Introduction

Species invasions can become a distinctive feature of newly created cultural landscapes, as they change from a mostly wild to mostly anthropogenic one (Sadori et al. 2010). Most of the arrivals of exotic species into their new ranges appear to result from intentional or accidental exchanges between distant regions via different pathways, depending on sociocultural factors (Hulme et al. 2008; Hulme 2009). Once introduced, their establishment and spread result from the complex interaction between new habitat and species characteristics. Successful invasions that spread into natural systems are the result of the cultural landscape construction that includes the biocultural dimension: a physically, culturally, and historically determined environment. Humans have been transporting plants species among regions for millennia. These interchanges were extremely important among Asia, Europe and Africa along the silk route, as well as between Europe and America after Columbus, and they have had unprecedented magnitude and complexity across the globe in recent decades (Hulme 2009). Purpose driven exchanges include, for example, species with agricultural, medicinal or ornamental value. However, some of these species are able to spread into natural and seminatural ecosystems affecting ecological functions and biodiversity (Vitousek et al. 1996; Bellard et al. 2013) as an unplanned, and frequently undesirable, side effect of the cultural landscape construction.

Cities are a particularly important feature of the cultural landscapes, regulating the multiple connections and flows between people and ecosystems that strongly affect species invasion. Cities act as attraction centers for the introduction of desirable and undesirable species and then as sources of propagules for the peri-urban environment (Alston and Richardson 2006; Botham et al. 2009; Wang et al. 2011a, b). For example, gardening, urban forestry or horticulture regulate the location of seed sources, increase the propagule pressure and reduce the probability of invasion failure by temporally protecting potential invaders from unsuitable environmental conditions until they adapt to local conditions (Mack 2000; Pyšek and Richardson 2010; Hulme 2011; Pergl et al. 2016). Recent studies found that human population and wealth (Pyšek et al. 2010; Decker et al. 2012), as well as the historical legacy (Essl et al. 2011) are strong predictors of a wide range of invasive species distribution. Therefore, it is expected that cities and anthropogenic peri-urban landscapes play a key role in the introduction and spread of invasive species.

The capacity of a particular species to colonize areas depends on the interaction among propagule availability, dispersal capacity, population growth potential, and landscape heterogeneity (Vilá et al. 2008; O’Reilly-Nugent et al. 2016). In this sense, biological (e.g., intrinsic species attributes, life history traits) (Grotkopp and Rejmánek 2007; Leishman et al. 2007; Peñuelas et al. 2010) and environmental factors (climate, topography, hydrology) are important drivers that interact with human activities and determine the geographical extent of plant invaders in their novel distribution range (Rejmánek and Richardson 1996; Thuiller et al. 2006). For example, human disturbances can regulate resource availability (e.g., light, soil nutrients), affecting ecosystem invasibility and often enhancing the competitive ability of invasive species (Standish et al. 2008; Karalius and Alpert 2010). Furthermore, changes in landscape configuration (e.g., replacing forests by grasslands, increased of roads, etc.) can affect dispersal barriers and corridors and thus, the spread pattern (Miller et al. 2015). This results in higher invasion rates in fragmented landscapes than in continuous and unconnected areas (Vilá and Ibañez 2011). When the cultural landscape construction results in strongly modified environmental conditions, they can overwhelm the influence of climate and natural physical environment (e.g., soils, hydrology or topography) (Chiron et al. 2009; Sharma et al. 2010; Fuentes et al. 2015). Cities and peri-urban areas are characterized by distinctively intensive features of the cultural landscape. In addition to present-day landscape configuration, invasions are often associated with the historical changes in land-use (Mosher et al. 2009; Vilá and Ibañez 2011). Although biophysical factors and their interaction with city dynamic can be very relevant to understand biological invasion processes as side effects of cultural landscape development, they have been largely explored separately.

The cultural landscape construction in the subtropical humid forest of northwest Argentina, Yungas ecoregion, experienced a major change with the Spanish arrival in the region in the sixteenth century. As a result of the territory reconfiguration implemented during colonial times, the main productive activities and population shifted from the highlands in the pre-Hispanic and early Hispanic period, to the forested humid flatlands of the foothills. Much of the lowland and lower montane forests with flat topography were deforested for agriculture and grazing, and the main urban centers were located nearby. These areas include the three province capital cities of the region: San Miguel de Tucumán, Salta, and San Salvador de Jujuy, with approximately 900,000, 600,000 and 300,000 inhabitants, respectively (INDEC 2010). During the past decades, several montane areas near these urban centers experienced abandonment or disintensification of agriculture and livestock grazing, which resulted in the expansion of secondary forests (Grau et al. 2008; Gutiérrez-Angonese and Grau 2014). Parts of these new forests are dominated by exotic tree species. A large proportion of them are originally from SW Asia, including Ligustrum lucidum W. T. Aiton (Oleaceae), the most aggressive and fast growing tree species in this area (Grau and Aragón 2000; Aragón and Morales 2003; Easdale et al. 2007). L. lucidum was possibly introduced primarily for urban shade, gardening, living fences and windbreaks. One of the first records in Argentina dates to c.1900 (Montti et al. 2016). The extent of L. lucidum forests and the drivers of the invasion are still not well documented. Here, we follow a multiscale approach to explore the dynamics of this invasion into cultural landscapes in NW Argentina, with particular emphasis on the role of cities and distant connections between native and novel ranges of distribution of this species. Specifically in this study, we pursued the following objectives: (1) to identify the potential area of invasion by L. lucidum in the Yungas ecoregion of Argentina using ecological niche distribution models, (2) to map, quantify and describe current invaded area in this ecoregion by using satellite images in three peri-urban focal zones, and (3) to quantitatively describe the spatial and temporal patterns of L. lucidum forest invasion at local scale, linking environmental and cultural landscape features in the largest peri-urban sector of the region: San Miguel de Tucumán and Sierra de San Javier (SSJ).

