra (Yemen), was analysed. Current distri-bution, abundance and vertical structure of D. cinnabari populations were assessed with 74 plots in nine remnant areas. A deterministic regression tree analysis model was used to examine environmental variables related to the current species distribution. Using this model, a current potential map and a predicted potential map for the $2080 climatic sce-nario were generated. D. cinnabari has an altitudinal range from 323 to 1483 m a.s.l., with a mean annual temperature of 19.8–28.6 °C and an annual precipitation of 207–569 mm. The current distribution and abundance of D. cinnabari is correlated to three factors: moisture index (i.e. the ratio between the annual precipitation and potential evapotranspiration), mean annual temperature and slope. According to this model, D. cinnabari occupies only 5% of its current potential habitat. This potential habitat is expected to be reduced with 45% by 2080 because of a predicted increased aridity. Only two out of the nine remnant areas should be considered as potential refugia. The boundaries of the strictly protected Skund Nature Sanctuary, where no (road) infrastructure is allowed, should be extended to include both areas. The construction of new roads leading towards these areas, thereby increasing permanent settlements and grazing pressure, should also be discouraged.
What are the main plant communities and vegetation zones on Socotra Island in relation to climatic, geological and topographic factors?
Socotra Island (Yemen).
A total of 318 relevés were sampled along an altitudinal gradient. Floristic and environmental (topographic, geological and climatic) data were collected and analysed using numerical classification and NDMS ordination; an analysis of the correlation between plant communities and environmental factors was also performed.
Eight types of woody vegetation, seven of shrubs, six of herbaceous and seven of halophytic vegetation were identified. Ordination revealed the importance of altitudinal and climatic gradients, as well as of geological substrata.
Four vegetation zones were identified. The first three are located in the arid region with altitude ranging from 0 to 1000 m and the fourth in the semi-arid region from 1000 to 1500 m a.s.l. Specifically they are: (1) an arid coastal plain mainly located on an alluvial substratum between 0 and 200 m, characterized by shrubland and grassland communities; (2) a transition zone from 200 to 400 m, between the alluvial substratum and the upper limestone area; (3) an arid limestone zone between 400 and 1000 m, interspersed with hills and plateaus; and (4) a semi-arid upper zone of the Haghier Mountains from 1000 to 1500 m on a granitic substratum.
Current threats to the planet's biodiversity are unprecedented, and they particularly imperil insular floras. In this investigation, we use the threat factors identified by the Millennium Ecosystem Assessment as the main drivers of biodiversity loss on islands to define and rank 13 current, continuing threats to the plant diversity of nine focal archipelagos where volcanic origin (or in the Seychelles a prolonged isolation after a continental origin) has produced a high degree of endemicity and fragility in the face of habitat alteration. We also conduct a global endangerment assessment based on the numbers of insular endemic plants in the endangered (EN) and critically endangered (CR) IUCN categories for 53 island groups with an estimated 9951 endemic plant species, providing a representative sample of the world's insular systems and their floristic richness. Our analyses indicate that isolation does not significantly influence endangerment, but plant endemics from very small islands are more often critically endangered. We estimate that between 3500 and 6800 of the estimated 70,000 insular endemic plant species worldwide might be highly threatened (CR+EN) and between ca. 2000 and 2800 of them in critical danger of extinction (CR). Based on these analyses, and on a worldwide literature review of the biological threat factors considered, we identify challenging questions for conservation research, asking (i) what are the most urgent priorities for the conservation of insular species and floras, and (ii) with the knowledge and assets available, how can we improve the impact of conservation science and practice on the preservation of island biodiversity? Our analysis indicates that the synergistic action of many threat factors can induce major ecological disturbances, leading to multiple extinctions. We review weaknesses and strengths in conservation research and management in the nine focal archipelagos, and highlight the urgent need for conservation scientists to share knowledge and expertise, identify and discuss common challenges, and formulate multi-disciplinary conservation objectives for insular plant endemics worldwide. To our knowledge, this is the most up-to-date and comprehensive survey yet to review the threat factors to native plants on oceanic islands and define priority research questions.
Assessing how environmental changes affect the distribution and dynamics of vegetation and animal populations is becoming increasingly important for terrestrial ecologists to enable better predictions of the effects of global warming, biodiversity reduction or habitat degradation. The ability to predict ecological responses has often been hampered by our rather limited understanding of trophic interactions. Indeed, it has proven difficult to discern direct and indirect effects of environmental change on animal populations owing to limited information about vegetation at large temporal and spatial scales. The rapidly increasing use of the Normalized Difference Vegetation Index (NDVI) in ecological studies has recently changed this situation. Here, we review the use of the NDVI in recent ecological studies and outline its possible key role in future research of environmental change in an ecosystem context.
Land-productivity dynamics: towards integrated assessment of land degradation at global scales
- E Ivits
- M Cherlet
Ivits E, Cherlet M (2013) Land-productivity dynamics: towards integrated assessment of land degradation at global scales. Joint
Research Centre (European Commission) Eur Union 10:59315
Ethnoflora of the Soqotra Archipelago
- A G Miller
- M Morris
- AG Miller
Miller AG, Morris M (2004) Ethnoflora of the Soqotra Archipelago.
Royal Botanic Garden, Edinburgh
Good practice guidance. SDG indicator 15.3. 1: proportion of land that is degraded over total land area
- N Sims
- C Green
- G Newnham
- J R England
- A Held
- M A Wulder
- M Herold
- S J Cox
- A R Huete
- L Kumar
- R A Vizcarra-Rossel
Sims N, Green C, Newnham G, England JR, Held A, Wulder MA,
Herold M, Cox SJ, Huete AR, Kumar L, Vizcarra-Rossel RA
(2017) Good practice guidance. SDG indicator 15.3. 1: proportion of land that is degraded over total land area. https ://www.
unccd.int/sites /defau lt/files /relev ant-links /2017-10/Good%20Pra
ctice %20Gui dance _SDG%20Ind icato r%2015.3.1_Versi on%20
1.0.pdf. Accessed 01 June 2020
Monitoring sensitivity to land degradation and desertification with the environmentally sensitive area index: the case of Lesvos Island
- E Symeonakis
- N Karathanasis
- S Koukouas
- G Panagopoulos
Symeonakis E, Karathanasis N, Koukouas S, Panagopoulos G (2016)
Monitoring sensitivity to land degradation and desertification
with the environmentally sensitive area index: the case of Lesvos
Island. Land Degrad Dev 27:1562-1573
New UN Decade on Ecosystem Restoration offers unparalleled opportunity for job creation, food security and addressing climate change
United Nations Environment Program (2019) New UN Decade on Ecosystem Restoration offers unparalleled opportunity for job creation, food security and addressing climate change. United Nations
Environment Program Press Release (01 March 2019);
Land in balance: the scientific conceptual framework for land degradation neutrality
- A L Cowie
- B J Orr
- V M Sanchez
- P Chasek
- N D Crossman
- A Erlewein
- G Louwagie
- M Maron
- G I Metternicht
- S Minelli
- A E Tengberg
- AL Cowie
Socotra-a natural history of the islands and their people
- C Cheung
- L Devantier
Soqotra archipelago: manual of traditional land-use practices
- M Morris