湿地景观格局变化研究进展

湿地是自然界最富生物多样性的生态景观,具有重要的生态功能。湿地景观格局是各种生态过程综合作用的结果,具有高度的景观异质性,对景观的功能和过程有着显著的影响。湿地生态系统是世界上受威胁最为严重的生态系统之一,在自然因素和人类活动的影响下发生了大面积的转化或丧失。本文从湿地景观格局研究方法、面积变化、景观类型转化、驱动力以及动态模型、湿地景观格局指数以及湿地景观格局与气候变化之间的关系等方面综述了湿地景观格局变化的研究进展,指出湿地景观格局变化及其生态效应和高原湿地景观格局变化与气候变化之间的关系是未来研究的重点领域。     

How landscapes change: Integration of spatial patterns and human processes in temperate landscapes of southern Chile

A comprehensive understanding of the patterns that occur as human processes transform landscapes is necessary for sustainable development. We provide new evidence on how landscapes change by analysing the spatial patterns of human processes in three forest landscapes in southern Chile at different states of alteration (40%-90% of old-growth forest loss). Three phases of landscape alteration are distinguished. In Phase I (40%-65% of old-growth forest loss), deforestation rates are < 1% yr⁻¹, forests are increasingly degraded, and clearance for pastureland is concentrated on deeper soils. In Phase II (65%-80%), deforestation reaches its maximum rate of 1-1.5% yr⁻¹, with clearance for pastureland being the main human process, creating a landscape dominated by disturbed forest and shrubland. In this phase, clearance for pastureland is the primary driver of change, with pastures expanding onto poorer soils in more spatially aggregated patterns. In Phase III (80%-90%), deforestation rates are again relatively low (<1% yr⁻¹) and forest regrowth is observed on marginal lands. During this phase, clearance is the dominant process and pastureland is the main land cover. As a forest landscape is transformed, the extent and intensity of human processes vary according to the existing state of landscape alteration, resulting in distinctive landscape patterns in each phase. A relationship between spatial patterns of land cover and human-related processes has been identified along the gradient of landscape alteration. This integrative framework can potentially provide insights into the patterns and processes of dynamic landscapes in other areas subjected to intensifying human use.     

Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression

Scientific interpretation of the relationships between agricultural landscape patterns and urbanization is important for ecological planning and management. Ordinary least squares (OLS) regression is the primary statistical method in previous studies. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between several urbanization indicators (urbanization intensity index, distance to urban centers and distance to road) and changes in metrics describing agricultural landscape patterns (total area, patch density, perimeter area ratio distribution and aggregation index) at two block scales (5 km and 10 km). Results denoted that GWR was more powerful than OLS in interpreting relationships between agricultural landscape patterns and urbanization, since GWR was characterized by higher adjust R², lower Akaike Information Criterion values and reduced spatial autocorrelations in model residuals. Character and strength of the relationships identified by GWR varied spatially. In addition, GWR results were scale-dependent and scale effects were particularly significant in three aspects: kernel bandwidth of weight determination, block scale of pattern analysis, and window size of local variance analysis. Homogeneity and heterogeneity in the relationships between agricultural landscape patterns and urbanization were subject to the coupled influences of the three scale effects. We argue that the spatially varying relationships between agricultural landscape patterns and urbanization are not accidental but nearly universal. This study demonstrated that GWR has the potential to provide references for ecological planners and managers to address agricultural landscapes issues at all scales.     

The Role of Thresholds and Fine-Scale Processes in Driving Upper Treeline Dynamics in the Bighorn Mountains,Wyoming

This research investigates whether abrupt changes indicative of a threshold response occurred in the spatial and temporal patterns of tree establishment within upper treeline ecotones in the Bighorn Mountains of north-central Wyoming, with a particular focus on assessing whether treeline advance occurred. Dendroecological techniques were used to reconstruct the spatiotemporal patterns of tree establishment at multiple spatial scales (local and landscape). Increases in the elevational extent of treeline and tree density above timberline were reconstructed for each decade of the 20^th century. Regime-shift analysis was used to detect threshold changes in tree establishment. Marked increases in tree establishment and density occurred at local and landscape scales during the 20th century, particularly during the post-1970 period and in areas above timberline. Varying degrees of treeline advance occurred during this time, yet establishment upslope from timberline was often contingent on the availability of sheltered microsites in the lee of boulders. This highlights the importance of both broad-scale climate inputs and fine-scale site conditions in governing the rate and pattern of tree establishment in high-elevation treeline environments. Overall, the abrupt changes in tree establishment over time and space since 1970 suggest that bioclimatic thresholds can strongly influence ecotonal dynamics at upper treeline.     

