Effects of land ownership and landscape-level factors on rare-species richness in natural areas of southern Ontario,Canada

Surprisingly few studies have considered the extent to which the nature of the ownership of land is associated with differences in biodiversity. We analysed ownership and other landscape-level effects on rare-species richness for both globally- and regionally-rare biota (including birds, herpetofauna, butterflies, mammals, and plants) in 289 designated natural areas (NAs) in southern Ontario, Canada. Information about each NA −including area, number of plant communities, ownership status and details of species diversity were collected from published sources. Length of perimeter of NA, relative isolation, and an estimate of fragmentation were measured using image analysis and GIS techniques. NAs were in general relatively small, with mean area of 158 ha (median 85 ha, range from 0.9 to 1278 ha) for private NAs; public NAs had mean area of 132 ha (median 16 ha, range from 0.1 to 1481 ha). Mean number of plant communities was 4.6 (median 4, range 1- 13) at private NAs and 3.8 (median 3, range 1-16) at public NAs. Our results show that, of several landscape-level factors, area had the greatest effects on rare-species richness and other biotic indices. Effects of area were followed by effects of plant community diversity, however this was itself significantly affected by area and the extent of perimeter of the NA. Both these factors were followed by effects of ownership of the NA and by effects of isolation of the NA (represented by minimum distance to nearest NA and by number of NAs in 10 km radius). Other landscape- level factors did not appear to have overall significant effects. Variation in area accounted for 0.1% to 29% of variation in number of rare species, with lower values for globally-rare, than for regionally-rare taxa. For all biotic groups, public ownership of NAs was associated with significantly greater rare-species richness compared to private ownership, even after other factors such as area were controlled. For all globally-rare biota except butterflies, area of NA had greater effects on rare-species richness than did ownership. Richness of regionally- rare birds was more affected by plant community diversity than by area of NA. Number of recorded plant communities accounted from 2.1% of variation in number of globally-rare plant species to as high as 31% of variation in regionally-rare butterflies. The diversity of plant communities was itself influenced by total site area (accounting for 45% of variation), extent of elongation of the NA, and both external- and interior- edge perimeters. Public NAs had greatest numbers of rare biota and so should be a significant focus for conservation programs. Smaller, privately-owned patches of natural area dominate (by number and area) in this densely populated region and their significance should not be overlooked. This revised version was published online in July 2006 with corrections to the Cover Date.     

Population dynamics and habitat connectivity affecting the spatial spread of populations – a simulation study

In this paper we show how the spatialconfiguration of habitat quality affects the spatial spread of apopulation in a heterogeneous environment. Our main result is thatfor species with limited dispersal ability and a landscape withisolated habitats, stepping stone patches of habitat greatlyincrease the ability of species to disperse. Our results showthat increasing reproductive rate first enables and thenaccelerates spatial spread, whereas increasing the connectivity has aremarkable effect only in case of low reproductive rates. Theimportance of landscape structure varied according to thedemographic characteristics of the population. To show this wepresent a spatially explicit habitat model taking into accountpopulation dynamics and habitat connectivity. The population dynamicsare based on a matrix projection model and are calculated on eachcell of a regular lattice. The parameters of the Leslie matrix dependon habitat suitability as well as density. Dispersal between adjacentcells takes place either unrestricted or with higher probability inthe direction of a higher habitat quality (restricted dispersal).Connectivity is maintained by corridors and stepping stones ofoptimal habitat quality in our fragmented model landscape containinga mosaic of different habitat suitabilities. The cellular automatonmodel serves as a basis for investigating different combinations ofparameter values and spatial arrangements of cells with high and lowquality.This revised version was published online in May 2005 with corrections to the Cover Date.     

Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah,USA

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

退耕还草产业化技术经济效果评价方法探讨

以平凉市退耕还草产业化技术开发为例,以产业化系统链中各子系统间的功能协调统一为依据,以退耕还草产业化机制为纽带,在研究建立平凉市退耕还草产业化技术经济效果包括4个一级指标(基础指标、配套指标、服务指标和效益指标)和17个二级指标体系的基础上,采用层次分析法(AHP法)、隶属度函数法和综合效益指数法作为退耕还草产业化技术经济效果的评价方法.经比较得出:平凉市退耕还草产业化技术开发综合指数达到0.595 1,属初步产业化阶段,相对发展指数达到27.268%,年均产业化进步速度达到6.817%.     

三江源区土壤侵蚀变化及驱动因素分析

采用修正通用土壤流失方程(revised universal soil loss equation, RUSLE)对三江源区1997-2012年的土壤侵蚀模数和土壤侵蚀量进行定量模拟,并对其生态工程实施前、后时空变化特征进行对比分析,采用空间叠加法分析降雨侵蚀力及植被覆盖度对土壤侵蚀状况的影响,利用模型参数控制法对气候变化和生态工程对土壤侵蚀变化的贡献率进行分析。结果表明:1)生态工程实施后,三江源区土壤侵蚀增加的趋势尚未得到遏制,多年平均年土壤侵蚀模数和侵蚀量较工程实施前增加6.5%,但局部地区土壤侵蚀状况有所好转,约占总面积的45%;2)长江流域在工程实施后的土壤侵蚀量与工程实施前基本持衡;黄河流域土壤侵蚀量增加明显,增幅超过45%;澜沧江流域土壤侵蚀量有所下降,降幅为9.8%;3)降水增强导致土壤侵蚀加剧的贡献率达到180%,植被恢复对土壤侵蚀变化的贡献率为-80%。全面遏制三江源区土壤侵蚀增加趋势,仍需持续努力。     

