Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Land use changes and conservation threats in the eastern Selous–Niassa wildlife corridor,Nachingwea, Tanzania

Selous–Niassa miombo woodland ecosystem has been and continues to face conservation threats. Understanding of changes happening in such ecosystem overtime is important for establishing management baseline data. This study identified land use changes, socio‐economic factors and conservation threats to the Selous–Niassa wildlife corridor across Nachingwea district, Tanzania. Landsat images of 1978, 1993 and 2000 were used to assess land use changes. Household survey was conducted to obtain socio‐economic data; logistic regression model was used to analyse the data. In 15 years (1978–1993) cultivated land only increased by 131% while forestlands decreased by 8.7%. In 12 years (1993–2005) cultivated land increased by 65.6% while forestland decreased by 10.7%. Land cover change per year has been found 0.54% relatively low compared to national land cover change of 45%per year. Land tenure, shifting cultivation and crops prices were major factors influencing land use changes while wildfires, farm encroachment and illegal timber harvesting were major conservation threats. Basing on the results, it was recommended that there is a need for a government to introduce community‐based natural resource management plans to improve natural resource utilization and reduce human stress to the corridor.     

Shifts in soil organic carbon for plantation and pasture establishment in native forests and grasslands of South America

The replacement of native vegetation by pastures or tree plantations is increasing worldwide. Contradictory effects of these land use transitions on the direction of changes in soil organic carbon (SOC) stocks, quality, and vertical distribution have been reported, which could be explained by the characteristics of the new or prior vegetation, time since vegetation replacement, and environmental conditions. We used a series of paired‐field experiments and a literature synthesis to evaluate how these factors affect SOC contents in transitions between tree‐ and grass‐dominated (grazed) ecosystems in South America. Both our field and literature approaches showed that SOC changes (0–20 cm of depth) were independent of the initial native vegetation (forest, grassland, or savanna) but strongly dependent on the characteristics of the new vegetation (tree plantations or pastures), its age, and precipitation. Pasture establishment increased SOC contents across all our precipitation gradient and C gains were greater as pastures aged. In contrast, tree plantations increased SOC stocks in arid sites but decreased them in humid ones. However, SOC losses in humid sites were counterbalanced by the effect of plantation age, as plantations increased their SOC stocks as plantations aged. A multiple regression model including age and precipitation explained more than 50% (p < 0.01) of SOC changes observed after sowing pastures or planting trees. The only clear shift observed in the vertical distribution of SOC occurred when pastures replaced native forests, with SOC gains in the surface soil but losses at greater depths. The changes in SOC stocks occurred mainly in the silt+clay soil size fraction (MAOM), while SOC stocks in labile (POM) fraction remained relatively constant. Our results can be considered in designing strategies to increase SOC storage and soil fertility and highlight the importance of precipitation, soil depth, and age in determining SOC changes across a range of environments and land‐use transitions.     

CLUE-S模型在长白山自然保护区外围规划中的应用

受自然保护区旅游业快速发展影响,长白山自然保护区外围土地利用变化加剧。因此,对区域土地利用布局进行科学规划具有十分重要的意义。以长白山自然保护区外围30 km区域为研究对象,探讨了CLUE-S模型在小尺度土地利用规划中的应用。在分析研究区1991—2007年土地利用变化的驱动力基础上,根据区域规划预案,模拟2020土地利用布局。利用模拟结果划定空间管制区和乡镇布局,并与现有规划进行了对比。结果表明,基于CLUE-S模型的土地规划明显抑制了区域景观破碎化进程,减弱了人为活动对景观的影响,该方法可以为长白山区域土地利用规划提供有力的技术手段和科学支撑。     

基于多智能体与元胞自动机的上海城市扩展动态模拟

利用元胞自动机模型和多智能体模型相结合的方法,在GIS技术手段的支持下构建了一个能够兼顾两种模型优点的城市扩展动态模型,并以上海市为实证对象,模拟了上海市2005年的城市扩展动态,分别预测了2010年和2020年上海城市扩展的动态演化结果。在元胞自动机模型中定义城市系统中的各种自然、社会和交通等要素,在智能体模型中定义政府和居民智能体的行为。模型将二者结合起来,模拟上海中心城区、城郊区及外围区的城市用地扩展模式。对模型模拟的上海2005年土地利用状态和实际土地利用状态进行验证,Kappa系数的平均值达到0.75以上,说明模型具有较高的可信度。对预测出2010年和2020年上海市土地利用状态分析表明,城镇用地以向东部和南部扩张最为明显。     