Methodology

Studied species

Ligustrum lucidum or Chinese glossy privet is an evergreen tree native of the south of the Yangtze River in China, where it grows in different climates and soil types between 0 and 2900 m.a.s.l., in full sunlight, as well as in shaded understory (Chang et al. 1996). L. lucidum has been extensively cultivated for different purposes (e.g., traditional medicine, culturing wax-insects to obtain white wax, furniture) for a long time in China. Because of its particular functional traits (e.g., fast growth rate, tolerance to air pollution), it is regarded as a great landscaping plant and it is used extensively as an ornamental in streets and gardens around the world (Guilhermetti et al. 2013). But it is also considered a successful global invader outside its native range (Panetta 2000; Aslan et al. 2012; Montti et al. 2016).

Study area

Our study focuses on Yungas ecoregion, the humid native forests of northwestern Argentina (−22.25° S to −27.95° S, −64.22° to −65.65° W; Fig. 1a). The climate is subtropical with a monsoon regime of precipitation (dry winters, rainy summers) (Brown et al. 2001). Temperature and precipitation are controlled by topography; the average annual temperature is high in the eastern piedmont (20 °C) and decreases with elevation. Precipitation exceeds 1100 mm per year (Bianchi 1981), 78% concentrated in the months of November to March. Additional supply of water, particularly during the dry season, comes from fog or horizontal rain (Hunzinger 1997). The native humid forest that L. lucidum replaces has a high proportion of evergreen and semi-deciduous tree species, with Ocotea porphyria, Blepharocalyx salicifolius, Pisonia ambigua and Cedrela lilloi, as dominant tree species (Brown et al. 2001; Grau et al. 2010; Blundo et al. 2012). For the purpose of this study, three spatial scales of analysis were considered: (1) regional: including all Yungas distribution in Argentina, c. 5.2 million ha, (2) sub-regional: three pre-selected focal zones or sectors where invasion was notorious covering 408,500 ha approx., and (3) local: that include the most affected sector by the invasion, near to 120,000 ha, the peri-urban region of San Miguel de Tucumán (Fig. 1a).

Fig. 1
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a Location of the study area in Argentina at three different scales, b Original Yungas ecorregion (native forest) and map of potential L. lucidum distribution in NW Argentina

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Potential distribution of Ligustrum lucidum at regional scale

We generated a potential distribution map at regional scale based on recently observed presence records, climatic variables and maximum entropy algorithm implemented in Maxent 3.3.1 (Phillips et al. 2006). This map represents the distribution of suitable climatic conditions for L. lucidum in our study area. Maxent has proven to produce more reliable results than other comparable methods such as Bioclim, Domain or Garp (Wisz et al. 2008). This reliability has been confirmed by its high capacity to predict novel presence for not so well-known species (Pearson et al. 2007) and to predict the outcome of introductions of invasive species outside the native range (Ficetola et al. 2007; Rödder et al. 2008; Rödder and Lötters 2009). We initially considered 127 presence records of L. lucidum collected from fieldwork (50%), national herbarium specimen data examined by the authors (35%) and well as other records reported in the literature throughout the study area (15%). Obviously erroneous occurrence points (e.g., coordinates outside the studied area under which they had been listed) and duplications resulting from the merger of records from the different sources were removed. In the case of invasive species, most records tend to be collected where high densities of people and researchers occurs. This sampling bias may influence the prediction of the model. Therefore, we removed randomly presence records that were geographically close together trying not to leave records in adjacent cells. As a result, not all presence records collected were used in model calibration (60 presences records).

