Can we measure carrying capacity with foraging behavior?

Carrying capacity is one of the most important, yet least understood and rarely estimated, parameters in population management and modeling. A simple behavioral metric of carrying capacity would advance theory, conservation, and management of biological populations. Such a metric should be possible because behavior is finely attuned to variation in environment including population density. We connect optimal foraging theory with population dynamics and life history to develop a simple model that predicts this sort of adaptive density-dependent change in food consumption. We then confirm the model's unexpected and manifold predictions with field experiments. The theory predicts reproductive thresholds that alter the marginal value of energy as well as the value of time. Both effects cause a pronounced discontinuity in quitting-harvest rate that we revealed with foraging experiments. Red-backed voles maintained across a range of high densities foraged at a lower density-dependent rate than the same animals exposed to low-density treatments. The change in harvest rate is diagnostic of populations that exceed their carrying capacity. Ecologists, conservation biologists, and wildlife managers may thus be able to use simple and efficient foraging experiments to estimate carrying capacity and habitat quality.     

Optimal control of lake pH for mercury bioaccumulation control

Mercury is recognized internationally as an important pollutant since mercury and its compounds are persistent, bioaccumulative and toxic, and pose human and ecosystem risks. A critical aspect of mercury cycling is its bioaccumulation, mainly as methylmercury, along the aquatic food web resulting in high risk of human exposure through contaminated fish consumption. Since lake acidity (pH) and mercury methylation are correlated, control of lake pH through lake liming is a possible option to mitigate mercury bioaccumulation. This work proposes to use optimal control theory to derive time-dependent lake liming strategies for a tighter control of lake pH. Since the behavior of the freshwater ecosystems such as lakes is often associated with considerable uncertainties, a robust and realistic analysis should incorporate such uncertainties. This work models the time-dependent uncertain variations in the basic lake pH value and derives the liming profiles in the presence of such seasonal pH fluctuations. Established techniques from real options theory are employed for modeling the uncertainty as a stochastic process, and stochastic optimal control is used for deriving liming profiles. The approach is critically evaluated through applications to various case study lakes. Considering the substantial costs associated with liming operations, the work formulates a multi-objective problem highlighting the tradeoff between accurate pH control and liming cost. The results of the control problem solution are also compared with heuristics based liming. The results, while highlighting the success of using time-dependent liming, put forth certain interesting aspects that might be helpful to a decision maker. The analysis is expected to make liming operation more reliable, thereby presenting one more tool to manage the harmful effects of mercury pollution.     

Differential effects of a local industrial sand lance fishery on seabird breeding performance.

Fisheries management across the world is moving toward an ecosystem-based approach, implying that fishery effects on nontarget species should be taken into account. However, such effects are often not well understood, partly because, they can be difficult to distinguish from impacts of environmental fluctuations. We evaluated the effects of an industrial sand lance (Ammodytes marinus) fishery off the North Sea coast of the United Kingdom, which has been opened and closed in a quasi-experimental fashion, on sand-lance-dependent breeding seabirds. Controlling for environmental variation (sea surface temperature, abundance of larval sand lance, and size of adult sand lance), we found that, when the fishery was operating, breeding productivity in the intensively studied seabird colony on the Isle of May was significantly depressed for one surface-feeding seabird species, the Black-legged Kittiwake (Rissa tridactyla), but not for four diving species. Analyzing Kittiwake data from 12 colonies inside and outside the closure zone in a replicated before-after control-impact design, we again found that breeding productivity was significantly depressed in the closure zone when the fishery was active, whereas no effect was found in the control zone. Furthermore, Kittiwake breeding productivity was negatively correlated with fishery effort during the fishery period in the closure zone, but not in the control zone. The contrasting findings in the two zones could be related to environmental differences or to the fact that only one study colony in the control zone was exposed to high fishery effort within the typical foraging range of Kittiwakes during the breeding season. The strong impact on Kittiwakes, but not on diving species, could result from (1) inherently high sensitivity to reduced prey availability, (2) changes in the vertical distribution of sand lance at lower densities, (3) sand lance showing avoidance behavior to fishery vessels, or a combination of some or all of these factors. These findings indicate that local fishery closures can benefit sensitive predators and should be considered as a tool for future ecosystem-based fisheries management.     

Graph theory as a proxy for spatially explicit population models in conservation planning.

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.     

The spatial links tool: Automated mapping of habitat linkages in variegated landscapes

The removal, alteration and fragmentation of habitat in many parts of the world has led to a loss of biodiversity. Within the prevailing societal limitations the process is not easily reversed. Attempts are being made to minimise the fragmentation of remaining habitat by strategically reversing or managing habitat loss. Although their relative usefulness is a topic of debate among ecologists, habitat corridors are seen as one way of maintaining spatially dependent ecological processes within landscapes where habitat has been seriously depleted. Corridors can only be effective if they significantly contribute to the species sustaining processes of gene flow, resource access or the colonisation of vacant patches. We present a spatial habitat modelling methodology for evaluating the contribution and potential contribution of connecting paths to landscape connectivity. We have developed the spatial links tool (SLT), which maps link value across a region. The SLT combines connectivity measures from metapopulation ecology with the least cost path algorithm from graph theory, and can be applied to continuously variable landscape data. Combined with expert judgement, link value maps can be used to delineate habitat corridors. The approach capitalises on some synergies between ecological relevance and computational efficiency to produce an easily applied heuristic tool that has been successfully applied in NSW Australia.     