Using past and present habitat to predict the current distribution and abundance of a rare cryptic lizard,Delma impar (Pygopodidae)

We present logistic regression models predicting the distribution and abundance of a threatened cryptic lizard, Delma impar (Pygopodidae), in the Australian Capital Territory (ACT). The models incorporate current habitat and historical land use and habitat change (woodland clearance, ploughing, grazing, fertilizer application). Information on historical land use was acquired from land survey maps, aerial photographs and from floristic indices of land management. Floristic indices were developed from a survey of local agronomists who scored individual plant species, responses to grazing, ploughing and fertilizer application. Floristic indicies proved to be more informative than floristic ordination analyses. It emerged that historical factors were of key importance for predicting the distribution and abundance of D. impar. Since European settlement, D. impar has apparently spread from primary (naturally treeless grasslands) into secondary grasslands (grassland formerly with an overstorey of trees) and has been locally excluded by some farming activities such as ploughing. We conclude that a combination of current habitat and past changes in habitat may be necessary to understand the current distributions of plant and animal species that have limited dispersal ability and that are susceptible to local temporary habitat destruction. Active conservation strategies involving, for example, assisted dispersal, may be important for these species.     

张家界女儿寨小流域植被变化驱动力

选择坡度、海拔、坡向、到道路和河流及居民点的最近距离等作为植被变化的空间驱动因子,分别采用传统Logistic和AutoLogistic回归模型,对比研究湖南张家界女儿寨小流域植被变化的驱动力,并用ROC方法检验这两个模型的解释能力。结果表明:(1)在女儿寨小流域,各类植被变化和空间驱动因子均表现出一定的空间正自相关,且这种空间自相关性随着距离的增加而逐渐减弱。(2)考虑空间自相关性的AutoLogistic模型比传统Logistic模型的精度更高,这说明在分析小流域植被变化的空间驱动力时不能忽略空间自相关性的影响。考虑空间自相关后,显著的空间驱动因子的个数比未考虑空间自相关性的个数少。(3)自然环境和人类活动因子对小流域植被变化的影响力不同:坡度对耕地变化、果园变化、常绿阔叶林变化和针叶林变化等均影响较大;坡向对耕地变化、果园变化、常绿阔叶林变化和灌木林地变化的影响显著;海拔对该小流域各种植被变化类型的影响相对较小;人类活动的影响对落叶阔叶林的变化影响显著。     

Landscape dynamics in Mediterranean oak forests under global change: understanding the role of anthropogenic and environmental drivers across forest types

The Mediterranean region is projected to be extremely vulnerable to global change, which will affect the distribution of typical forest types such as native oak forests. However, our understanding of Mediterranean oak forest responses to future conditions is still very limited by the lack of knowledge on oak forest dynamics and species‐specific responses to multiple drivers. We compared the long‐term (1966–2006) forest persistence and land cover change among evergreen (cork oak and holm oak) and deciduous oak forests and evaluated the importance of anthropogenic and environmental drivers on observed changes for Portugal. We used National Forest Inventories to quantify the changes in oak forests and explored the drivers of change using multinomial logistic regression analysis and an information theoretical approach. We found distinct trends among oak forest types, reflecting the differences in oak economic value, protection status and management schemes: cork oak forests were the most persistent (62%), changing mostly to pines and eucalypt; holm oak forests were less persistent (53.2%), changing mostly to agriculture; and deciduous oak forests were the least persistent (45.7%), changing mostly to shrublands. Drivers of change had distinct importance across oak forest types, but drivers from anthropogenic origin (wildfires, population density, and land accessibility) were always among the most important. Climatic extremes were also important predictors of oak forest changes, namely extreme temperatures for evergreen oak forests and deficit of precipitation for deciduous oak forests. Our results indicate that under increasing human pressure and forecasted climate change, evergreen oak forests will continue declining and deciduous oak forests will be replaced by forests dominated by more xeric species. In the long run, multiple disturbances may change competitive dominance from oak forests to pyrophytic shrublands. A better understanding of forest dynamics and the inclusion of anthropogenic drivers on models of vegetation change will improve predicting the future of Mediterranean oak forests.     