First, we obtained an initial set of 10 models setting Maxent with hinge and quadratic features and cross-validation, using 90% of presence data to fit the model and the remaining 10% for model validation given the small number of presence points. In addition, we disaggregated potentially clustered/repeated presence records by randomly selecting one per grid cell. In order to characterize the “background” of environment available to the species, we restricted the area only to the study region (Merow et al. 2013). This initial set was used to identify variables with minimal or no contribution to overall model taking into account the predictive efficacy using the jackknife test of variable importance, variable response curves and percent contribution of each variable in the model. Only environmental variables with relatively low collinearity (i.e., Pearson correlation values lower than 0.7 considering only the cells with presence data) and greater biological significance were selected. The average training gain values of selected variables were examined once again and the variables showing the lowest decrease in gain values when omitted from the full model were removed. These variables correspond to a subset of 19 climatic variables from the WorldClim database (http://www.worldclim.org/; Hijamans et al. 2005), that were projected at a 30 arc second (approximately 1 km2) spatial resolution.

The model’s performance was evaluated using the area under the receiver operating characteristic curve (AUC). An AUC value of 0.5 indicates that the performance of the model is no better than random, while values closer to 1.0 indicate better model performance (Phillips et al. 2006). To obtain a model we ran Maxent with 100 replicate using the reduced set of variables and the same setting. Then the 10 models with greatest AUC values were selected and averaged to obtain the final model. Finally, to generate a binary prediction of occurrence it was necessary to choose a threshold. Because no single procedure is recommended to select thresholds, we used a maximum training sensitivity plus logistic threshold to cut-off. This criterion has been described as the most objective to identify optimal habitats when only presence data are available (Liu et al. 2013a, b). Pixels with a value higher than the selected threshold were considered presence data, meaning that they harbored the appropriate climate conditions for the species. We used ArcGis 10.1 and Spatial Analysis tool to construct the final model.

Current distribution of Ligustrum lucidum forest at sub-regional scale

To evaluate and quantify the current distribution of L. lucidum forests we surveyed the whole Yungas ecoregion in Argentina and identified three focal zones where invasion was notorious (i.e., where several hectares of monodominant forest are present). These sectors included the peri-urban landscapes around the most important cities, centered in the localities of Yala (Y, Jujuy province), San Lorenzo (SL, Salta province) and Sierra de San Javier (SSJ, Tucumán province). These study sectors were included in two subsets of Landsat TM images: scene path 231/row 77 for Y and SL and scenes path 231/row 78 and 79 (mosaic) for SSJ. Four images were selected for each sector corresponding to January, July, August and December 2010 to maximize potential differences in phenology between native and exotic forest. Images were almost cloudless; the remaining few clouds (less than 10% in two images in one date) were masked. Landsat image proved an excellent alternative at low cost to mapping spread of L. lucidum forests and was previously used by Hoyos et al. (2010) and Gavier-Pizarro et al. (2012) in more seasonal forests of Argentina at higher latitude. The images have 30 × 30 m spatial resolution and were orthorectified and georeferenced using GPS points obtained in the field (geopositional error <10 m) and converted to the official coordinate system of Argentina (Gauss-Krügger POSGAR94 System, zone 3). The six multispectral bands of the Landsat images were combined into a single multi-temporal stack with resulting 24 bands for each study area. The stack of bands also included the normalized difference vegetation index (NDVI) and the hill shade image, obtained from the digital elevation model resampled to match the spatial resolution to a 30 × 30 m pixel, which allows modelling the shadows caused by the topography. As a result, final staked images included 26 layers of information: 24 multispectral bands + NDVI + hill shade. Images were obtained from the Instituto Nacional de Pesquisas Espaciais (http://www.dgi.inpe.br/CDSR/). Lastly, multi-temporal images for the three sites were clipped to cover the interest sectors leaving a surface of 106,183 ha for Y and SL sector, and 248,305 ha for SSJ.

Land cover maps were derived using the non-parametric classifier support vector machine (SVM; Hsu et al. 2007). SVM defines a hyperplane that separates points corresponding to two different classes in a multidimensional space (Huang et al. 2002; Foody and Mathur 2004). In our case, land cover was classified into five classes: 1, forest (including Yungas and dry forest, but also a small proportion of tree plantations), 2, L. lucidum forest, 3, urban, 4, water, and 5, others (agriculture, grassland, mix agriculture, citrus and perennials plantation, cleared, roads and bare soil). L. lucidum forests differ substantially in structural and physical characteristics from native forest (Grau et al. 2010). L. lucidum canopies are evergreen and closed, resulting in higher absorption in the visible domain and higher reflection in the near-infrared domain and thus present high NDVI (Zamora Nazca et al. 2014). During fieldwork in 2010, we identified training areas used to parameterize a SVM classifier. This methodological approach was previously used to classify our study species in other region of Argentina by Gavier-Pizarro et al. (2012).

