Suitable Land Cover Research Articles

Simulating impacts on UK air quality from net-zero forest planting scenarios

Abstract. The UK proposes additional bioenergy plantations and afforestation as part of measures to meet net-zero greenhouse gas emissions, but species and locations are not yet decided. Different tree species emit varying amounts of isoprene and monoterpene volatile organic compounds that are precursors to ozone and secondary organic aerosol (SOA) formation, the latter of which is a component of PM2.5. The forest canopy also acts as a depositional sink for air pollutants. All these processes are meteorologically influenced. We present here a first step in coupling information on tree species planting suitability and other planting constraints with data on UK-specific BVOC emission rates and tree canopy data to simulate, via the WRF-EMEP4UK high spatial-resolution atmospheric chemistry transport model, the impact on UK air quality of four potential scenarios. Our “maximum planting” scenarios are based on planting areas where yields are predicted to be ≥ 50 % of the maximum from the Ecological Site Classification decision support system (ESC DSS) for Eucalyptus gunnii, hybrid aspen (Populus tremula), Italian alder (Alnus cordata) and Sitka spruce (Picea sitchensis). The additional areas of forest in our scenarios are 2.0 to 2.7 times the current suggestions for new bioenergy and afforestation land cover in the UK. Our planting scenarios increase UK annual mean surface ozone concentrations by 1.0 ppb or 3 % relative to the baseline land cover for the highest BVOC-emitting species (e.g. E. gunnii). Increases in ozone reach 2 ppb in summer when BVOC emissions are greatest. In contrast, all the additional planting scenarios lead to reductions in UK annual mean PM2.5 – ranging from −0.2 µg m−3 (−3 %) for Sitka spruce to −0.5 µg m−3 (−7 %) for aspen – revealing that PM2.5 deposition to the additional forest canopy area more than offsets additional SOA formation. Relative decreases in annual mean PM2.5 are greater than the relative increases in annual mean ozone. Reductions in PM2.5 are least in summer, coinciding with the period of maximum monoterpene emissions. Although only a first step in evaluating the impact of increased forest plantation on UK air quality, our study demonstrates the need for locally relevant data on land cover suitability, emissions and meteorology in model simulations.

Future land use land cover changes in El-Fayoum governorate: a simulation study using satellite data and CA-Markov model

This study aims to monitor the changes in land use land cover (LULC) in El-Fayoum governorate over time (past, present, and future) to provide current information for stakeholders involved in land use planning. The study utilized Landsat satellite images and applied the Support Vector Machine algorithm using ArcGIS Pro 2.8.3 to classify the images into four major LULC classes: water, desert, built-up, and agricultural. To evaluate the accuracy of the LULC maps, the study used kappa statistical parameters, which ranged from 0.91 to 0.94, indicating acceptable results for further analysis. To predict spatio-temporal LULC changes, the study considered biophysical and socioeconomic factors such as distance to canals, distance to roads, distance to urban areas, a digital elevation model, and slope. A combination of Multi-Criteria Evaluation, a Fuzzy Membership Function, and the Analytic Hierarchy Process were employed to develop a land cover suitability map. The Hybrid CA-Markov model of the IDRISI-TerrSet software was used to simulate LULC changes, and the accuracy of the simulation was validated using 2020 imagery data. The values gained from the kappa indices for agreement (standard) = 0.9006, kappa for lack of information (no) = 0.916, and kappa for location at grid cell level (location) = 0.9572 demonstrate that the results of the simulation of the LULC changes were deemed satisfactory. The future scenarios modeled in LULC indicate a significant change in the LULC classes over time, specifically for 2030. The change rates of agriculture, desert, built-up, and water areas in El-Fayoum in 2030 compared to 2020 are estimated to be 9.68%, − 17.58%, 133.62%, and 6.06%, respectively. These findings establish both past and future LULC trends and provide crucial data useful for planning and sustainable land use management.

