Management options for river conservation planning: condition and conservation re-visited

1. Systematic conservation planning is a process widely used in terrestrial and marine environments. A principal goal is to establish a network of protected areas representing the full variety of species or ecosystems. We suggest considering three key attributes of a catchment when planning for aquatic conservation: irreplaceability, condition and vulnerability. 2. Based on observed and modelled distributions of 367 invertebrates in the Australian state of Victoria, conservation value was measured by calculating an irreplaceability coefficient for 1854 subcatchments. Irreplaceability indicates the likelihood of any subcatchment being needed to achieve conservation targets. We estimated it with a bootstrapped heuristic reserve design algorithm, which included upstream–downstream connectivity rules. The selection metric within the algorithm was total summed rarity, corrected for protected area. 3. Condition was estimated using a stressor gradient approach in which two classes of geographical information system Layers were summarised using principal components analysis. The first class was disturbance measures such as nutrient and sediment budgets, salinisation and weed cover. The second class was land use layers, including classes of forestry, agricultural and urban use. The main gradient, explaining 56% of the variation, could be characterised as agricultural disturbance. Seventy‐five per cent of the study area was classified as disturbed. 4. Our definition of vulnerability was the likelihood of a catchment being exposed to a land use that degrades its condition. This was estimated by comparing land capability and current land use. If land was capable of supporting a land use that would have a more degrading effect on a river than its current tenure, it was classified vulnerable (66% of the study area). 79% of catchments contained more then 50% vulnerable land. 5. When integrating the three measures, two major groups of catchments requiring urgent conservation measures were identified. Seven per cent of catchments were highly irreplaceable, highly vulnerable but in degraded condition. These catchments were flagged for restoration. While most highly irreplaceable catchments in good condition were already protected, 2.5% of catchments in this category are on vulnerable land. These are priority areas for assigning river reserves.     

Land use designation and vegetation community structure in the Adirondack uplands (New York,USA)

Question: Does forest vegetation community structure reflect legislative land use designations? Location: Adirondack Park, New York, USA. Methods: The Adirondack Park, located in northern New York State, is a mixture of public and private lands, with state‐owned Forest Preserve lands comprising ca. 42% of the 2.4 million ha, on which timber harvesting and many other forms of anthropogenic disturbance are prohibited. A survey of vegetation communities was conducted in eighteen upland catchments with differing land use history (managed and Forest Preserve), including overstory, understory, and dead wood (snags and downed woody debris) using randomly placed plots. Results: Mean overstory density and basal area were not significantly different between land uses, although mean overstory tree size was greater in Preserve catchments. Sapling densities were greater in managed catchments, while mean herb/shrub coverage was not affected by land use. Densities of 25% of common species were affected by land use, determined by GIS coverages constructed using an Inverse Distance Weighted estimation procedure. Discriminant Analysis of per‐plot plant community data correctly classified 89% of both managed and Preserve plots. Conclusion: The success of the Discriminant Analysis in classifying land uses based on vegetation communities indicates its potential utility of this method in comparing forest vegetation to a reference condition in this and other areas. The analysis suggests that at least 85 years is required for Adirondack up‐land catchments to recover following harvesting. Uncertainty in classification was related to heterogenous management and disturbance patterns within catchments.     

Stratification of density in dry deciduous forest using satellite remote sensing digital data—An approach based on spectral indices

Forest density expressing the stocking status constitutes the major stand physiognomic parameter of Indian forest. Density and age are often taken as surrogate to structural and compositional changes that occur with the forest succession. Satellite remote sensing spectral response is reported to provide information on structure and composition of forest stands. The various vegetation indices are also correlated with forest canopy closure. The paper presents a three way crown density model utilizing the vegetation indices viz., advanced vegetation index, bare soil index and canopy shadow index for classification of forest crown density. The crop and water classes which could not be delineated by the model were finally masked from normalized difference vegetation index and TM band 7 respectively. The rule based approach has been implemented for land use and forest density classification. The broad land cover classification accuracy has been found to be 91.5%. In the higher forest density classes the classification accuracy ranged between 93 and 95%, whereas in the lower density classes it was found to be between 82 and 85%.     

Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

Aims 1. To characterize ecosystem functioning by focusing on above‐ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location Western portion of the Patagonian steppes in Argentina (39°30′ S to 45°27′ S). Methods We used remotely‐sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM‐derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely‐sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.     

Are landscape attributes a useful shortcut for classifying vegetation in the tropics? A case study of La Amistad International Park

Effective vegetation classification schemes identify the processes determining species assemblages and support the management of protected areas. They can also provide a framework for ecological research. In the tropics, elevation‐based classifications dominate over alternatives such as river catchments. Given the existence of floristic data for many localities, we ask how useful floristic data are for developing classification schemes in species‐rich tropical landscapes and whether floristic data provide support for classification by river catchment. We analyzed the distribution of vascular plant species within 141 plots across an elevation gradient of 130 to 3200 m asl within La Amistad National Park. We tested the hypothesis that river catchment, combined with elevation, explains much of the variation in species composition. We found that annual mean temperature, elevation, and river catchment variables best explained the variation within local species communities. However, only plots in high‐elevation oak forest and Páramo were distinct from those in low‐ and mid‐elevation zones. Beta diversity did not significantly differ in plots grouped by elevation zones, except for low‐elevation forest, although it did differ between river catchments. None of the analyses identified discrete vegetation assemblages within mid‐elevation (700–2600 m asl) plots. Our analysis supports the hypothesis that river catchment can be an alternative means for classifying tropical forest assemblages in conservation settings.     

Integrating a global agro-climatic classification with bioregional boundaries in Australia

Aim Stratification of major differences in the biophysical features of landscapes at the continental scale is necessary to collectively assess local observations of landscape response to management actions for consistency and difference. Such a stratification is an important step in the development of generalizations concerning how landscapes respond to different management regimes. As part of the development of a comparative framework for this purpose, we propose a climate classification adapted from an existing broad scale global agro‐climatic classification, which is closely aligned with natural vegetation formations and common land uses across Australia. Location The project considered landscapes across the continent of Australia. Methods The global agro‐climatic classification was adapted by using elevation‐dependent thin plate smoothing splines to clarify the spatial extents of the 18 global classes found in Australia. The clarified class boundaries were interpolated from known classes at 822 points across Australia. These classes were then aligned with the existing bioregional classification, Interim Biogeographic Regionalization for Australia IBRA 5.1. Results The aligned climate classes reflect major patterns in plant growth temperature and moisture indices and seasonality. These in turn reflect broad differences in cropping and other land use characteristics. Fifty‐two of the 85 bioregions were classified entirely into one of the 18 agro‐climatic classes. The remaining bioregions were classified according to sub‐bioregional boundaries. A small number of these sub‐bioregions were split to better reflect agro‐climatic boundaries. Main conclusions The agro‐climatic classification provided an explicit global context for the analysis. The topographic dependence of the revised climate class boundaries clarified the spatial extents of poorly sampled highland classes and facilitated the alignment of these classes with the bioregional classification. This also made the classification amenable to explicit application. The bioregional and subregional boundaries reflect discontinuities in biophysical features. These permit the integrated classification to reflect major potential differences in landscape function and response to management. The refined agro‐climatic classification and its integration with the IBRA bioregions are both available for general use and assessment.     

Relationships between land use, spatial scale and stream macroinvertebrate communities