Ligustrum lucidum relationship invasion with environment and land-cover changes at sub-regional and local scale

Based on the current distribution map of the L. lucidum forests in the three focal sectors (see current distribution of Ligustrum lucidum forest at sub-regional scale section) the landscape structure of these invaded stands was analyzed using the FRAGSTATS software (McGarigal and Marks 1995) at sub-regional scale. The selection of metrics was based on their ability to characterize various aspects of fragmentation such as: class area (sum the area of all fragments per class), mean patch size (an index of fragmentation), number of patches (an indicator of several ecological processes and landscape heterogeneity), total edge length (indicator of patch complexity), average nearest-neighbor distance and mean proximity index. Additional information on these metrics and detailed mathematical description can be found in McGarigal and Cushman (2002). In addition, we used ArcGis 10.1 and Spatial Analysis tool to compute descriptive statistics and explore the relationship between geographic distribution of L. lucidum forest patches and variables such as slope, elevation, temperature, precipitation and distance to roads, rivers and urban areas. We also explored the relationship between L. lucidum forests per sector (SSJ, SL and Y), population and cities’ features as time of foundation and size by fitting linear regression. Population data was extracted from official data of Censo Nacional de Población, Hogares y Viviendas 2010. INDEC-Instituto Geográfico Nacional (IGN, http://www.sig.indec.gov.ar/censo2010/). Additionally, to enrich the discussion we combined Ligustrum sub-regional map and urban data with the data from Córdoba City extracted from Gavier-Pizarro et al. (2012) where L. lucidum invasion has been reported.

To analyze the influence of past land-uses on forest invasion and to assess the invasion rate we worked at local scale in SSJ and San Miguel de Tucumán City, the most affected sector by the invasion. San Miguel de Tucumán is the largest political, economic and cultural urban center in NW Argentina. For this analysis, we used an additional set of land cover history data that we combined with our L. lucidum forests areas for 2010. The series of land cover maps previously made for SSJ by Gutiérrez-Angonese and Grau (2014) and Gutiérrez-Angonese (2015) were derived from Landsat MSS and TM images (30 × 30 m of spatial resolution) from 1972 to 2010, selecting early-spring cloud-free images with a temporal frequency of 4–5 years (1972, 1977, 1981, 1986, 1992, 1996, 2001, 2006 and 2010). All Landsat images were image-to-image spatially co-registered and atmospherically corrected using DOS method (Song et al. 2001). Images were classified by applying the machine learning algorithm Random Forest (Breiman 2001), using the Random Forest Package (Liaw and Wiener 2002) in the R statistical Software (R Development Core Team 2014). For this map land cover was classified into seven categories: 1, montane forest (SMF) that we called here Yungas forest, 2, dry forest or “Chaco” (DF), 3, montane grassland (MG), 4, anthropogenic grassland and shrubland (AG), 5, sugar cane (SC), 6, citrus plantations (CPs) and 7, high-to-medium density urban areas (UR). Final accuracy estimation OOB (out of bag) ranges from 8.8 to 12.6% of error in TM scenes and 12.9 to 18.8% in MSS scenes (Gutiérrez-Angonese and Grau 2014). To combine our data with the land cover history, we used our map of invaded areas by L. lucidum in 2010 as a reference. The set of data from Gutiérrez-Angonese and Grau (2014) and Gutiérrez-Angonese (2015) was used to estimate the temporal trajectory of the invasion and the previous land cover for the areas that end being L. lucidum forests in 2010. In the Gutiérrez-Angonese and Grau (2014) and Gutiérrez-Angonese (2015) data, different land covers were discriminated (see above), but L. lucidum forests were not discriminated from native forest (Yungas). Therefore, the map of L. lucidum forests in 2010 was used as a mask to extract the information from the history land cover maps and the invasion rate was estimated assuming that the class “SMF” in the Gutiérrez-Angonese and Grau data corresponds to L. lucidum forests.

Additionally, to investigate the factors that were associated with past invasion patterns of L. lucidum, we performed a multiple logistic regression using the presence of L. lucidum forests in 2010 as a binary dependent variable, and two sets of independent environmental and land use variables derived from the map of 1972 (Eastman 2016) (Table 2). A stratified sample (selecting 10% of the pixels) was applied to reduce the inherent spatial autocorrelation of spatial data (i.e., locations close to each other exhibit more similar values than those further apart). Model fit was evaluated through the pseudo-R2 coefficient, ranging from 0 to 1 (values greater than 0.2 means a good fit, Eastman 2016), representing the percentage of variance explained in non-linear functions. Additionally, the contribution of each independent variable to explain the probability of occurrence of L. lucidum forests in 2010 was assessed by obtaining the standardized coefficients (b′) of each variable, which allows comparing variables with one another, regardless of the unit of measurement for each variable. Standard coefficients were quantified using the formula proposed by Lesschen et al. (2005). The higher the ‘b’ value the more the corresponding variable contributes to explain the presence of Ligustrum forests in its current location.

Results

The model of potential L. lucidum distribution at regional scale (Fig. 1b) had a good overall accuracy with an AUC of 0.82 for independent data. Four variables were used in the setting of final model of the predictive map with different relative contribution: Bio 14: precipitation of the driest month (56%), Bio 1: annual mean temperature (25%), Bio 12: annual precipitation (12%) and Bio 6: minimum temperature of the coldest month (7%). The spatial model generated only by these environmental variables suggests that the study area presents a high climatic suitability, almost overlapping in some part with the distribution of Yungas ecoregion in Argentina (Fig. 1b). This is not surprising, given that L. lucidum tolerate a wide range of environmental conditions (Chang et al. 1996).