Scale dependence in habitat selection: the case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Animals select habitat resources at multiple spatial scales. Thus, explicit attention to scale dependency in species–habitat relationships is critical to understand the habitat suitability patterns as perceived by organisms in complex landscapes. Identification of the scales at which particular environmental variables influence habitat selection may be as important as the selection of variables themselves. In this study, we combined bivariate scaling and Maximum entropy (Maxent) modeling to investigate multiscale habitat selection of endangered brown bear (Ursus arctos) populations in northwest Spain. Bivariate scaling showed that the strength of apparent habitat relationships was highly sensitive to the scale at which predictor variables are evaluated. Maxent models on the optimal scale for each variable suggested that landscape composition together with human disturbances was dominant drivers of bear habitat selection, while habitat configuration and edge effects were substantially less influential. We found that explicitly optimizing the scale of habitat suitability models considerably improved single-scale modeling in terms of model performance and spatial prediction. We found that patterns of brown bear habitat suitability represent the cumulative influence of habitat selection across a broad range of scales, from local resources within habitat patches to the landscape composition at broader spatial scales.     

Integrated Approaches,Multiple Scales: Snag Dynamics in Burned Versus Unburned Landscapes*

By studying landscape form and patterns, we can study processes at multiple scales and determine how collectively those processes inform us about function(s). Integrating landscape ecology from a biogeographical perspective with geographic information science (GIScience) practices offers new ways to study how landscapes change over time and space, including how they can be measured, analyzed, and modeled for management needs. This article presents methodologies and selected results of analyzing spatial patterns from field data across multiple scales by examining standing dead tree (snag) processes across wildfire‐disturbed landscapes in Arizona. Our primary motivation was to illustrate a particular type of work benefiting from the coalescing of landscape ecology and GIScience, functioning at the methodological and practical overlap of these two contributing fields. Our management goals were to (1) describe spatial patterns and characteristics of snags in pairs of burned and unburned ponderosa pine forests of Arizona in four recent (within the past ten years) wildfires, (2) document bird response to wildfires by combining landscape ecology and GIScience methods, and (3) link these patterns to snag monitoring plots and cavity‐nesting bird use to predict the probability of snag use by birds and cavity nesters based on snag characteristics (snag use model). The methods and results demonstrate how integration of landscape ecology with both GIS and GIScience improves the ways to study landscapes and land management issues, in this case offering guidelines for retention of snags that provide habitat for wildlife.     

鄱阳湖区2004-2010年水稻种植制度时空变化(英文)

Rice cropping systems not only characterize comprehensive utilization intensity of agricultural resources but also serve as the basis to enhance the provision services of agro-ecosystems.Yet,it is always affected by external factors,like agricultural policies.Since 2004,seven consecutive No.1 Central Documents issued by the Central Government have focused on agricultural development in China.So far,few studies have investigated the ef-fects of these policies on the rice cropping systems.In this study,based upon the long-term field survey information on paddy rice fields,we proposed a method to discriminate the rice cropping systems with Landsat data and quantified the spatial variations of rice cropping systems in the Poyang Lake Region(PLR),China.The results revealed that:(1) from 2004 to 2010,the decrement of paddy rice field was 46.76 km2 due to the land use change.(2) The temporal dynamics of NDVI derived from Landsat historical images could well characterize the temporal development of paddy rice fields.NDVI curves of single cropping rice fields showed one peak,while NDVI curves of double cropping rice fields displayed two peaks an-nually.NDVI of fallow field fluctuated between 0.15 and 0.40.NDVI of the flooded field during the transplanting period was relatively low,about 0.20±0.05,while NDVI during the period of panicle initiation to heading reached the highest level(above 0.80).Then,several temporal windows were determined based upon the NDVI variations of different rice cropping systems.(3) With the spatial pattern of paddy rice field and the NDVI threshold within optimum tem-poral windows,the spatial variation of rice cropping systems was very obvious,with an in-creased multiple cropping index of rice about 20.2% from 2004 to 2010.The result indicates that agricultural policies have greatly enhanced the food provision services in the PLR,China.     