1. The structure of lotic macroinvertebrate communities may be strongly influenced by land‐use practices within catchments. However, the relative magnitude of influence on the benthos may depend upon the spatial arrangement of different land uses in the catchment. 2. We examined the influence of land‐cover patterns on in‐stream physico‐chemical features and macroinvertebrate assemblages in nine southern Appalachian headwater basins characterized by a mixture of land‐use practices. Using a geographical information system (GIS)/remote sensing approach, we quantified land‐cover at five spatial scales; the entire catchment, the riparian corridor, and three riparian ‘sub‐corridors’ extending 200, 1000 and 2000 m upstream of sampling reaches. 3. Stream water chemistry was generally related to features at the catchment scale. Conversely, stream temperature and substratum characteristics were strongly influenced by land‐cover patterns at the riparian corridor and sub‐corridor scales. 4. Macroinvertebrate assemblage structure was quantified using the slope of rank‐abundance plots, and further described using diversity and evenness indices. Taxon richness ranged from 24 to 54 among sites, and the analysis of rank‐abundance curves defined three distinct groups with high, medium and low diversity. In general, other macroinvertebrate indices were in accord with rank‐abundance groups, with richness and evenness decreasing among sites with maximum stream temperature. 5. Macroinvertebrate indices were most closely related to land‐cover patterns evaluated at the 200 m sub‐corridor scale, suggesting that local, streamside development effectively alters assemblage structure. 6. Results suggest that differences in macroinvertebrate assemblage structure can be explained by land‐cover patterns when appropriate spatial scales are employed. In addition, the influence of riparian forest patches on in‐stream habitat features (e.g. the thermal regime) may be critical to the distribution of many taxa in headwater streams draining catchments with mixed land‐use practices.     

Pattern and process in Norwegian upland grasslands: a functional analysis

Abstract. Four classes of functional and morphological plant traits – established strategies (the CSR scheme sensu Grime 1979), life‐forms (sensu Raunkiaer 1934), morphology, and regenerative strategies – are used as tools for explaining vegetation gradients at summer farms in the mountains of western Norway. These farms are assembly points for free‐ranging domestic grazers, and differ floristically and ecologically from the surrounding heath or woodland vegetation. DCA and TWINSPAN are used to relate major gradients in a floristic data set from 12 summer farms to two sets of explanatory variables: (1) environmental variables representing physical factors, plot position, soils, and land use, and (2) the 4 classification schemes. The main floristic gradient parallels a spatial gradient from the centres of the farms to the surrounding vegetation. A functional interpretation based on the concurrent use of the 2 sets of explanatory variables suggests that the gradient is one of decreasing disturbance and increasing environmental stress caused by decreasing grazing and manure effects away from farms. Partial CCA is used to investigate the relationships between the 4 functional/morphological plant trait classes. The 4 classification schemes are partially redundant, and do not represent different trends of specialization within the landscape. There is no strong evidence for decoupling of the traits of the vegetative and regenerative phases within the data. The combination of general process‐based theories and specific plant attribute responses enhances the generality and interpretability of the study.     

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Clustering of multivariate data is a commonly used technique in ecology, and many approaches to clustering are available. The results from a clustering algorithm are uncertain, but few clustering approaches explicitly acknowledge this uncertainty. One exception is Bayesian mixture modelling, which treats all results probabilistically, and allows comparison of multiple plausible classifications of the same data set. We used this method, implemented in the AutoClass program, to classify catchments (watersheds) in the Murray Darling Basin (MDB), Australia, based on their physiographic characteristics (e.g. slope, rainfall, lithology). The most likely classification found nine classes of catchments. Members of each class were aggregated geographically within the MDB. Rainfall and slope were the two most important variables that defined classes. The second-most likely classification was very similar to the first, but had one fewer class. Increasing the nominal uncertainty of continuous data resulted in a most likely classification with five classes, which were again aggregated geographically. Membership probabilities suggested that a small number of cases could be members of either of two classes. Such cases were located on the edges of groups of catchments that belonged to one class, with a group belonging to the second-most likely class adjacent. A comparison of the Bayesian approach to a distance-based deterministic method showed that the Bayesian mixture model produced solutions that were more spatially cohesive and intuitively appealing. The probabilistic presentation of results from the Bayesian classification allows richer interpretation, including decisions on how to treat cases that are intermediate between two or more classes, and whether to consider more than one classification. The explicit consideration and presentation of uncertainty makes this approach useful for ecological investigations, where both data and expectations are often highly uncertain.     