Despite its wide potential distribution range, L. lucidum forest patches were limited in 2010 to three “hotspots” of invasion in the peri-urban areas of the largest cities (Fig. 2). The L. lucidum forests covered approximately 700 ha in 2010, that represents 0.22% of the total forest area (324,000 ha) in these three sectors and was distributed in several patches (relatively discrete forest areas) with mean patch size of <0.6 ha (Table 1). Although the mean patch size was small, a high proportion of the invaded forests were distributed in large patches (between 2 and 38 ha, that represent more than 50% of the total invaded area). SSJ in Tucumán has the largest area of L. lucidum forests, and Y the smallest one. The spatial and spectral resolution of the Landsat TM images (30 m) did not allow us to detect young or mixed forest of L. lucidum, and only monodominant-invaded forest was detected, mapped and analyzed. Landscape indices appear related to the size of the total invaded area per sector. We observed an increase in mean patch size and a decrease in distance to nearest-neighbor from Y to SSJ (less to more invaded areas; Table 1); indicating a process of forest patch coalescence (inverse of fragmentation) as the area of L. lucidum forests increases.

Fig. 2
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Ligustrum lucidum forests current distribution and different land covers at sub-regional scale. Blue squares water† (lakes, lagoons, dams and rivers), yellow urban (cities, roads and others built-up areas), green forest (native perennial and deciduous forests and tree plantations), red L. lucidum forests (mono-specific and mature secondary forest) and brown others (all other cover types, i.e., extensive agriculture, grassland, mix agriculture, citrus and perennials plantation, sugar cane crops, cleared, roads and bare soil). †This class was considered as “other” in most of the analyses, figures, and tables. Black circles highlight areas with L. lucidum forests. (Color figure online)

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Table 1 Spatial patterns of L. lucidum forests (LFs) and other land-cover classes around three study areas in NW Argentina at sub-regional scale
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At sub-regional scale, the current L. lucidum forests were located between 15 and 19 °C mean annual temperature and 600–900 annual precipitation and in areas with gentle slopes (Fig. 3a–c). However, a particular distribution pattern was observed when considering elevation: L. lucidum forests were concentrated in two distinct altitudinal ranges: low elevation foothills (around 500 m.a.s.l.) and mountain ridges and slopes (between 1000 and 1500 m.a.s.l.; Fig. 3d). Additionally, L. lucidum forest patches were less common as distance to roads and rivers increase (Fig. 3e, f). Along the three sectors, a sturdy relationship with variables associated to cities was observed: L. lucidum forests extent appeared to be influenced by different urban features such as age of city foundation, size, urban population and population density of the three more important cities located in the Yungas. This relationship holds when the data for the City of Córdoba is included (Fig. 4).

Fig. 3
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Ligustrum lucidum forests (ha) and environmental or distance variables in the three peri-urban areas of NW Argentina (Y Yala, SL San Lorenzo, SSJ Sierra de San Javier) at sub-regional scale

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Fig. 4
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Relationship between urban features and Ligustrum lucidum forests by in the three peri-urban areas of NW Argentina (Y Yala, SL San Lorenzo, SSJ Sierra de San Javier) and Córdoba City (Cba). Data presented was transformed to natural logarithm (LN) in all cases. Data for Córdoba was obtained from Gavier-Pizarro et al. (2012). Population data was extracted from official data of INDEC. Censo Nacional de Población, Hogares y Viviendas 2010. Instituto Geográfico Nacional (IGN). 2010. http://www.sig.indec.gov.ar/censo2010/

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At local scale, patches of L. lucidum forest were distributed in seven clusters around San Miguel de Tucumán City and SSJ, mostly located at the top and bottom of the mountain range (Figs. 3d, 5). The distribution of L. lucidum forests cover in 2010 and the land-cover changes observed since 1972, indicate that the species doubled its area during this period from 306 to 620 ha. The invasion process apparently varied in intensity through time, with two main expansion pulses, during 1986–1992 and after 2001 (Fig. 6a). The expansion occurred mainly over CPs (43%, Fig. 6b) located at the foothills. Other anthropic uses such as AG or SC were comparatively less invaded by L. lucidum forests, representing 8 and 11% of net changes, respectively. Among natural ecosystems L. lucidum expansion occurred mainly over MG (approximately 34%) distributed at the top of SSJ.