Impact of Land Use Change on Land Capability in Katingan Regency, Central Kalimantan, Indonesia

The imbalance between land use and land capability can cause environmental problems in Katingan Regency. This study aims to analyze changes in land use change for the 2015-2021 period, land capability, land cover suitability with land capability in Katingan Regency. This research uses the method of overlaying the 2015 and 2021 land cover maps, analyzing land capability with variables of erosion maps, flood maps, and aridity maps, and analyzing land suitability by overlapping land use maps and land capability maps. The results show that land use change is 67.864 ha with map accuracy KA = 90.6% and OA 81.1%, while the concentration of land use change in Malan Island District with an LQ value of 2.5. Land capability is divided into three with the limiting factors of erosion, flooding, and slope class, namely: class II, III, IV, VI, and VII which are designated as productive paddy fields, dry land agriculture, and agriculture mixed with shrubs. Land use change has an impact on land capability, namely the increase of unsuitable land by 23.050 ha. This research can provide important information for taking policies and strategies for optimizing land use at the site level in Katingan Regency in the future.

A GIS framework for the application of the land degradation neutrality concept in Mediterranean landscapes

Given the absence of soil loss indicators within the Land Degradation Neutrality (LDN) framework, this study integrates land cover suitability, soil erosion and sediment transport as complementary Mediterranean-tailored indicators. The 309 km2 Lebanese Nahr Ibrahim basin was chosen for this purpose. Land cover suitability was determined by combining land capability-land cover maps, while soil erosion and sediment transport were assessed using the CORINE and SWAT models, respectively. Under current conditions, the following was found: a 34.84% land cover suitability; 4% low, 39.55% moderate and 56.45% high soil erosion risks zones, and 2.85% low, 26% moderate and 68.15% high sediment yields zones. Through the LDN response strategy based land use plan, land cover suitability increased by 26.54%, while soil erosion risks changed by: +3.1% low, +10.85% moderate and −18% high risk zones. For sediment transport, changes were: 0% low, +10.85% moderate and −18% high risk zones, hence the multi-effectiveness of LDN.

Developing a national indicator of functional connectivity

Habitat loss is a significant driver of biodiversity loss, causing fragmentation into small, isolated patches of suitable land cover. This reduces the permeability of landscapes to the movement of individuals and reduces the likelihood of metapopulation persistence. Quantifying functional connectivity, the ability of a focal species to move between resource patches, is therefore essential for conservation management. There is substantial evidence supporting a technique based on ‘population synchrony’- the degree of correlation in time-series of annual population growth rates between different long-term monitoring sites, to provide a measure of functional connectivity. However, synchronised population dynamics are not only driven by the movement of individuals between sites, but also shared environmental conditions which must be accounted for. Here, we use species survey data from over four decades to investigate average levels and temporal trends in population synchrony for 58 British bird and butterfly species. We first show that population synchrony is significantly associated with synchrony in some seasonal climatic variables. Once we accounted for spatiotemporal climatic patterns, we found that synchrony in butterflies declined over time by 71% between 1985 and 2000 but increased by 64% in recent years. Synchrony in birds showed some decline between 1999 and 2005, after which there appears to being recovery, however most species (74%) show no significant overall change in synchrony. Our proposed indicator provides a ‘species-eye-view’ of functional connectivity using widely available abundance data. Developing such indicators of functional connectivity, which can be updated annually, is crucial to improve the effectiveness of land management strategies for conservation under increasing environmental change.

A Comparative Study of Support Vector Machine and Maximum Likelihood Classification to Extract Land Cover of Lahore District, Punjab, Pakistan

The advent of technological era, the scientists and researchers develop machine learning classification techniques to classify land cover accurately. Researches prove that these classification techniques perform better than previous traditional techniques. In this research main objective is to identify suitable land cover classification method to extract land cover information of Lahore district. Two supervised classification techniques i.e., Maximum Likelihood Classifier (MLC) (based on neighbourhood function) and Support Vector Machine (SVM) (based on optimal hyper-plane function) are compared by using Sentinel-2 data. For this optimization, four land cover classes have been selected. Field based training samples have been collected and prepared through a survey of the study area at four spatial levels. Accuracy for each of the classifier has been assessed using error matrix and kappa statistics. Results show that SVM performs better than MLC. Overall accuracies of SVM and MLC are 95.20% and 88.80% whereas their kappa co-efficient are 0.93 and 0.84 respectively.

