For assessing those patterns, one can use different methods, including ecological surveys, museum specimens, bibliographical records, and interviews [e. By unravelling such patterns and identifying range shifts, both contractions and expansions, it is possible to create accurate measures for conservation and management with the emphasis on the species-environment relationship [ 8 ].
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The diversity of factors affecting such distributional patterns have been categorized as either biotic—e. Animal and plant species have specific ecological requirements for their survival, and literature shows that the same factors impact different species at different levels, depending on temporal and spatial scales [e.
More specifically, several studies assert human presence, anthropogenic activities and urban infrastructures as some of the major causes of declines and contractions in wildlife populations due to their consequences for habitat fragmentation [ 20 , 21 , 22 ]. However, other authors present a more optimistic scenario, indicating that the conservation of wild species might be possible even where human presence is strong [ 23 , 24 ]. Human-mediated changes to land-cover are now ubiquitous across the globe and are drastically transforming landscapes and, consequently, altering species distributions [e.
Many studies have dealt with the impact of land use changes on species distribution in Mediterranean Europe [e.
There is now ample evidence that climate change may lead to range contractions in many organisms [ 37 ], either by reducing their optimal climatic envelope or due to the encroachment of the optimal climatic envelope of better-adapted invaders [ 38 ]. Under a scenario of anthropogenic-driven environmental changes, is essential to understand the processes beneath range shifts. Also, for expanding species, there may be a need to control for their potential impacts on the newly occupied territory [ 39 — 42 ]. Shifts in species ranges may be modelled according to stochastic processes but also according to deterministic mechanisms, such as those resulting from a response to changes in the environment [ 43 ].
Most studies in the literature focused on understanding rapid range expansions of exotic species during processes of invasion [ 44 , 45 , 46 ]. However, it is equally important to understand how and why a native species that was confined for a long time within a specific range, suddenly expands into new areas [e. This is the case of the Egyptian mongoose, Herpestes ichneumon Linnaeus, Though traditionally considered an exotic herpestid species in the Iberian Peninsula that was intentionally introduced by the invading Moors in the Middle Ages [ 49 , 50 , 51 ], recent genetic studies showed that this carnivore probably naturally settled in Iberia during the Late Pleistocene sea-level fluctuations [ 52 ].
In Africa, the species is widely distributed, albeit absent from the Sahara Desert, the wet forests of central and West Africa and the deserts of South Africa [ 53 , 54 ]. Whether of Pleistocene origin or a Moorish introduction, until recently the Egyptian mongoose was restricted to the south of the Tagus River, which probably acted as a natural barrier to the expansion into northern territories [ 56 ].
However, in the late s the Egyptian mongoose rapidly started expanded northwards beyond the Tagus River in Portugal [ 57 , 58 ], considerably extending the limits of its traditionally known range in this country [ 59 ]. Knowing that species ranges are limited by several factors, including vegetation cover and climatic aspects, and that those may change over time and space, we hypothesize that the sudden expansion of the Egyptian mongoose in Portugal is due to changes in either the i barrier effects of human infrastructure and topographic features; ii availability of suitable areas due to climate change; iii availability of suitable areas and expansion corridors due to changes in land use; or iv a combination of all of the above.
The Egyptian mongoose is known to favour the Mediterranean maquis and it is well-adapted to the climate of southern Portugal, which presents warmer temperatures in comparison to central and northern regions.
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Hence, we trust that any occurred alterations across the Portuguese range especially comprising vegetation cover and climatic aspects consequently affected the distribution of this species. The thorough analysis of the species expansion across the last three decades will largely contribute with new information related with the ecology of the Egyptian mongoose, by emphasizing the link between the changing environment and the occurrence of this species. Central and northern areas are characterised by a mountainous landscape with the highest altitude in the Iberian Central Mountain Chain at Serra da Estrela m.
Southern areas are characterised by flatlands and two major mountain chains: Serra de S. Mamede m and Serra de Monchique m.
Climate and vegetation vary with the biogeographic sub-region: the Atlantic Mid-European Sub-region in the northwest has a temperate and humid climate, wet summers and high levels of precipitation. The remaining and the majority of the territory is within the Western Mediterranean sub-region, with hot and dry summers and with high precipitation levels in other seasons, ranging from mm to mm.
The Mediterranean Sub-region is characterised by oaks, mastic Pistacia lentiscus , laurustinus Virbunum tinus , olive trees Olea europaea , carob trees Ceratonia siliqua and Phillyrea angustifolia [ 60 ]. However, in recent decades, intensive monocultures of eucalyptus Eucalyptus globulus and maritime pine Pinus pinaster have been planted throughout the country, significantly modifying forest composition [ 61 ]. The new presence-absence data was assessed by collected specimens from hunting activities. We also used additional information on the distribution of the mongoose available in the literature for confirmation purposes [ 56 , 59 , 62 ].