Fig. 5
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Land cover type spatial distribution in 2010 at local scale. Black circles highlight areas that present Ligustrum lucidum forests. The small maps in the lower left corner shows the location of Tucumán province in Argentina and the location of surveyed area at local scale inside the province

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Fig. 6
figure 6

Local scale study in Sierra de San Javier (SSJ, Tucumán). a Area invaded by Ligustrum lucidum in each date during the period 1972–2010. b Area of land cover classes replaced by L. lucidum forests during the period 1972–2010. The values express the relative percentage of each land cover over the total invaded area during the period. MG mountain grassland, CPs citrus plantations, AG anthropogenic grassland, DF dry forest, SC sugar cane

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At local scale, precipitation and elevation were the best environmental predictors to explain the presence of L. lucidum forests. In addition, at this spatial scale there was also a negative relationship between new L. lucidum forests and slope (pseudo-R2 = 0.66, Table 2). However, according to the logistic regression analysis, land cover variables were better predictors than environmental factors to explain the presence of L. lucidum forests in SSJ (Table 2, b′ coefficient). Among these variables, distance to L. lucidum forests in 1972 was the variable that better explained the probability of occurrence of Ligustrum forests in 2010. Many patches were close to the initial foci of invasion, irrespectively of whether these patches were previously occupied by other uses, showing that this species’ spread involves a spatial “contagious” pattern. In addition, the invasion was enhanced in areas near to roads, CPs, DF, SC and UR, land covers mainly distributed in the piedmont of SSJ, and away from MG or AG (located at the top of SSJ) during the 1970s (Table 2).

Table 2 Results of multiple logistic regression at local scale (dependent variable = presence of L. lucidum forests in 2010; independent variables = environmental condition and distance to different land cover in 1972)
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Discussion

At the classical ecological or landscape scales, controls of plant succession can be categorized in three main groups of factors: (1) site availability, (2) differential species performance and (3) species availability (Pickett et al. 1987). Exotic plant invasions can be considered a particular component of plant succession, in which species availability plays a key role, and in turn, is regulated by mechanisms that operate at global scale and are dependent on socio-political variables in addition to biophysical ones. Thus, understanding plant invasion and its effects in framing emerging cultural landscapes, depends on the co-occurrence of factors that operate a different spatial scales, from global to local and that includes: (1) suitable environmental and climatic conditions, (2) human induced conditions/cultural landscape, and (3) human propagule introduction, “pressure”; and a posteriori landscape scale dispersal. In this study, we explored these different components as controls of the invasion of the Asian tree L. lucidum in the Argentinian Yungas ecoregion. Cities are a prominent and increasingly important cultural feature of landscapes and regions, since they regulate economic and political activities and concentrate human population that in turn has influential decisions over ecosystems. Our study point out the potential role of cities as key controls of the interaction between invasive species availability (largely anthropogenic) and landscape characteristics that control colonization and dispersal.

Suitable environmental and climatic conditions

The influence of environmental variables in invasive species distribution is well known (e.g., Gormley et al. 2011; Xu 2015). The results of our niche modelling (Fig. 1b) suggested that Yungas ecoregion in NW Argentina (mainly in Tucumán province) has suitable climatic conditions for the expansion of this species. L. lucidum forests current distribution, however, only occupies a minor and aggregated portion of this potential range, despite the species has been present in the region for more than a century. This could reflect the “lag phase” in biological invasions (Aikio et al. 2010). Although our understanding of causality is still limited, dispersal barriers coupled with the original location of seed sources rather than climatic conditions appear to be the main restriction to a widespread distribution. In its native range, L. lucidum experiences more extreme climatic conditions than in subtropical Argentina (from wet-warm to temperate) and grows up to 2500 m.a.s.l. (Chang et al. 1996). As a result, and according with niche conservationism (Peterson 2003; Thuiller et al. 2005), it is possible that this species presents advantageous adaptations to diverse environmental conditions. Furthermore, it has been documented that exotic species can broaden their native-range ecological niche during the process of invasion (e.g., Broennimann et al. 2007; Essl et al. 2009; Fitzpatrick et al. 2012). If this is the case of L. lucidum, we could expect major expansions of the current distribution area into the Argentinian Yungas, but also in other ecosystems such as dry forest or natural grasslands. The potential capacity of L. lucidum to invade places under different and contrasting environmental and vegetation conditions is supported by examples of invasions in other places of Argentina including sectors of dry forest in Córdoba (Gavier-Pizarro et al. 2012), grasslands in Buenos Aires (Ghersa et al. 2002) and riparian forest in Entre Rios (Torresin et al. 2013). In this work, we only sampled a subset of L. lucidum’s large geographic range. Thus, other environmental and climatic predictors may be important to explain the distribution at bigger scale studies (i.e., country, continental or global).

Human induced conditions/cultural landscape

We identified three hotspots of invasion in the Argentinian Yungas, with SSJ as the one experiencing the most advanced invasion (with more than 600 ha of homogeneous monodominant L. lucidum forest) and Y the least. Although this represents only 0.22% of the studied Yungas forest cover, there are many potential sources of invasion along this ecoregion. Landsat images provided an excellent data source to map L. lucidum invasion in dry seasonal forests (Hoyos et al. 2010; Gavier-Pizarro et al. 2012), but in partially evergreen mountain ecosystems, it showed limitations for mapping young or mixed stands, which could not be reliably discriminated from native forests. Previous works using remote sensing in SSJ showed the same limitation (Grau et al. 2008). In addition, small patches (<0.5 ha), even those highly dominated by L. lucidum were not detected due to the medium-spatial resolution of Landsat images. However, based on our extensive field knowledge, we are confident that our map captures the main patterns of L. lucidum invasion, showing the largest invaded forest patches.