Land use improves spatial predictions of mountain plant abundance but not presence‐absence

Question: Does a land‐use variable improve spatial predictions of plant species presence‐absence and abundance models at the regional scale in a mountain landscape? Location: Western Swiss Alps. Methods: Presence‐absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo‐climatic and/or land‐use variables available at a 25‐m resolution. The additional contribution of land use when added to topo‐climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo‐climatic variables and the land‐use variable through variation partitioning, and (5) comparing spatial projections. Results: Land use significantly improved the fit of presence‐absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence‐absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions: In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence‐absence. The importance of adding land‐use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence‐absence and abundance models.     

基于地理加权回归模型的武汉城市圈生态用地时空演变及影响因素

生态用地对城市圈可持续发展至关重要。本研究以武汉城市圈32个研究单元生态用地为对象,采用土地利用转移矩阵、探索性回归分析和地理加权回归模型(GWR),首先利用遥感影像解译成果对2000—2005、2005—2010和2010—2015年各个单元生态用地的时空演变进行统计,然后利用公司企业、生活服务等点位及数量大数据完善传统影响因素指标体系,并进行探索性回归分析,精选最优回归模型,最后基于GWR模型对不同时期影响因素及空间分异规律进行分析。结果表明: 2000—2015年,城市圈内生态用地非生态转化呈现先升后降的倒“U”形变化规律,空间上呈现由点到面的扩张趋势;城市圈内共有8.4%的土地利用类型发生了转化,其中,耕地、林地、草地、水体和未利用地向非生态用地转型量占41.9%;空间格局由武汉中心城区逐渐向市级次中心、县级城镇周边扩展。探索性回归分析3期的通过模型数为326个,对所有模型进行GWR和普通最小二乘法(OLS)回归比较分析,3期最优模型的调整R²分别为0.83、0.91和0.76,前者较后者提高了0.02、0.03和0.02,AICc值分别减小2.88、3.42和0.83。GWR模型结果表明,武汉城市圈内生态用地转化影响因素的空间分异明显,影响模式在空间上以不同方向的逐渐过渡为主,兼有“V”形分布等其他模式。空间因素影响效果显著,空间数据潜在信息增强了城市圈内生态用地演化的解释力度。     

土地利用变化模拟研究进展

土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata,CA)模型和CLUE-S (Conversion of Land Use and its Effects at Small region extent)模型的基础上进行改进,马尔科夫模型、系统动力学(System Dynamics,SD)模型、Logistic回归和随机森林等均可计算CA模型和CLUE-S模型中所需的土地利用需求,多标准评价、地理加权回归、多主体模型以及人工神经网络等方法也多被用于CA模型的扩展,而CLUE-S的改进则存在模型本身系列的升级。这些模型广泛应用于各种区域和尺度土地利用变化预测实例研究并研发软件系统和数据集。驱动力分析主要从自然因素与人文因素两方面进行,人文因素是引发土地利用变化的主要因素。在目前的研究中,由于技术手段的限制,仍然存在时空尺度、数据误差、数据整合的不确定性等问题。未来土地利用变化模拟研究应进一步发挥大数据技术优势,推动土地利用变化模拟研究朝向精细化、多元化方向发展。结合生态环境领域实际问题,深挖土地利用变化与其生态环境效应之间的互馈机制,将研究视角从探究人类活动对土地利用变化的影响逐渐转向二者相互作用,最终促进人地关系协调发展。     

Environmental Cognitions, Land Change and Social-Ecological Feedbacks: Local Case Studies of Forest Transition in Vietnam

Forest transition — i.e., the shift from decreasing to expanding forest cover — in the northern mountains of Vietnam was analyzed at the local scale in four villages from the 1970s to 2007–2008 to understand feedbacks from local environmental degradation on land uses, the conditions under which such feedbacks occur, and their possible roles in the transition. Remote sensing data were combined with field surveys including interviews, group discussions, mental and participatory mapping, observations and secondary sources. The feedbacks from environmental degradation and changes in the provision of ecosystem services to land practices via environmental cognitions were analyzed. The case studies showed that forest scarcity was perceived, interpreted and evaluated before possibly affecting land use practices.     

