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Remote sensing (RS) data and geographic information system (GIS) techniques were used to monitor the changes in the Oasis agroecosystem of the pre-Saharan province of Errachidia, southeastern Morocco. The land use and land cover (LULC) change of the agroecosystem of this province was processed using Landsat time series with 5-year intervals of the last thirty years. The normalized difference vegetation index (NDVI) and the maximum likelihood classification (MLC) were categorized into five classes, including water bodies, cultivated land, bare land, built-up, and desertified land. The overall accuracy of the MLC maps was estimated to be higher than 90%. The finding showed a degradation trend represented by an increase in desertified lands, which tripled in the ten last years, passing from 20.62% in 2011 to 58.49% in 2022. The findings also depicted a decreasing trend in the cultivated area in this period passing from 174.2 km2 in 1991 to 82.2 km2 in 2022. Using NDWI, Landsat images from 1991 to 2021 depicted a strong association between the water reserve in Hassan Eddakhil dam in the upstream area and the LULC changes. The oases from the dam (upstream) to Er-Rissani (downstream) recorded high rates of decline with an increasing trend of desertification due to drought and overuse mainly of groundwater. The outputs of this research effort constitute a significant source of information that may be used to support further research and decision-makers to manage arid ecosystems and achieve the sustainable development goals (SDGs), precisely the SDGs 15 (Life on land).

BackgroundPhlebotomus (Paraphlebotomus) sergenti is a widespread proven vector of Leishmania pathogens causing anthroponotic cutaneous leishmaniasis (ACL), due to L. tropica, in the old world. The activity of P. (Par.) sergenti is seasonal and sensitive to general variations in climate. Phenological data sets can thus provide a baseline for continuing investigations on P. (Par.) sergenti population dynamics that may impact future leishmaniasis transmission and control scenarios.Methods/principal findingA systematic review of the seasonality of P. (Par.) sergenti was undertaken globally. Six hundred eight scientific papers were identified, and data were extracted from 35 ones, with informative data on sand fly seasonal dynamics on trapping performed from 1992 to December 2021 on 63 sites from 12 countries. Morocco, Saudi Arabia, Iraq, Iran, Pakistan, Palestine, Turkey, Spain, Portugal, Italy, Cyprus, and Georgia. The data extracted from the literature survey were further normalized. Our analysis recorded that the highest P.(Par.) sergenti activity occurs during the hot and dry seasons, primarily in July and August, whatever the location studied. We noticed a relationship between the latitude of sites and sand fly presence (from early April to June) and the type of density trend, varying from a single peak to multiple peaks. On a geographical scale, P. (Par.) sergenti concentrates between 32-37° in latitude in a large interval following the longitude and the highest number of sites with high P. (Par.) sergenti activity is located at the latitude 32°. We also quoted a similar seasonal dynamic and geographic distribution with Phlebotomus (Phlebotomus) papatasi, a proven vector of L. major that causes cutaneous infection. No apparent risk for ACL occurred from December to March, at least in the years and geographic areas considered in this survey. Altogether, knowing that high P. (Par.) sergenti activity would be linked with an increased risk of leishmaniasis transmission, and our study provides information that can be used for control programs on ACL transmission.ConclusionsDespite variations, we found a relatively homogeneous pattern of P. (Par.) sergenti potential behavior in sites whose data are published. A higher risk for L. tropica transmission was identified in the June-October period. Still, such risk was not equally distributed throughout the area since density waves of adults occurred earlier and were more frequent in some territories, like Saudi Arabia.