中国景观生态学与生物多样性的交叉研究进展（英文）

The spatiotemporal landscape heterogeneity implies multiple biodiversity mechanisms across scales, and the cross-disciplinary studies between landscape ecology and biodiversity are becoming a new research field in China. This paper briefly reviews the development of the field by comparing papers published in international journals and Chinese journals;then it investigates the differences in the trends and focuses between international and Chinese studies. We also introduce several study areas that have emerged over the last 10 years in this field, including metacommunity assembly, landscape genetics, biodiversity and ecosystem service relationship, and landscape planning for biodiversity conservation. The major advances emerging in this field in China over the past 5 years can be classified into six subject areas: 1) effects of urban landscape and urbanization on biodiversity;2) altitudinal patterns of biodiversity in mountain landscapes;3) effects of topographic heterogeneity on plant community assembly and species coexistence;4) impacts of landscape patterns and processes on animal behaviors;5) forest fires and spatiotemporal patterns of vegetation responses;and 6) landscape ecology applications in natural conservation planning and design. In an attempt to promote cross-field studies between geography and ecology, this special issue collected 10 research articles, involving multiple landscape types and biological assemblages, in order to explore the interaction between landscape features and biodiversity. We anticipate that the future development of this active front will be primarily driven by the application of novel information techniques and the realistic demands of sustainability issues, in addition to answering scientific questions cross scales.     

Fragmentation Patterns in Land Reform Settlements in the Brazilian Amazon

Direct action land reform (DALR) and settlement formation are new drivers of deforestation in the Brazilian Amazon. However, until now no research has paid attention to fragmentation patterns and the social processes that lead to them. This article analyzes two types of settlements, spontaneous and social movement organization-led settlements. The study uses neutral landscape models (NLMs) to compare simulated landscapes with the real fragmentation patterns found in DALR settlements. In sequence, the article uses landscape metrics to analyze the temporal and spatial dynamics of fragmentation patterns in these two types of DALR settlements. Results showed that there are significant differences between real landscape patterns and simulated landscapes using NLMs. In other words, human interferences did play a significant role in shaping deforestation patches in DALR settlements. Our metric results revealed a process in which deforestation patch mean area, shape complexity, and physical connectedness increase over time.     

Can vegetation productivity be derived from greenness in a semi-arid environment? Evidence from ground-based measurements

Trends of biomass production and land processes in the Sahel have been widely studied since the droughts of 1970s. Satellite data have been an important source of information because of limited in situ data. Previous studies relied on the assumed existence of a relationship between vegetation productivity and the NDVI, in particular the annually integrated NDVI (iNDVI). This study examines this assumption and its limitations, based on in situ time series measurements of biomass, species composition, NDVI and soil moisture at the Dahra test site in northern Senegal. It is shown that, there are large differences between the NDVI – vegetation productivity relationships, and these differences can be linked to species composition. There is moderate correlation between NDVI and above-ground net primary productivity (ANPP) at the peak season (r² = 0.39). In particular, the species Zornia glochidiata is characterized by high peak NDVI and low ANPP, compared to other common species such as Cenchrus biflorus and Aristida adscensionis. It is concluded that spatial and temporal variations in species dominance is likely to add noise to the relationship between NDVI and biomass. However, the seasonal cyclic fraction of the NDVI – “small seasonal integral” – reduces such noise.     