Variable response of functional macrophyte groups to lake characteristics,land use,and space: implications for bioassessment

We investigated how land use at multiple scales affects functional macrophytes groups and ecological status index in the boreal region. We employed a variance partitioning analysis to quantify the relative role of lake characteristics, multiple-scaled land use (catchment, buffer zones of 100, 300 and 500 m), and space in explaining the composition and richness of functional macrophyte groups (emergent and submerged macrophytes and hydrophytes) and ecological status of macrophytes in 110 Finnish lakes. Partial redundancy analysis (community composition) and partial linear regression (richness and status index) revealed that macrophyte community composition, richness, and status index were mostly explained by the pure effect of lake characteristics, which dominated over space for most macrophyte variables. Land use adjacent to shoreline had a higher effect on emergent macrophytes and status index compared to the land use of the whole catchment. Our findings suggest that emergent macrophytes can indicate changes in water quality and hydro-morphology originated from the close vicinity of the littoral zone. Ecological quality assessment based on emergent macrophytes only is probably not sufficient, but including emergent species in the assessments is recommended, especially in the species-poor boreal region.     

Herd-level risk factors associated with tuberculosis breakdowns among cattle herds in England before the 2001 foot-and-mouth disease epidemic

A case-control study of the factors associated with the risk of a bovine tuberculosis (TB) breakdown in cattle herds was undertaken within the randomized badger culling trial (RBCT). TB breakdowns occurring prior to the 2001 foot-and-mouth disease epidemic in three RBCT triplets were eligible to be cases; controls were selected from the same RBCT area. Data from 151 case farms and 117 control farms were analysed using logistic regression. The strongest factors associated with an increased TB risk were movement of cattle onto the farm from markets or farm sales, operating a farm over multiple premises and the use of either covered yard or 'other' housing types. Spreading artificial fertilizers or farmyard manure on grazing land were both associated with decreased risk. These first case-control results from the RBCT will be followed by similar analyses as more data become available.     

Land‐use Change Dynamics,Soil Type and Species Forming Mono‐dominant Patches: the Case of Pteridium aquilinum in a Neotropical Rain Forest Region

Deforestation and agricultural land degradation in tropical regions can create conditions for growth of perennial plant species forming mono‐dominated patches (MDP). Such species might limit forest regeneration, and their proliferation forces the abandonment of fields and subsequent deforestation to establish new fields. Therefore, identifying factors fostering MDP species is critical for biodiversity conservation in human‐modified landscapes. Here, we propose a conceptual framework to identify such factors and apply it to the case of Pteridium aquilinum (bracken fern), a light‐demanding species, tolerant of low soil fertility and fire. We hypothesize that bracken proliferation is promoted by land‐use changes that increase light availability, especially in sites with low soil fertility and land uses involving fire. We assessed this idea using agricultural fields in southeastern Mexico with different land‐use change histories and quantifying prevalence and cover of bracken. Five different land‐use change histories resulted from transitions among forest, crop, pasture, and fallow field stages. Of the 133 fields sampled, 71 percent had P. aquilinum; regression tree analysis indicated that 65 percent of inter‐field variation in prevalence and 90 percent in cover was explained by land‐use change history and soil type. Maximum prevalence, cover, and rates of increase in bracken were found on fields with low fertility sandy/clay soils, which had been used for crops and pasture, were frequently burned, and had high levels of light. Fields on fertile alluvial soil never used for pasture were bracken‐free. Agriculture promoting high light environments on less fertile soils is a major cause of bracken proliferation and likely that of other MDP species.     

不同海拔高度高寒草甸光能利用效率的遥感模拟

利用植被光合模型模拟了藏北高原3个海拔高度(4300,4500 m和4700 m)的高寒草甸生态系统的光能利用效率.海拔4500 m的光能利用效率均值(0.47 g C/MJ)显著高于海拔4300 m(0.38 g C/MJ)和4700 m(0.35 g C/MJ),而海拔4300 m和4700 m两者间差异不显著.相关分析和多重逐步回归分析表明,影响每个海拔光能利用效率季节变化的主要因子为空气温度,相对湿度以及地表水分指数,这3个因子共同解释了99％以上的光能利用效率的季节变化,其中空气温度的贡献最大,相对湿度的贡献次之,地表水分指数的贡献最小,这说明在3个海拔的任何一个海拔高度,温度对光能利用效率季节变化的胁迫作用大于水分对光能利用效率季节变化的胁迫作用.多重逐步线性回归分析表明,生长季节均土壤含水量是决定生长季节均光能利用效率沿海拔高度分布的主导因子.单因子线性回归分析表明,地表水分指数可以定量化高寒嵩草草甸生态系统水分状况,它同时可以反应土壤水分、近地表空气湿度以及生态系统植被含水量状态.因此,在高寒嵩草草甸生态系统,用地表水分指数反应生态系统尺度水分对光能利用效率的胁迫作用是可行的.     