Using Ecological Niche Models for Population and Range Estimates of a Threatened Snake Species (Crotalus oreganus) in Canada

Modelling the distribution and abundance of species at risk is extremely important for their conservation and management. We used ecological niche models (ENMs) to predict the occurrence of western rattlesnakes (Crotalus oreganus) in British Columbia (BC), Canada. We applied this to existing population estimates to support a threshold of occurrence for management and conservation. We also identified predictors influencing rattlesnake distribution and abundance in this region. Using a Geographic Information Systems platform, we incorporated ENMs, capture–mark–recapture (CMR) and radio-telemetry results, province-wide observations, Landsat imagery and provincial databases for agricultural land use to produce quantitative, spatially explicit, population estimates across BC. Using available western rattlesnake habitat estimated at 183.9 km2 and averaging estimates calculated from densities in three study populations, we generated a mean adult population size of 9722 (±SD 3009; 0.8 relative index of occurrence [RIO] threshold). Only a small area (21.6 km2) of suitable land cover was located within protected areas, potentially protecting an estimated 1144 (±354) adults. Most suitable land cover was within 500 m of roads (170.6 km2), representing potential habitat being used by an estimated 9017 (±2791) adults. At the threshold RIO value chosen (0.8), only a very small area of farmland provided suitable land cover. Our results highlight the possibility of high mortality rates for western rattlesnakes near roads and the fact that protected areas do not provide sufficient coverage to conserve the population. Given that this species has relatively low mobility and high site fidelity to home ranges, our population estimate for BC provides a useful reference for the northern part of the species’ range. It also fulfills a need to estimate population size within political jurisdictions where conservation management decisions are made, as well as presenting a method that can be applied to other parts of the range, including the southern United States. Our study provides an important benchmark for future monitoring of western rattlesnakes in BC using a repeatable and transparent approach. Similar applications can be extrapolated and applied for other threatened species to identify and quantify population distributions and threats, further supporting conservation prioritization tools to be used to maximize the effectiveness of conservation strategies under financial constraints.

Phenology based classification index method for land cover mapping from hyperspectral imagery

Remote sensing imagery classification contributes assistance to real-time applications for comfort and secures the society. The imagery of satellites entirely depends on the sensor type in satellites. Phenology reflection varies based on the land cover type, which absorbs external energy. Multispectral high-resolution imagery has the maximum details about the earth’s surface. This research work defines phenology based classification approach, which can produce precise high precision land cover classification. The need to develop a phenology based methodology reflects on the vegetation development classification and produces a much more suitable land cover map based on reflection values. The RGB channel values of the image do not influence this technique of reflection phenology classification. Phenology Based Classification Index (PBCI) supervised method is used to classify the high-resolution multispectral imagery with improved phenology classification methods. PBCI works on the passive sensor satellite images, without clouds and shadow in classification. The proposed method has compared with existing phenology classification methods using more than seven quality metrics.

Potential enlargement of the European roller’ breeding range in the Carpathian Basin

The decline of farmland and grassland biodiversity is one the major conservation concerns nowadays. The European roller is a secondary cavity nester species typically inhabiting grasslands and farmlands. It has suffered large declines both in size and range of the population since the 1960s, but this negative trend has been reversed in several countries by applying direct conservation actions. As part of this study we aimed to evaluate the current habitat suitability of the historical breeding area of the species within Hungary, to promote the recolonization and the enlargement of the breeding range in the Carpathian Basin, and to evaluate the potential significance of the Natura 2000 network in this process. We applied species distribution modelling (SDM) based on nest-box occupancy data to map potential areas for nest-box supplementation. Grasslands, broad-leaved forests and agricultural sites with significant areas of natural vegetation were found to be the most important predictors. The majority (71%) of the predicted area has no occupied nest-boxes. A significantly larger proportion of grid cells with archive data still preserve suitable land cover composition for rollers, than cells where former breeding was not confirmed, and only a small proportion of former breeding area has become completely unsuitable for the species. Our results indicate large overlaps between the Natura 2000 network and the predicted area, of which 28.3% overlaps with Special Protection Area (SPA) sites and 23.8% with Special Area of Conservation (SAC/SCI) sites. Our study highlights the importance of promoting the recolonization of the European roller in the Transdanubian region of Hungary and provides a useful tool for direct conservation planning for the species. Our results also suggest that a coordinated network of protected areas such as Natura 2000 can potentially serve as core areas in the recolonization processes.

Future Lyme disease risk in the south-eastern United States based on projected land cover.