In SSJ particularly, CPs (in the foothills) and MG (mainly distributed close to the mountain top) were the land cover types over which Ligustrum forests expanded more aggressively. Expansion occurred at a higher rate between 1986 and 1992 and after 2001 (Fig. 6). During the 1940s, a small touristic village was developed in SSJ, and in 1948 the National Government, legally expropriated nearly 10,000 ha to create a university project and a Natural Reserve. As a consequence, 36 private owners abandoned their agricultural land. However, the development failed to materialize; this history of land use may have produced the initial introduction of seed sources and availability of potentially colonized fields. Then, during 1973 through a Resolution of the National University of Tucumán, the Biological Park SSJ, a protected area that belonged to the University was created, and many areas were abandoned (Gutiérrez-Angonese and Grau 2014), creating opportunities for the second pulse of invasion. Although we do not have strong evidence to link directly the first and second pulses of invasion, our interpretation of the observed pattern is that political conservation decisions taken several years before invasion pulse could have unintentionally promoted the spread of L. lucidum by creating adequate local environmental conditions and encouraging the abandonment of agriculture and grazing fields. A similar pattern was found in another area by Gavier-Pizarro et al. (2012). In addition to formal conservation practices, the combination of abandonment of marginal agriculture and the expansion of sub-urban residential areas after the rapid economic growth during the beginning of the twenty first century may have favored the second expansion pulse.

Ligustrum lucidum monodominant forests close to peri-urban areas of large urban centers, present a strong spatial association with roads and rivers and with urban areas of larger size and higher population density (Figs. 3, 4; Table 1). Roads and rivers often act as corridors along which invasive species can spread (Wang et al. 2011a, b) and cities as reservoir of seed sources. Large urban areas of the Yungas ecoregion, appeared to have favored L. lucidum invasion likely by hosting large seed sources since the species is intensively used for urban forestry and vegetated fences near recently disturbed areas (e.g., in association to urban development), or recently abandoned agriculture lands (as agriculture becomes non-competitive in comparison to urban land uses) (Davis et al. 2000; Theoharides and Dukes 2007; Hufbauer et al. 2012). Importantly, the relationship between L. lucidum invaded area and cities size is consistent with the scaling attribute of cities (Bettencourt 2013), that explains several properties of urban systems considering variables such as green areas, transport infrastructure, human interaction, among others. This pattern is more evident if we combine our data with the L. lucidum cover around Córdoba City described by Gavier-Pizarro et al. (2012) (see Fig. 4). This relationship confirms that L. lucidum responds to the scaling rule proposed for city systems and could be considered as a side effect linked with the urban centers dynamics and functioning. It is also worth noting that even though L. lucidum showed strong association with peri-urban forest transition and land abandonment, and that the urban areas grew during the last decades, the expansion of new forest has slowed down in recent times (Gutiérrez-Angonese 2015); probably because newly abandoned agriculture areas are becoming scarce. However, our results should be considered a conservative estimate of the present invaded forests. Recent field data shows that L. lucidum is expanding into mature native forest (Malizia et al. 2017), revealing that invasion could occur by other ways unable to be detected by standard remote sensing methods.

Propagule pressure and dispersal

Our results suggest that humans and their activities are the main control of landscape features influencing L. lucidum distribution pattern. Urban areas play an important role as L. lucidum propagule sources, and roads and rivers enhance dispersion and increase propagule pressure into sites suitable for invasion, such as abandoned fields. The invasion across the cultural landscape followed a contagious pattern, with a strong decrease of invasion probability with distance from pre-existing Ligustrum stands. Consistently, previous studies suggested this pattern also could be consequence of propagule pressure conditions and seed dispersal mechanism at a micro local scale (Aragón and Morales 2003; Powell et al. unpublished work). In others words, urban and peri-urban areas present a relatively high abundance of L. lucidum as a result of widespread cultivation by humans in gardens and streets, and the availability of invasion prone sites. L. lucidum invasion into areas nearby seed sources, can later achieve persistence by two mechanisms. First, this species has a high growth rate and effective vegetative reproduction (Grau and Aragón 2000; Aragón and Groom 2003), which helps competitively displacing native species (Malizia et al. 2017). Second, L. lucidum produces massive fruit crops that fall and germinate underneath the parental tree (Aragón and Groom 2003). In addition, L. lucidum produces fruits during the winter (when native fruit offer is scarce) and its seeds are frequently eaten and dispersed by birds (Aragón and Groom 2003). Turdus rufiventris a medium-sized passerine, which is the most abundant fruit-eating bird species in the southern Argentinian Yungas, disperses seeds beyond canopy proximity, using native trees or abandoned CPs as perches (Blendinger et al. 2012; Ayup et al. 2014). Also as Powell et al. (unpublished work) confirmed recently, seeds dispersed by birds presented different spatial patterns depending on their handling technique and the tree density influenced the number of seeds and their dispersal distance. The combination and relative contribution of these factors to control invasion spread needs to be better understood in order to refine models of invasion and develop future scenarios.