Carbon outcomes of major land‐cover transitions in SE Asia: great uncertainties and REDD+ policy implications

Policy makers across the tropics propose that carbon finance could provide incentives for forest frontier communities to transition away from swidden agriculture (slash‐and‐burn or shifting cultivation) to other systems that potentially reduce emissions and/or increase carbon sequestration. However, there is little certainty regarding the carbon outcomes of many key land‐use transitions at the center of current policy debates. Our meta‐analysis of over 250 studies reporting above‐ and below‐ground carbon estimates for different land‐use types indicates great uncertainty in the net total ecosystem carbon changes that can be expected from many transitions, including the replacement of various types of swidden agriculture with oil palm, rubber, or some other types of agroforestry systems. These transitions are underway throughout Southeast Asia, and are at the heart of REDD+ debates. Exceptions of unambiguous carbon outcomes are the abandonment of any type of agriculture to allow forest regeneration (a certain positive carbon outcome) and expansion of agriculture into mature forest (a certain negative carbon outcome). With respect to swiddening, our meta‐analysis supports a reassessment of policies that encourage land‐cover conversion away from these [especially long‐fallow] systems to other more cash‐crop‐oriented systems producing ambiguous carbon stock changes – including oil palm and rubber. In some instances, lengthening fallow periods of an existing swidden system may produce substantial carbon benefits, as would conversion from intensely cultivated lands to high‐biomass plantations and some other types of agroforestry. More field studies are needed to provide better data of above‐ and below‐ground carbon stocks before informed recommendations or policy decisions can be made regarding which land‐use regimes optimize or increase carbon sequestration. As some transitions may negatively impact other ecosystem services, food security, and local livelihoods, the entire carbon and noncarbon benefit stream should also be taken into account before prescribing transitions with ambiguous carbon benefits.     

Chronological location analyses of giant bamboo (Phyllostachys pubescens) groves and their invasive expansion in a satoyama landscape area,western Japan

Since the 1980s, giant bamboo groves consisting mainly of naturalized Phyllostachys pubescens have been expanding in Japanese rural landscapes (satoyama). Using aerial photographs, I evaluated changes in bamboo grove distribution between 1947 and 2006 at Mount Hachiman, Ohmi‐hachiman City in western Japan, where there is an area of satoyama landscape adjacent to the suburbs. I also quantitatively determined the natural and artificial factors that accelerated bamboo grove expansion using a multiple logistic regression analysis with stepwise procedure. I attempted to describe the positions of bamboo groves in Japanese satoyama landscapes. The area of bamboo groves in the survey area expanded after 1967. The bamboo groves are located at the base of mountain slopes and on alluvial fans adjacent to residential areas, where they are most susceptible to human interferences (mainly disturbance). They mark the boundary between agricultural fields and secondary forests. The model analysis indicated that the abandonment of lands adjacent to bamboo groves caused bamboo‐grove expansion. As forests and agricultural land were abandoned, bamboo, mainly P. pubescens, invaded these areas by rhizomatous clonal growth. Bamboo grove expansion in Japanese satoyama landscapes is dependent on the type of land use, topography, and existing vegetation as well as the invasive life‐history traits of P. pubescens.     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

Biodiversity and Land uses at a regional scale: Is agriculture the biggest threat for reptile assemblages?

The human exploitation of land resources (land use) has been considered the major factor responsible for changes in biodiversity within terrestrial ecosystems given that it affects directly the distribution of the fauna. Reptiles are known to be particularly sensitive to habitat change due to their ecological constraints. Here, the impact of land use on reptile diversity was analysed, choosing Catalonia (NE Iberia) as a case study. This region provides a suitable scenario for such a biogeographical study since it harbours: 1) a rich reptile fauna; 2) a highly diverse environment showing strong variation in those variables usually shaping reptile distributions; and 3) good species distribution data. Potential species richness was calculated, using ecological modelling techniques (Ecological Niche Factor Analysis – ENFA). The subtraction of the observed from the potential species richness was the dependent variable in a backwards multiple linear regression, using land use variables. Agriculture was the land use with the strongest relation with the non-fulfilment of the potential species richness, indicating a trend towards a deficit of biodiversity. Deciduous forest was the only land use negatively related with the subtracted species richness. Results indicate a clear relationship between land use and biodiversity at a mesoscale. This finding represents an important baseline for conservation guidelines within the habitat change framework because it has been achieved at the same spatial scale of chorological studies and management policies.