Lyme disease is the most significant vector-borne disease in the United States, and its southward advance over several decades has been quantified. Previous research has examined the potential role of climate change on the disease's expansion, but no studies have considered the role of future land cover upon its distribution. This research examines Lyme disease risk in the south-eastern U.S. based on projected land cover developed under four Intergovernmental Panel on Climate Change Scenarios: A1B, A2, B1, and B2. Land cover types and edge indices significantly associated with Lyme disease in Virginia were incorporated into a spatial Poisson regression model to quantify potential land cover suitability for Lyme disease in the south-eastern U.S. under each scenario. Our results indicate an intensification of potential land cover suitability for Lyme disease under the A scenarios and a decrease of potential land cover suitability under the B scenarios. The decrease under the B scenarios is a critical result, indicating that Lyme disease risk can be decreased by making different land cover choices. Additionally, health officials can focus efforts in projected high incidence areas.

Distance to international border shapes the distribution pattern of the growing Little BustardTetrax tetraxwinter population in Northern Iran

SummaryThe Little BustardTetrax tetraxis a Near Threatened grassland bird that is fully migratory within its eastern population, wintering in large numbers across the south Caucasus and northern parts of Iran. The species’ habitat selection has been comprehensively studied in its western European range, but very limited information is available for its eastern population. Surveys carried out between 2010 and 2015 show a considerable population increase and probable range expansion in the region. We modelled the suitability of potential winter habitat for the species and found that distance to country border, land cover and altitude were the most important variables in predicting habitat suitability. There is still considerable hunting pressure in Iran and distance to border is likely to be related to strict hunting prohibition along the border belt imposed for military purposes. This represents an opportunity for the conservation of the species, where management efforts should aim at ensuring the maintenance of suitable land cover.

GIS-based surface irrigation suitability analysis: a case study of Walga sub-basin, Oromia Region, Ethiopia

Irrigation development could improve agricultural productivity and enhance socioeconomic development of the community. Though agriculture is the leading economic development sector of Ethiopia, most of the country's cultivated land is under rain-fed farming. Assessment of GIS-based irrigation suitability analysis with regard to the prevailing slope, soil, land use/land cover and surface water resources has been carried out. Geo-referenced irrigation suitability map of the watershed area for the intended irrigation method was produced using ArcGIS weighted overlay model. Results of the suitability analysis revealed that about 45.72% (135,519.2 ha) of the watershed area is categorised in the range of highly suitable to marginally suitable for surface irrigation development as a result of combined effect of slope, soil and land use land cover suitability. Potentially suitable sites for surface irrigation development were evaluated for the selected dominant crops (maize, soybean and sesame) in the sub-watershed. Accordingly, Amanya, Rebu, Kulit, Nano, Walga and Darge river catchments have a total potentially irrigable area of 41.32% (122,488.2 ha). The analysis results from the present study might be providing a useful information for decision makers.

Climate Change and Coastal Floods: The Susceptibility of Coastal Areas of Nigeria

The pressures caused by anthropogenic activities such as housing development and road construction, oil and gas exploration, economic development and demographic changes, have partly fuelled several environmental challenges faced in the coastal areas of Nigeria. One of these challenges is the flood events which have recently caused damage of properties and loss of lives in the areas. This study examines and predicts the susceptibility of the coastal region of Nigeria to flood hazard in a changing climate using geo-spatial techniques. Topographic maps and Moderateresolution imaging spectroradiometer (MODIS) image of 2015 were processed, digitized, interpolated, classified and overlaid using the suitable algorithms. The MODIS imagery was classified into suitable land cover classes using the supervised maximum likelihood scheme. The 3D-analyst module was used to generate the Hydrological Digital Elevation Model (HDEM), Triangulated Irregular Network (TIN), and flood risk map of the study area. The flood risk map was classified into high, medium, low, and no risk zones. Results showed that, areas lying along the banks of Guinea coast are highly susceptible to flood hazards with the degree of susceptibility decreasing towards the North and eastern part of the area. These areas are classified as swamps (water-log) with low water retention which gives rise to high susceptibility of coastal flood hazards. The study discovered that the flood risk map can be used as an effective tool for precautionary measures, early warning systems, and consequently reduce the damages that could be caused by flood events.