西辽河流域历史早期的文化景观格局

考古发现表明 ,西辽河流域自历史早期以来 ,先后演绎了多期文化 ,文明一直延续至今。本文根据大量的野外考古调查资料 ,在典型考古遗址、教来河流域、敖汉旗三个空间尺度上建立了本区历史早期文化景观的DEM模型 ,分析了赤峰全境历史早期文化遗址点的水平分布格局 ,从四个不同的空间尺度探讨了西辽河流域历史早期文化景观的演变过程 ,概括出本区历史时期文化景观垂向变迁和水平变迁两种模式 ,为进一步深入研究本区人地系统的相互作用机制提供了基础。     

Exploring the relationships between post-fire vegetation regeneration dynamics,topography and burn severity: A case study from the Montane Cordillera Ecozones of Western Canada

In this study the relationships between vegetation regeneration dynamics to topography and burn severity for a Canadian landscape were investigated using freely available Earth Observation (EO) imagery from Landsat TM sensor. The Okanagan Mountain Park, located in the Montane Cordillera Ecozones of Western Canada at which a fire occurred in 2003, was used as a case study. First, vegetation regeneration dynamics were quantified for a period of 8 years following the fire event based on a chronosequence analysis of the Normalized Difference Vegetation Index (NDVI) and the Regeneration Index (RI). The spatio-temporal patterns of post-fire NDVI from each image date were statistically compared to the pre-fire pattern to determine the extent to which the pre-fire spatial pattern was re-established and also the rate of recovery. Subsequently, the relationships of vegetation regrowth to both topography and burn severity was quantified using a series of additional statistical metrics. Burn severity was derived from the differenced Normalized Burn Ratio (dNBR) index computed from the Landsat TM images. Information on topography properties of the region was obtained from the ASTER global operational product.NDVI and RI analysis indicated a moderate vegetation recovery to pre-fire patterns, with regeneration to over 60% of the pre-fire levels 8-years after the fire. Regression analysis of pre- and post-fire mean NDVI exhibited significant re-growth in the first 3 years after the fire with a more gradual return in later years (an increase of 0.400 in R² by 2006 compared to only an increase of 0.129 for the subsequent 5 years). Re-growth rates appeared to be somewhat higher in north-facing slopes in comparison to south facing ones. As expected, NDVI decline due to fire was positively correlated with burn severity class, whereas negative correlation was found between damage and regeneration ability (recovery after 3 years = low severity 64%/high severity 58%, recovery after 8 years = low severity 72%/high severity 70%). To our knowledge, this study is one of the few attempting to explore the interrelationships of post-fire vegetation regrowth, topography and burn severity, especially in the case of a single large fire. RI based on control plots provides a valuable tool to quantify fire impact and subsequent vegetation regrowth. Furthermore, indication of burn severity is useful for strategically rehabilitating areas of slow or unsuitable post-fire vegetation recovery. This study corroborates the significance of EO technology as a successful and cost-effective solution in providing information related to economic and environmental post-fire regeneration assessment.     

深圳市不透水表面的遥感监测与时空格局

定量监测城市不透水表面扩展过程,是分析城市景观格局动态,深入剖析城市地区空间镶嵌体内部异质性景观相互转化的重要基础。以深圳市为例,通过定量划分城市不透水表面等级体系,计算不透水表面的转移矩阵与景观格局指数,分析不透水表面的时空动态,结果表明:1990～2005年间,高盖度及极高盖度的不透水表面持续增加,中盖度及低盖度不透水表面先增加后减少,而自然地表及极低盖度的不透水表面则为先减少后恢复,反映了城市化进程对城市地表覆被的结构性影响。景观格局变化显示景观多样性程度较高,且经历了低-高-低-高的变化;斑块在1990年以自然地表为主,1995年以后以中盖度等级为主,高盖度等级显著增加。自然地表和中等盖度的不透水表面变化分别主导着前期和中后期的变化过程。城市建设的迅速扩张,将林地、农田、水体及滩涂等自然地表快速地转变为不同功能的建设用地,主导着不透水表面等级分布的梯度性变化。     

Transhumance as a driving force of landscape change in the marginal grabens of northern Ethiopia