The study investigates the land use and land cover (LULC) in Errachidia province (Pre-Saharan of Morocco) in the period 2005–2020. To this end, remote sensing (RS) tools such as LULC, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), the Enhanced Vegetation Index (EVI), Gravity Recovery and Climate Experiment (GRACE) satellite data, and precipitations were processed and combined. The monitoring of LULC over this period reveals different changes in this area. Generally, for water bodies, two trends can be observed, an increasing trend since 2006 and a decreasing trend from 2011 to the present. However, an increasing trend was recorded for the urban-and-built-up-lands and the grasslands categories. NDVI, NDWI, and EVI showed three major peaks recorded in the same periods (in 2007, 2009, and 2015). In terms of water storage, three phases were found. The first depicted the lowest groundwater quantities with a decreasing trend, which corresponds to a period of drought and/or human pressure. The second phase, the most important that recorded the greatest storage of water while the third phase corresponds to low storage with a decreasing trend. LULC of croplands reveals a slightly increasing trend from 2012 to 2020, which shows an orientation to an extension of crops mainly of date palm encouraged by government programs. A strong correlation between the seasonal NDVI and water storage using GRACE-Data for the period was found. In the end, recommendations on the adaptation to CC were proposed. The findings demonstrate that RS techniques are useful tools to detect hydrological droughts, observe, and conserve land resources. In arid areas such as Errachidia, the solution lies in rationalizing the use of water resources protecting them from uncontrolled anthropogenic events, which may alleviate the pressure. To support local sustainable development, environmental scientists and decision-makers may use the outputs of this study.

Leishmanioses are of public health concern in Morocco, mainly the Zoonotic Cutaneous Leishmaniasis (ZCL) endemic in the Moroccan pre-Saharian area. Transmission of this disease depends on eco-epidemiological and socio-economic conditions. Therefore, a multivariable approach is required to delineate the risk and intensity of transmission. This will help outline main disease risk factors and understand interactions between all underlying factors acting on disease transmission at a local and regional scale. In this context, we propose a new conceptual model, the Biophysical-Drivers-Response-Zoonotic Cutaneous Leishmaniasis (BDRZCL), adapted to the Pre-Saharian area. The proposed model highlights how the physical and human drivers affect the environment and human health. The incidence of ZCL is linked to human activity and biophysical changes or by their interactions. The human response added to risk drivers are the main components that influence the biophysical part. This model improves our understanding of the cause-effect interactions and helps decision-makers and stakeholders react appropriately.

Rodents play a significant role in the balance of a terrestrial ecosystem; they are considered prey for many predators like owls and snakes. However, they present a high risk to agriculture (damaging crops) and health. These rodents are the main reservoirs of some vector-borne diseases like leishmaniasis. Meriones shawi (MS) and Psammomys obesus (PO) are the primary Zoonotic cutaneous leishmaniasis (ZCL) reservoirs in the Middle East and North Africa (MENA). A review on the MS and PO at the MENA scale was explored. A database of about 1500 papers was used. 38 sites were investigated as foci for MS and 36 sites for PO, and 83 sites of Phlebotomus papatasi (Pp) in the studied region. An updated map at the regional scale and the trend of the reservoir distribution was carried out using a performing proper density analysis. In this paper, climatic conditions and habitat characteristics of these two reservoirs were reviewed. The association of rodent density with some climatic variables is another aspect explored in a case study from Tunisia in the period 2009–2015 using Pearson correlation. Lastly, the protection and control measures of the reservoir were analyzed. The high concentration of the MS, PO, and Pp can be used as an indicator to identify the high-risk area of leishmaniasis infection.

Background: In North African countries, zoonotic cutaneous leishmaniasis (ZCL) is a seasonal disease linked to Phlebotomus papatasi, Scopoli, 1786, the primary proven vector of L. major dynamics. Even if the disease is of public health importance, studies of P. papatasi seasonal dynamics are often local and dispersed in space and time. Therefore, a detailed picture of the biology and behavior of the vector linked with climatic factors and the framework of ZCL outbreaks is still lacking at the North African countries’ level. Our study aims to fill this gap via a systematic review and meta-analysis of the seasonal incidence of ZCL and the activity of P. papatasi in North African countries. We address the relationship between the seasonal number of declared ZCL cases, the seasonal dynamic of P. papatasi, and climatic variables at the North African region scale. Methods: We selected 585 publications, dissertations, and archives data published from 1990 to July 2022. The monthly incidence data of ZCL were extracted from 15 documents and those on the seasonal dynamic of P. papatasi from 11 publications from four North African countries. Results: Our analysis disclosed that for most studied sites, the highest ZCL incidence is recorded from October to February (the hibernal season of the vector), while the P. papatasi density peaks primarily during the hot season of June to September. Overall, at the North African region scale, two to four months laps are present before the apparition of the scars reminiscent of infection by L. major. Conclusions: Such analysis is of interest to regional decision-makers for planning control of ZCL in North African countries. They can also be a rationale on which future field studies combining ZCL disease incidence, vector activity, and climatic data can be built.