De-extinction potential under climate change: Extensive mismatch between historic and future habitat suitability for three candidate birds

De-extinction is becoming potentially feasible for restoring extinct species in the wild, but research is required to determine the likelihood of success in light of contemporary and future environmental change. We assessed 1900–2100 change in suitable climate and land cover in the historic range of Carolina parakeet (Conuropsis carolinensis), ivory-billed woodpecker (Campephilus principalis) and passenger pigeon (Ectopistes migratorius), in North America. Parakeet and woodpecker historic range currently remains climatically-favourable, but intensified land use has broadly reduced habitat in contemporary landscapes. For passenger pigeon, more substantive loss in climate and land cover suitability exists in both the historic full range and primary breeding range. Long-term climate and land cover projections suggest that improved habitat suitability and increased potential future distribution outside historic ranges are likely for each de-extinction candidate. While such changes could improve probability of success for de-extinction programs, extensive mismatch between historic and future habitat suitability highlights the potential risks of reviving species that may colonize novel geographic space. To date, potential long-term negative effects of de-extinction programs to ecosystems outside historic ranges have not been elucidated, making this a priority concern for any serious proposal. To address whether benefits of reinstating extinct species to historic ecosystems outweigh risks to extant species outside their historic range will require extensive ecological, social and economic analyses that extend beyond that conducted to-date for this potentially transformational conservation tool.

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003–2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

Habitat loss, not fragmentation, drives occurrence patterns of Canada lynx at the southern range periphery.

Peripheral populations often experience more extreme environmental conditions than those in the centre of a species' range. Such extreme conditions include habitat loss, defined as a reduction in the amount of suitable habitat, as well as habitat fragmentation, which involves the breaking apart of habitat independent of habitat loss. The ‘threshold hypothesis’ predicts that organisms will be more affected by habitat fragmentation when the amount of habitat on the landscape is scarce (i.e., less than 30%) than when habitat is abundant, implying that habitat fragmentation may compound habitat loss through changes in patch size and configuration. Alternatively, the ‘flexibility hypothesis’ predicts that individuals may respond to increased habitat disturbance by altering their selection patterns and thereby reducing sensitivity to habitat loss and fragmentation. While the range of Canada lynx (Lynx canadensis) has contracted during recent decades, the relative importance of habitat loss and habitat fragmentation on this phenomenon is poorly understood. We used a habitat suitability model for lynx to identify suitable land cover in Ontario, and contrasted occupancy patterns across landscapes differing in cover, to test the ‘threshold hypothesis’ and ‘flexibility hypothesis’. When suitable land cover was widely available, lynx avoided areas with less than 30% habitat and were unaffected by habitat fragmentation. However, on landscapes with minimal suitable land cover, lynx occurrence was not related to either habitat loss or habitat fragmentation, indicating support for the ‘flexibility hypothesis’. We conclude that lynx are broadly affected by habitat loss, and not specifically by habitat fragmentation, although occurrence patterns are flexible and dependent on landscape condition. We suggest that lynx may alter their habitat selection patterns depending on local conditions, thereby reducing their sensitivity to anthropogenically-driven habitat alteration.

MODIS-derived snow-free ground reflectance statistics of selected Eurasian non-forested land cover types for the application of estimating fractional snow cover

This work aims at the improvement of the reflectance model-based methodology for mapping of fractional snow cover (FSC) in seasonally snow covered areas in the Northern Hemisphere. The investigations are focused to the determination and analyses of snow-free ground reflectance (ρground). The objective is to derive information on typical average snow-free ground reflectance for predominant non-forested land cover classes in Eurasia and to investigate the implications of their variations to the FSC estimation accuracy. The snow-free ground reflectances are derived from MODIS time series, using single band reflectances and their related indices. Our approach for the determination of ρground is based on the assumption that the behavior of ground reflectance in conditions occurring directly after the snow melt adequately represents the snow-free ground reflectance during snow ablation i.e. melting snow cover including snow-free patches. Additionally, the effects of the ρground variability to snow mapping accuracy for different land cover types are analyzed focusing to the SCAmod algorithm. The current operational implementations of SCAmod use a fixed value for snow-free ground reflectance at the visible wavelengths around 555nm (corresponding to Terra/MODIS band 4). The deviation between the true snow-free ground value and the fixed value causes error in FSC estimation and, thus, it is necessary to investigate the magnitude and variations of the true ρground for different land covers. Even so, our investigation for the target area of Europe, shows that the currently used fixed value of ρground (10.0%-units) in SCAmod seems to work adequately for land cover classes investigated here. For example, the obtained ρground mean and standard deviation 10.0±1.3%-units for the agricultural areas and steppe at 555nm seem to widely coincide with the fixed value. According to SCAmod, the error in FSC estimation caused by the deviation between the fixed and the land cover class-specific value of ρground for agricultural areas and steppe yields a systematic error close to zero and a random error ranging from 2.5 to 1.5%-units with the corresponding FSC range of 0–50%. However, in the case of wetlands (7.4±0.8%-units), the systematic error caused to FSC estimation using the fixed value compared to using the estimated class-specific value is as large as from 5 to 2.5%-units with the FSC range of 0–50%. For FSC retrievals larger than 50% the error caused by the variability in ρground is considerably smaller for all of the studied land cover classes.Our results show that the performance of SCAmod improves if land cover-specific ρground values are applied at least for wetlands. We also suggest that the global application of SCAmod would benefit from the generation of a ρground map for all land cover types by using the methods presented in this paper. This post-winter reflectance climatology map can be constructed by calculating and using the class-specific ρground statistics together with suitable land cover information.