Telecoupled cultural landscapes as a modifier of site and species availability to explain the L. lucidum invasion

Several studies described the biological traits that confer advantages to L. lucidum over the native species (Aragón and Groom 2003; Aragón and Morales 2003; Tecco et al. 2006; Easdale et al. 2007; Ferreras et al. 2008). Here, we showed that, human activities are also key factors controlling its expansion in Argentinian Yungas. As different studies revealed, human-assisted propagule movements and disturbances related to the development of cultural landscapes could be more important in shaping the invasion process than the invasive species’ traits themselves (Chytrý et al. 2008a, b). This suggests that tree invasion should be tackled from a multidisciplinary focus that includes the human dimension view and the dynamic processes associated with it (i.e., social, economic, geographic, historic and landscape ecology), in order to develop a comprehensive theoretical framework on how these factors operate during the invasion process at different stages and spatio-temporal scales.

Based in our multiscale analysis we argue that invasions have a strong interaction with “telecoupled cultural landscapes”. The concept of “telecouplings” has been recently developed to study the links between distant socio-environmental systems and the environmental modifications related with distant drivers (Liu et al. 2013a, b). The concept is used to study land use change processes (e.g., Gasparri and le Polain de Waroux 2014) and urban–rural interactions (Deines et al. 2016); it was proposed as potentially important to explain species invasions (Liu et al. 2013a, b). In the telecoupling frame, cities are crucial elements to articulate the interaction between the telecoupled systems (Seto et al. 2012). Cities concentrate the main fluxes of information, energy and materials, as well as the most powerful decisions. Therefore cities and peri-urban zones are particularly prone to result into “telecoupled cultural landscapes” where invasive plants such as L. lucidum could play the role of incorporating biological features from distant locations and creating novel ecosystems. In this scenario, peri-urban areas are expected to be the first ones affected.

Under this framework, to better understand why L. lucidum became a successful invasive species in Argentina it is advisable to consider the long and intermittent telecouplings operating between China and Americas, and particularly Argentina. Since the 1600s, sociocultural and economic telecoupling between Asia and the Americas has been intensive, especially related with the interchange of natural resources. For example, American silver enhanced Chinese economy particularly on final of Ming and beginning of Qing Dynasties (Flynn and Giráldez 2002; Flynn et al. 2003); and American crops species (maize, potato, sweet potato) helped mitigating human famine and changed human population dynamic (mainly in eighteenth century). In addition, sugar cane from SE Asia influenced socioeconomic organization and food habits in America (Mann 2006). Nowadays, both areas continue with some relationships that not only favor international trade of material resources (i.e., China is the main soybean importer from Argentina), but also important flows of people, information and cultural aspects (as garden diversity composition, type of food, natural medicine, etc.). Three of the cities described here, in which the surrounds are being invaded by L. lucidum forests (Salta, San Miguel de Tucumán and Córdoba), have more than 1% of their population composed by Asian people (INDEC 2010). Also, these cities and San Salvador de Jujuy, were important nodes of the trade route known as the ‘‘Hispanic American china silk route” used to commerce different goods from Asia during the colonial times (Bonialian 2014). Essl et al. (2011) emphasizes that the impact of human activities and socio economy legacy on species invasion can often exhibit a considerable time lag. For these reasons, we argue that historical flows and connections between native (China) and novel ranges (Argentina) need to be studied as relevant drivers of cultural landscape change and L. lucidum invasion.

Conclusions

Two main conclusions emerge from this study: first, a multiscale approach is necessary to explain invasive species distributions. Second, the interaction at multiple-scale between biophysical variables and factors involved in the development of cultural landscapes is crucial to explain invasive species success. As a corollary, we suggest that a better developed inclusion of cultural aspects into the theory of invasion is a priority.

Our results suggest that at regional scale, Yungas ecoregion of NW Argentina presents climatic conditions adequate for L. lucidum expansion. However, for the invasion to develop it is necessary the co-occurrence of other factors. In the studied area invaded ranges are clustered around the regional major cities and according to scale rules (i.e., the bigger the city, the larger the invaded area), thus suggesting that major urban centers in the Yungas ecoregion could create particular conditions in their surrounding areas that increase invasibility. The mechanisms that explain the relationship between cities size and L. lucidum invaded area are still unclear and need more research; but the contagious pattern of invasion suggests that propagule pressure and biological mechanisms (as seed dispersion and vegetative reproduction) can play a key role. Although we only evaluated recent historical factors of land use change in relation to trees invasion, we suggest that understanding the longer-term historical legacy of socioeconomic teleconnections between Asia and the Americas may provide useful insights for the development of a framework of teleconnected cultural landscapes, a potentially important concept for the geographical socioecology of the Anthropocene.