Transhumance between the Afar lowlands and Tigray escarpments has been a common practice in northern Ethiopia. However, the impact of transhumance on landscape changes in the marginal grabens has not been significantly researched. Hence, this study aims to understand the process of transhumance and the linkages between social and biophysical aspects of the graben landscapes of northern Ethiopia. Google Earth (2010?2016) and Landsat Imageries (1995?2015) were used to analyse the spatio‐temporal landscape changes. Normalized Difference Vegetation Index (NDVI) was applied to measure the change in vegetation cover. Interview and Focus Group Discussions were used to collect perceptions of communities on transhumance and landscape change. The findings reveal that transhumance caused conflicts between the lowlanders and highlanders, which in turn led to displacement of communities. Consequently, the NDVI value of the abandoned settlement increased over time. Conversely, the analysis of Google Earth Imageries and NDVI values show that vegetation cover of the new settlement has decreased. Moreover, the NDVI values of the transhumance areas showed little increase due to the establishments of exclosures in the escarpments. The findings of this study can, therefore, be used to develop targeted interventions aimed at solving transhumance‐induced conflicts, displacement of communities and conservation of natural resources.     

Satellite-derived vegetation index and cover type maps for estimating carbon dioxide flux for arctic tundra regions

The spatial variability and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO₂ flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized difference vegetation index (NDVI) generated at two different spatial resolutions to a map of vegetation types derived by image classification of data from the Landsat multispectral scanner (MSS). Mean values of NDVI for each cover type stratum are unique (with the exception of moist acidic tundra and shrubland types). Based on analysis of semi-variograms generated for SPOT-NDVI data, most of the vegetation cover and landform features of this arctic tundra landscape have spatial dimensions of less than 1 km. Thaw lakes on the coastal plain and glacial depositional landforms, such as moraines in the foothills, seem to be the largest features, with vegetation units having dimensions no larger than 700 m. Frequency distributions of NDVI and vegetation types extracted for sampling transects flown by an aircraft sensing CO₂ flux, relative to distributions for the entire Kuparuk River watershed, suggest a slight sampling bias towards greater cover of mesic wet sedge tundra and thaw lakes and associated lower NDVI values. The regional pattern of NDVI for the North Slope of Alaska corresponds primarily to differences between the two major physiographic provinces of this region.     

Spatial expansion and water requirements of urban agriculture in Khartoum,Sudan

Urban agriculture (UA) in Khartoum, Sudan, contributes to meeting the increasing food demand of the city's rapidly growing population, but its spatial extent, development over time and resource consumption are unknown. To fill this knowledge gap, we analyzed scenes captured by Landsat satellites in 1972, 1987 and 2000. For each dataset, we calculated the Normalized Difference Vegetation Index (NDVI) and classified all grid cells with NDVI values higher than one standard deviation above the mean as vegetated land. We also quantified agricultural vegetation on aerial photographs taken in 1958 and on a recent Google Earth image. The built-up area of the city was estimated for each point in time. Based on these spatial estimates, we computed water consumption by UA based on geographic, temporal and climatic datasets and official data on the cropping patterns of Khartoum State, using the Penman–Monteith equation to estimate crop water demands, and assuming a water use efficiency of 0.56.Urban agriculture increased from 8751 ha in 1972 to 13,249 ha today. In the municipal core zone, UA decreased from 4799 ha in 1958 to 2869 ha today. Along the Nile, UA persisted through time, whereas many urban irrigation schemes have been pushed into the periphery. The built-up area increased strongly and today exceeds the UA area 5.5-fold. Estimated crop water demand on UA land increased from 241 to 365 million m³ year^?1 between 1972 and today.     

The tropical forest in south east Asia: Monitoring and scenario modeling using synthetic aperture radar data