A century of chasing the ice: delayed colonisation of ice‐free sites by ground beetles along glacier forelands in the Alps

Climate change is affecting species distribution, composition of biological communities, and species traits. Despite the growing body of knowledge on the reaction of species to climate change, the potentially delayed response of species is still severely understudied.In this paper we modelled the time needed by ground‐living invertebrates to effectively react to habitat modification induced by climate change in relation to dispersal abilities. We analyzed the occurrence pattern of alpine ground beetles (carabids) along areas recently freed by retreating glaciers in the central‐eastern Italian Alps, to test how the synergic effects of time since deglaciation and environmental factors may affect the colonisation process.Different times of response to climate change in ground beetles were found. Sites already hosting the land cover type suitable for our study taxon, but ice‐free for less than 100 yr, are mainly colonised by winged carabid beetles (which have high dispersal abilities and are mostly habitat generalists). No, or very few, wingless species (slow colonizers and ecologically specialized) occur within those sites. The overall pattern suggests that within a site, suitable land cover is established prior to colonization, due to a strong joint effect of time since deglaciation and land cover type.Long‐lasting habitat development at the fine scale is likely to result in a lack of specific resources (e.g. food items, or microhabitat), which is likely to contribute to delayed colonisation, which potentially could be tied also to dispersal abilities. Whatever the reason, the existence of a time‐lag often equal to or greater than 100 yr in species colonisation implies caution in predicting species’ occurrence shifts following climate change.

A comparison of scenarios for rural development planning and conservation in the Democratic Republic of the Congo

Including a diverse set of stakeholders in collaborative land use planning processes is facilitated by data and maps that communicate and inform an array of possible planning options and potential scenarios of future land use change. In northern Democratic Republic of the Congo (DRC), the African Wildlife Foundation (AWF) has engaged stakeholders and the DRC Government to lead a participatory zoning process in the Maringa–Lopori–Wamba (MLW) Landscape. To assist landscape scale macro-zoning efforts, we employed a spatial allocation decision support tool called Marxan to develop a set of three scenarios of potential human and agricultural expansion for 2050. The results offer guidance to stakeholders and assist decision-makers in determining the most suitable land for inclusion in a proposed Rural Development Zone (RDZ), designed to accommodate the expansion of agricultural activities and subsequent deforestation while considering conservation priority areas. We used data describing current patterns of human activity, including historical primary forest loss, land cover suitability for agricultural activity, and presence of important wildlife connectivity zones and protected areas to identify locations where future agricultural expansion might be encouraged. We found that future agricultural demands can be met by expansion around historically intensive agricultural areas in the eastern portion of MLW without significantly compromising conservation priority areas. Wildlife connectivity zones are most vulnerable to future agricultural expansion because of their proximity to current agricultural activity. Our results demonstrate the need to prioritize conservation action in these areas and illustrate how competing needs might be balanced in planning for both agricultural expansion and terrestrial biological conservation in this landscape.

Using Geographical Information System (GIS) and Satellite Remote Sensing for Understanding the Impacts of Land Cover on Apiculture over Time

The development of apiculture is strongly related to the suitable land cover, mainly the availability of honey plants. The land cover is not stable over time due to the human activities. The honey yield per honey bee colony has been reduced greatly in El-Behera Governorate, Egypt over time. The decline in the cultivated areas is considered to be the main cause for the low honey yield. In this research, the land cover changes were investigated during a long period of time from 1970s till 2000s to understand the possible roles of the land cover changes on apiculture and low honey yield. The GIS and Landsat satellite images in combination with Google Earth historical images were used for land cover change analysis. The obtained results showed a relative increase in the cultivated areas over time with approximately the presence of the same plant types. Therefore, the low honey production can not be explained by the decline in the cultivated areas.