Local vs. landscape controls on diversity: a test using surface-dwelling soil macroinvertebrates of differing mobility

Aim A better understanding of the processes driving local species richness and of the scales at which they operate is crucial for conserving biodiversity in cultivated landscapes. Local species richness may be controlled by ecological processes acting at larger spatial scales. Very little is known about the effect of landscape variables on soil biota. The aim of our study was to partly fill this gap by relating the local variation of surface‐dwelling macroarthropod species richness to factors operating at the habitat scale (i.e. land use and habitat characteristics) and the landscape scale (i.e. composition of the surrounding matrix). Location An agricultural landscape with a low‐input farming system in Central Hesse, Germany. Methods We focused on five taxa significantly differing in mobility and ecological requirements: ants, ground beetles, rove beetles, woodlice, and millipedes. Animals were caught with pitfall traps in fields of different land use (arable land, grassland, fallow land) and different habitat conditions (insolation, soil humidity). Composition of the surrounding landscape was analysed within a radius of 250 m around the fields. Results Factors from both scales together explained a large amount of the local variation in species richness, but the explanatory strength of the factors differed significantly among taxa. Land use particularly affected ground beetles and woodlice, whereas ants and rove beetles were more strongly affected by habitat characteristics, namely by insolation and soil characteristics. Local species richness of diplopods depended almost entirely on the surrounding landscape. In general, the composition of the neighbouring landscape had a lower impact on the species richness of most soil macroarthropod taxa than did land use and habitat characteristics. Main conclusions We conclude that agri‐environment schemes for the conservation of biodiversity in cultivated landscapes have to secure management for both habitat quality and heterogeneous landscape mosaics.     

The roles of floristics and physiognomy in avian community composition

There has been debate as to whether the composition of avifaunas is determined primarily by responses of species to the floristic composition of habitats or to the structural features of habitats (viz. physiognomy). Some evidence suggests that the effects of geographic scale may be the source of this dispute. The present analysis demonstrated that the influence of both floristics and physiognomy could be detected at the regional level for avifaunas of south-eastern Australian woodlands. The impact of floristics often may be obscured by patchiness and relatively rapid rates of spatial change in the phytosociology of habitats relative to those of avian species, even at the local scale (say 10 km). Such potential occlusion of the importance of floristics to avifaunas may be overcome by using floristic similarity indices that are based on plant taxonomic representations at both the specific and subfamilial levels. Both floristics and physiognomy are likely to affect avifaunal composition, although the perceived significance of each factor may vary with the scale of observation.     

Disentangling and ranking the influences of multiple environmental factors on plant and soil-dwelling arthropod assemblages in a river Rhine floodplain area

Floodplains of large rivers are among the most dynamic and diverse, yet most threatened ecosystems on earth. For a solid underpinning of river conservation and rehabilitation measures, it is critical to unravel the influences of the multiple stressors affecting floodplain ecosystems. Using canonical correspondence analysis with variance partitioning, we disentangled and ranked the influences of three floodplain ecosystem stressors (land use, flooding and soil contamination) on terrestrial plant and soil-dwelling arthropod assemblages in a floodplain area along the river Rhine in The Netherlands. We included five biotic assemblages: plant species (73 taxa), ground beetle species (57 taxa), ground beetle genera (29 taxa), beetle families (32 taxa) and arthropod groups at taxonomic levels from family to class (10 taxa). Plant and arthropod assemblages were primarily related to land use, which explained 19–30% of the variation in taxonomic composition. For plant species composition, flooding characteristics were nearly as important as land use. Soil metal contamination constituted a subordinate explanatory factor for the plant assemblages only (3% of variation explained). We conclude that the taxonomic composition of terrestrial plant and arthropod assemblages in our study area is related to land use and flooding rather than soil metal contamination.     