土壤侵蚀下黑龙江省人地系统适应性研究

为缓解人地关系,以对黑龙江省威胁最大的土壤侵蚀为切入点,从"三生"视角分析区域人地系统适应性,并提出基于不同修复优先级的人地系统修复方案。首先,在总结、梳理适应性内涵,整合适应性理论与方法基础上,从"三生"视角提出了基于风险扰动的适应性分析框架,将系统适应性分解为扰动、影响、响应、能力4方面,并从土壤侵蚀风险扰动出发,构建了系统适应性评价指标体系与评价模型;其次,采用极差标准化法、克里格插值法、蔡崇法法和DEA-CCR模型处理数据,利用土壤侵蚀方程测算土壤侵蚀风险,利用适应性评价模型测算适应性指数,分析土壤侵蚀风险和人地系统适应性分布情况;最后,提出基于不同修复优先级组合模式的人地系统修复方案。结果表明:黑龙江省土壤侵蚀风险区面积为1 366.61万hm2,占区域耕地面积的85.74%,高、中、低级别风险规模分别为324.02、596.33、446.26万hm2。高、较高级别人地系统适宜程度区分布在三江平原东北部和松嫩平原东南部地区,中级别分布在大兴安岭和松嫩平原南部地区,低、较低级别分布在东南部山地和松嫩平原北部地区。形成了基于不同修复优先级组合模式的人地系统修复方案,其中53个地区仅存在1种人地系统修复方案,其余27个地区在不同优先级组合模式下形成了不同的人地系统修复方案,为区域人地系统修复提供了多种选择方案。     

不同保水处理下苏丹草光合特性研究

为了研究矿区生态修复过程中植物对不同保水措施的生理响应,以常用修复植物苏丹草为研究对象,利用CIRAS-2型(PP-Systems)光合仪测定苏丹草的光合指标,探讨高温下苏丹草对不同保水措施的生理响应,以期为矿区生态修复中的保水措施提供理论依据。结果表明：不同保水处理下苏丹草的光合速率Pn和瞬间水分利用效率WUE日变化均呈“W”型曲线,蒸腾速率Tr日变化呈“M”型曲线。苏丹草的Pn有“午休”现象存在,主要受非气孔因素的影响。影响苏丹草Pn、Tr的主要环境因子为大气CO₂浓度Ca、大气温度Tc、大气相对湿度RH。在土壤上覆盖火烧石和添加粉煤灰均显著增大了苏丹草的Pn和WUE,增强了苏丹草适应高温环境的能力。从Pn的指标来看,土壤表面覆盖火烧石处理比土壤中添加粉煤灰处理的效果好,但两者同时作用效果略低于单独用火烧石处理,原因有待进一步研究。     

四川新津白鹤滩国家湿地公园核心区植物景观配置研究

四川新津白鹤滩国家湿地公园位于成都市新津县境内,是典型的河流漫滩和沙洲地貌。受亚热带湿润气候影响,湿地公园核心区拥有种类丰富的湿地动植物资源,但近几年人们在场地周边的开发活动,对基地原有植物生态环境造成破坏_^[1]。现在核心区仅存那些对水质要求低和抗逆性强的植物,同时也因为植物种类过于单一,随之而来的就是湿地季节性功能失调现象,如对水质净化的能力差,水体富营养化严重。为缓解和改善湿地核心区现存问题,一个具有生态修复功能的植物景观配置就显得尤为重要,本论文主要以生态恢复学、植被演替理论等为理论支撑,借鉴LID技术在湿地生态修复的应用,结合对基地本身植物资源调查的基础,通过对不同植物的配置选择,构建起了多样的新旧植物景观模式,用以探索科学合理的湿地公园植物景观配置模式,以期恢复新津湿地公园植被生态多样性,提升视觉景观效果。     

Contrasting development of soil microbial community structure under no-tilled perennial and tilled cropping during early pedogenesis of a Mollisol

A range of agricultural practices influence soil microbial communities, such as tillage and organic C inputs, however such effects are largely unknown at the initial stage of soil formation. Using an eight-year field experiment established on exposed parent material (PM) of a Mollisol, our objectives were to: (1) to determine the effects of field management and soil depth on soil microbial community structure; (2) to elucidate shifts in microbial community structure in relation to PM, compared to an arable Mollisol (MO) without organic amendment; and (3) to identify the controlling factors of such changes in microbial community structure. The treatments included two no-tilled soils supporting perennial crops, and four tilled soils under the same cropping system, with or without chemical fertilization and crop residue amendment. Principal component (PC) analysis of phospholipid fatty acid (PLFA) profiles demonstrated that microbial community structures were affected by tillage and/or organic and inorganic inputs via PC1 and by land use and/or soil depth via PC2. All the field treatments were separated by PM into two groups via PC1, the tilled and the no-tilled soils, with the tilled soils more developed towards MO. The tilled soils were separated with respect to MO via PC1 associated with the differences in mineral fertilization and the quality of organic amendments, with the soils without organic amendment being more similar to MO. The separations via PC1 were principally driven by bacteria and associated with soil pH and soil C, N and P. The separations via PC2 were driven by fungi, actinomycetes and Gram (−) bacteria, and associated with soil bulk density. The separations via both PC1 and PC2 were associated with soil aggregate stability and exchangeable K, indicating the effects of weathering and soil aggregation. The results suggest that in spite of the importance of mineral fertilization and organic amendments, tillage and land-use type play a significant role in determining the nature of the development of associated soil microbial community structures at the initial stages of soil formation.