Tropical forests play a major role in storing large carbon stocks and regulating energy, and water fluxes, but such forest cover is decreasing rapidly in spite of the policy attention on reducing deforestation. High-resolution spatiotemporal maps are unavailable for the forests in majority of the tropical regions in Asia because of the persistent cloud cover and haze cover. Recent advances in radar remote sensing have provided weather-independent data of earth surface, thus offering an opportunity to monitor tropical forest change processes with relatively high spatiotemporal resolutions. In this research, we aim to examine the tropical deforestation process and develop a spatial model to simulate future forest patterns under various scenarios. Riau Province from central Sumatra of Indonesia is selected as the study area; this province has received much attention worldwide because the highest CO₂ emission resulting from tropical deforestation has been recorded. Annual time series PALSAR data from 2007 to 2010 were analyzed for forest mapping and detecting land cover changes. A spatial model was calibrated using the Bayesian method. Modeling parameters were customized for the local subregions that allocate deforestation on the basis of their empirical relationships to physical and socioeconomic drivers. The model generated landscape spatial patterns mirrored the possible locations and extent of deforested areas by 2030 and provided time-series crucial information on forest landscape under various scenarios for future landscape management projects. The results suggested that the current deforestation process is in a critical stage where some subregions may face unprecedented stress on primary forest costing rivers and forest ecosystems by the end of 2020. The perspective views of Riau Province generated by the model highlighted the need for forest/environmental planning controls for the conservation of environmentally sensitive areas.     

Effects of spatial aggregation approaches on classified satellite imagery

Spatial aggregations of raster data based on the majority rule have been typically used in landscape ecological studies. It is generally acknowledged that (1) dominant classes increase in abundance while minor classes decrease in abundance or even disappear through aggregation processes; and (2) spatial patterns also change with aggregations. In this paper, we examined an alternative, random rule-based aggregation and its effects on cover type abundance and landscape patterns, in comparison with the majority rule-based aggregation. We aggregated a classified TM imagery (about 1.5 million ha) from 30m (4231 × 3717 pixels) incrementally to 990m resolution (132 pixels × 116 pixels). Cover type proportion, mean patch size ratio, aggregation index (AI), and fractal dimension (FD) were used to assess the effects of aggregation. To compare landscapes under different resolutions, we assumed that the landscapes were least distorted if (1) the cover type proportions and mean patch size ratios among classes were maintained, and (2) all cover types responded in the same way for a given index as aggregation levels increased. For example, distortion is introduced by aggregation if some cover types increase their AI values with increasing aggregation levels while other cover types decrease. Our study indicated that the two spatial aggregation techniques led to different results in cover type proportions and they altered spatial pattern in opposite ways. The majority rule-based aggregations caused distortions of cover type proportions and spatial patterns. Generally, the majority rule-based aggregation filtered out minor classes and produced clumped landscapes. Such landscape representations are relatively easy for interpreting and, therefore, are suitable for land managers to conceptualize spatial patterns of a study region. By contrast, the random rule-based aggregations maintained cover type proportions accurately, but tended to make spatial patterns change toward disaggregation. Overall, the measurements of landscape indices used in this study indicated that     

Intermediate disturbance and patterns of species richness

Abstract

The intermediate disturbance hypothesis (IDH) predicts highest species diversity in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting the magnitude of disturbance and the time since it occurred. We model changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance in order to predict first the variation of richness through time in individual patches, based on their disturbance histories, and then the changing patterns of richness across the landscape through time, representing the cumulative impact of changing richness within the individual patches. Model outputs show that individual landscape patches have highly variable species richness through time, with the trajectory reflecting the timing, intensity and sequence of disturbances. When the results are mapped across the landscape, the resulting temporal and spatial complexity reveals a distribution of biodiversity that is strikingly contingent on the details of disturbance history. These results illustrate the danger of generalization (in either data interpretation or management decisions), as IDH actually imposes a highly variable pattern of diversity.     

陕北黄土高原景观动态的植被覆盖季节响应

半干旱地区生态环境状态与景观动态变化息息相关,为深入探讨景观动态的生态响应,本研究选择陕北黄土高原为研究区,分别就景观动态的3种类型 (景观类型间变化、类型内组分变化及未变化) 与植被覆盖状态进行分析。其中植被覆盖状态主要通过植被覆盖值高低及年内植被恢复期、维持期与转折点等曲线特征体现。结果发现研究区景观类型的动态变化并不显著,而各动态类型与植被覆盖的相关程度各不相同,植被覆盖不仅和景观类型有关,亦与景观动态类型有关,而在植被覆盖对景观动态的响应上,则体现出由于景观动态类型的差异,造成同一景观类型的植被覆盖季节响应模式和强度完全不同。