Avifaunal gradients in two arid zones of central Iran in relation to vegetation, climate, and topography

Aim To identify the ecological factors (related to vegetation, altitude, climate, or geomorphology) that could explain the main gradients of avifaunal richness and composition in arid environments of Central Iran. Location The study was carried out in two nearby semi‐arid protected areas of the Ispahan province: the Kolah‐Ghazi National Park (c. 50,000 ha; 1540–2535 m a.s.l.) and the Mouteh Wildlife Refuge (c. 220,000 ha; 1493–2900 m a.s.l.). Annual average precipitation and temperature range from 155–205 mm and 15–19.5 °C, respectively. Vegetation cover is sparse. Methods The two study areas were sampled with a 1 × 1 km grid design. A subset of 405 squares was randomly chosen and each was visited once during spring or summer by a team of five observers walking from one side of a square to the other and back, recording the birds encountered. Raptors and species considered to be accidental or migrating were not taken into account. We first looked for avifaunal, vegetation, and geomorphological gradients using Correspondence Analysis. As we found spatial autocorrelation within our response variables (avifaunal richness, abundance and/or composition), we first calculated an autocorrelation term, then added this autocorrelation term in anova , ancova (separate slope design) and stepwise regression to assess the relative role of spatial autocorrelation and environmental explanatory variables (vegetation, altitude, climate, or topography). We also partitioned the variance of the avifaunal matrix between several sets of co‐variables, after controlling for spatial effects, using a series of partial Canonical Correspondence Analyses. Results A main gradient, common to the two areas, distinguishes bird species characteristic of flat sedimentary areas and species dwelling in mountainous and/or rocky areas. Despite the generally low values of the correlations measured, we found that richness, abundance and composition of the avifauna were better correlated with topography, especially the altitudinal amplitude within each square, than any other variable, including vegetation. Altitudinal amplitude is related to substrate complexity. Main conclusions In arid zones of central Iran, topographic features seem to be the main factors structuring avifaunal composition and abundance. Avifaunal composition and richness are mainly correlated with the complexity of the substrate, but both avifaunal richness and abundance increase with altitude, probably in response to decreasing aridity. We did not observe any bird altitudinal zonation in a strict sense. These results contrast with those generally observed in mid‐latitude regions of the Palaearctic.     

Controls on water balance of shallow thermokarst lakes and their relations with catchment characteristics: a multi‐year,landscape‐scale assessment based on water isotope tracers and remote sensing in Old Crow Flats,Yukon (Canada)

Many northern lake‐rich regions are undergoing pronounced hydrological change, yet inadequate knowledge of the drivers of these landscape‐scale responses hampers our ability to predict future conditions. We address this challenge in the thermokarst landscape of Old Crow Flats (OCF) using a combination of remote sensing imagery and monitoring of stable isotope compositions of lake waters over three thaw seasons (2007–2009). Quantitative analysis confirmed that the hydrological behavior of lakes is strongly influenced by catchment vegetation and physiography. Catchments of snowmelt‐dominated lakes, typically located in southern peripheral areas of OCF, encompass high proportions of woodland/forest and tall shrub vegetation (mean percent land cover = ca. 60%). These land cover types effectively capture snow and generate abundant snowmelt runoff that offsets lake water evaporation. Rainfall‐dominated lakes that are not strongly influenced by evaporation are typically located in eastern and northern OCF where their catchments have higher proportions of dwarf shrub/herbaceous and sparse vegetation (ca. 45%), as well as surface water (ca. 20%). Evaporation‐dominated lakes, are located in the OCF interior where their catchments are distinguished by substantially higher lake area to catchment area ratios (LA/CA = ca. 29%) compared to low evaporation‐influenced rainfall‐dominated (ca. 10%) and snowmelt‐dominated (ca. 4%) lakes. Lakes whose catchments contain >75% combined dwarf shrub/herbaceous vegetation and surface water are most susceptible to evaporative lake‐level drawdown, especially following periods of low precipitation. Findings indicate that multiple hydrological trajectories are probable in response to climate‐driven changes in precipitation amount and seasonality, vegetation composition, and thermokarst processes. These will likely include a shift to greater snowmelt influence in catchments experiencing expansion of tall shrubs, greater influence from evaporation in catchments having higher proportions of surface water, and an increase in the rate of thermokarst lake expansion and probability of drainage. Local observations suggest that some of these changes are already underway.     