We then evaluated the expansion between the units where the mongoose was present in the previous period to the new units occupied by the mongoose in the following one. All variables were selected based on previous studies describing habitat requirements that influence mongoose presence and also on species having similarly-described habitat requirements [ 63 — 66 ].
We did not include prey availability as a variable in our study due to the generalist nature of the diet of this species, including small mammals, reptiles, amphibians, invertebrates and occasionally berries and other fruits, and its significant variation across its distribution range [ 67 , 68 ]. The Egyptian mongoose is considered an opportunistic species, as it usually preys on the most abundant items available, which also causes significant variation in its diet along the year [ 69 ]. Data from all the variables was obtained for each studied period.
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To reduce the risk of overfitting [ 70 ], an exploratory analysis was made by calculating the Spearman rank correlation to rank the variables in each studied temporal range. Variables showing a correlation above 0.
go here We then used hierarchical partitioning analysis HPA [ 71 , 72 ], also for each temporal range, to select uncorrelated potential explanatory variables from those described above. HPA separates up to twelve variables with high independent correlations with the dependent variable from variables that show a high pairwise correlation with the dependent variable but that is due to the joint action of other independent variables [ 72 ]. In identical cases like ours, some incongruities were found in terms of the ranking of the independent and co-dependent contributions of the variables depending on the order they enter the hierarchical analysis [ 74 ].
To correct these errors, Olea et al. We adopted this approach in our study and then ranked the variables according to the number of times they showed the highest independent contribution towards the variation of the response variable, i. Egyptian mongoose expansion across the three periods.
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Once we were able to select a subset of significant potential predictors, we then grouped the variables in different groups based on each one of the explanatory hypotheses. We considered different hypotheses aiming to evaluate the partitioning of the variance in relation to the response variable. We then used generalized linear models GLM with a binomial error distribution and logit link function to evaluate which hypothesis and set of variables best modelled the expansion of the Egyptian mongoose in each period. GLM is a rather flexible and robust technique, least susceptible to over-fitting than other methods e.
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Also, the GLM approach is able to deal with response variables that are not normally distributed [ 76 ]. Every model was run for these incremental areas against the variables associated with those increments. All analyses were done in R Version 3. The species expanded more intensively towards the central [both inland and along the coast and north-eastern territories Fig 1.
From the s to the s, the range of the Egyptian mongoose in Portugal increased from approximately km 2 to km 2 Fig 2. The steepest increase in the range of the species was documented in the last decade—between and —when its expansion continued further northeast, but also towards coastal areas with an increase of 55 km 2 relative to — Currently, the area occupied by the Egyptian mongoose in Portugal is ca.
Highly correlated variables were eliminated. WCrop was eliminated from the — and — ranges, as well as RV1Pond from — ranges. Table 2 shows the best models for each temporal range. The best models for the three temporal ranges include variables from the three hypotheses Global Model , with the majority of the variables highly correlated with the expansion of the Egyptian mongoose. There is a clear link between the physical environment and the distribution of a species, in which the influencing factors may assume a major or minor role depending on a geographic-time gradient [ 78 , 79 ].
This explains why the best models found for each temporal range included variables expressing different effects on mongoose expansion in the Portuguese territory. Variables explaining mongoose expansion were mutable over time, except MeanAltit. Our results suggest that the expansion of the Egyptian mongoose in the Portuguese territory is mostly associated with anthropogenically-driven changes in the landscape.
In Portugal, rural areas exhibit lower human densities compared to the coastal region, where urbanisation is more intense [ 80 ]. This dichotomy started to be even more evident in the s with migration from inland to the coast, resulting in significant rural depopulation [ 81 , 82 ]. We found a highly significant negative effect of urban areas on mongoose expansion across the two first studied temporal ranges Table 2. Similarly to the majority of wild carnivores [ 83 , 84 ], in the Iberian Peninsula the Egyptian mongoose avoids anthropic-disturbed areas with high human population densities [ 56 ].
In the first decade, the species was mainly present in the south-east where it was absent from intensely urbanized areas. In the second decade, the expansion was most notable towards the coast, and particularly the Lisbon district, but it was still absent from highly populated areas. We also found a negative correlation between road density and the expansion of the species during the — period. Road networks can negatively affect wildlife and ecosystems [ 85 — 88 ], limiting animal movements and causing a significant number of deaths by road- kills [ 89 — 93 ].
This underlines the negative impact the increasing construction of roads in the second period must have had on the Egyptian mongoose populations.