Importance of scale,land‐use,and stream network properties for riparian plant communities along an urban gradient

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Impacts of land use at the catchment scale constrain the habitat benefits of stream riparian buffers

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Climate and satellite-derived land cover for predicting breeding bird distribution in the Great Lakes Basin

Aim We examined relationships between breeding bird distribution of 10 forest songbirds in the Great Lakes Basin, large‐scale climate and the distribution of land cover types as estimated by advanced very high resolution radiometer (AVHRR) and multi‐spectral scanner (MSS) land cover classifications. Our objective was to examine the ability of regional climate, AVHRR (1 km resolution) land cover and MSS (200 m resolution) land cover to predict the distribution of breeding forest birds at the scale of the Great Lakes Basin and at the resolution of Breeding Bird Atlas data (5–10 km²). Specifically we addressed the following questions. (1) How well do AVHRR or MSS classifications capture the variation in distribution of bird species? (2) Is one land cover classification more useful than the other for predicting distribution? (3) How do models based on climate compare with models based on land cover? (4) Can the combination of both climate and land cover improve the predictive ability of these models. Location Modelling was conducted over the area of the Great Lakes Basin including parts of Ontario, Canada and parts of Illinois, Indiana, Michigan, New York, Ohio, Pennsylvania Wisconsin, and Minnesota, USA. Methods We conducted single variable logistic regression with the forest classes of AVHRR and MSS land cover using evidence of breeding as the response variable. We conducted multiple logistic regression with stepwise selection to select models from five sets of explanatory variables (AVHRR, MSS, climate, AVHRR + climate, MSS + climate). Results Generally, species were related to both AVHRR and MSS land cover types in the direction expected based on the known local habitat use of the species. Neither land cover classification appeared to produce consistently more intuitive results. Good models were generated using each of the explanatory data sets examined here. And at least one but usually all five variable sets produced acceptable or excellent models for each species. Main conclusions Both climate and large scale land cover were effective predictors of the distribution of the 10 forest bird species examined here. Models generated from these data had good classification accuracy of independent validation data. Good models were produced from all explanatory data sets or combinations suggesting that the distribution of climate, AVHRR land cover, and MSS land cover all captured similar variance in the distribution of the birds. It is difficult to separate the effects of climate and vegetation on the species’ distributions at this scale.     

High value of short rotation coppice plantations for phytodiversity in rural landscapes

The demand for wood from short rotation coppice (SRC) plantations as a renewable energy source is currently increasing and could affect biodiversity in agricultural areas. The objective was to evaluate the contribution of SRC plantations to phytodiversity in agricultural landscapes assessed as species richness, species–area relationships, Shannon indices, detrended correspondence analysis on species composition, Sørensen similarities, habitat preference proportions, and species proportions found in only one land use. Vegetation surveys were conducted on 12 willow (Salix spp.) and three poplar (Populus spp.) coppice sites as well as on surrounding arable lands, grasslands and forests in central Sweden and northern Germany. SRC plantations were richer in plant species (mean: 30 species per 100 m²) than arable land (10), coniferous forests (13) and mixed forests in Germany (12). Comparing SRC plantations with other land uses, we found lowest similarities in species composition with arable lands, coniferous forests and German mixed forests and highest similarities with marginal grassland strips, grasslands and Swedish mixed forests. Similarity depended on the SRC tree cover: at increased tree cover, SRC plantations became less similar to grasslands but more similar to forests. The SRC plantations were composed of a mixture of grassland (33%), ruderal (24%) and woodland (15%) species. Species abundance in SRC plantations was more heterogeneous than in arable lands. We conclude that SRC plantations form novel habitats leading to different plant species composition compared to conventional land uses. Their landscape‐scale value for phytodiversity changes depending on harvest cycles and over time. As a structural landscape element, SRC plantations contribute positively to phytodiversity in rural areas, especially in land use mosaics where these plantations are admixed to other land uses with dissimilar plant species composition such as arable land, coniferous forest and, at the German sites, also mixed forest.