Optimal movement strategies for social foragers in unpredictable environments

Spatial movement models often base movement decision rules on traditional optimal foraging theories, including ideal free distribution (IFD) theory, more recently generalized as density-dependent habitat selection (DDHS) theory, and the marginal value theorem (MVT). Thus optimal patch departure times are predicted on the basis of the density-dependent resource level in the patch. Recently, alternatives to density as a habitat selection criterion, such as individual knowledge of the resource distribution, conspecific attraction, and site fidelity, have been recognized as important influences on movement behavior in environments with an uncertain resource distribution. For foraging processes incorporating these influences, it is not clear whether simple optimal foraging theories provide a reasonable approximation to animal behavior or whether they may be misleading. This study compares patch departure strategies predicted by DDHS theory and the MVT with evolutionarily optimal patch departure strategies for a wide range of foraging scenarios. The level of accuracy with which individuals can navigate toward local food sources is varied, and individual tendency for conspecific attraction or repulsion is optimized over a continuous spectrum. We find that DDHS theory and the MVT accurately predict the evolutionarily optimal patch departure strategy for foragers with high navigational accuracy for a wide range of resource distributions. As navigational accuracy is reduced, the patch departure strategy cannot be accurately predicted by these theories for environments with a heterogeneous resource distribution. In these situations, social forces improve foraging success and have a strong influence on optimal patch departure strategies, causing individuals to stay longer in patches than the optimal foraging theories predict.     

Glucosinolates and trichomes track tissue value in two sympatric mustards

Glucosinolates, trichomes, nitrogen, and carbon are not distributed uniformly through the canopies of mustards. In this study, we asked whether glucosinolate concentrations and trichome densities in two sympatric mustards, Brassica kaber and B. nigra, are highest in tissues of greatest value to the plant. We also asked whether nitrogen or carbon content is the stronger predictor of tissue value, and what fraction of each resource is incorporated in glucosinolates. To quantify tissue values, we removed three equal-area fractions (lower, middle, and upper) from the canopies of B. kaber and B. nigra in the greenhouse, as well as whole canopies of naturally growing B. nigra in the field, at two times during growth and measured reductions in their performance relative to controls. We also measured trichome density in both experiments, as well as glucosinolate, nitrogen, and carbon concentrations for the equal-area fractions in the greenhouse. We found that upper leaves had the highest glucosinolate concentrations, trichome densities, and tissue values. Furthermore, young plants in the field had higher trichome densities and tissue values than did older plants. Collectively, these data provide strong support for optimal defense theory and are among the first such evidence for glucosinolates and for physical defenses. The positive relationship between trichome density and tissue value was strong even after we accounted for the effects of leaf expansion. While nitrogen and carbon have both received attention as currencies for trade-offs, our data suggest that nitrogen concentration is a significantly better predictor of tissue value in these two mustard species. Interestingly, <1% of the nitrogen or carbon in leaves was incorporated in glucosinolates, which may explain why glucosinolates lack a consistent response to nitrogen fertilization.     

Competition, predation and coexistence in a three trophic system

Simple ecological models that mostly operate with population densities using continuous variables, explain quite well the behavior of real populations. In this work we propose and discuss the continuous dynamics of a system of three species, which belongs to the well-known family of Lotka–Volterra models. In particular, the proposed model includes direct effects such as predation and competition among species, and indirect effects such as refuge. The model is proposed to explain recent studies about a group of crustacean (amphipods of genus Hyallela) found in all the plain streams and shallow lakes of the American continent. The studied system includes three compartments: algae, a strictly herbivore amphipod and an omnivore (herbivore and carnivore) one. The analysis of the model shows that there are stable extinction equilibria throughout all the parameters’ space. There are also equilibria with stable coexistence of the three species and two interesting binary equilibria: one with stable coexistence of algae and herbivore and other with coexistence between algae and omnivore amphipods. The presence of Allee effect in the algae growth and the existence of refuge for the herbivore amphipod (prey) determine a bottom-up control.     

Modeling individual and population dynamics in a consumer–resource system: Behavior under food limitation and crowding and the effect on population cycling in Daphnia

In population modeling, a considerable level of complexity is often required to provide trustworthy results, comparable with field observations. By assuring sufficient detail at the individual level while preserving the potential to explore the consequences at higher levels, individual-based modeling may thus provide a useful tool to investigate dynamics at different levels of organization. Still, population dynamics resulting from such models are often at odds with observations from the field. This may be partly caused by a lack of focus on the individual dynamics under conditions of food stress and starvation. I developed a physiologically structured, individual-based simulation model to investigate life history of Daphnia and its effect on population dynamics in response to the productivity of the system. In verifying model behavior with available literature data on life history and physiology, I paid special attention to the dynamics of food intake and the verification of individual level results under conditions of food limitation and starvation. I show that the maximum filtering rates under low food levels used in the current model are much closer to measured filtering rates than the ones used in other models. Being consistent with results on physiology and life history from experiments at a wide range of food availability (including starvation), the model generates low amplitude or high amplitude population density cycles depending on the productivity of the system, as observed in field and experimental populations of Daphnia and with the minimum population densities being one to two orders of magnitude lower in the high amplitude than in the low amplitude cycles. To generate results which are not only qualitatively but also quantitatively comparable to experimental and field observations, however, a crowding effect on the filtering response has to be incorporated in the model.     

Sensitivity to assumptions in models of generalist predation on a cyclic prey

Ecological theory predicts that generalist predators should damp or suppress long-term periodic fluctuations (cycles) in their prey populations and depress their average densities. However, the magnitude of these impacts is likely to vary depending on the availability of alternative prey species and the nature of ecological mechanisms driving the prey cycles. These multispecies effects can be modeled explicitly if parameterized functions relating prey consumption to prey abundance, and realistic population dynamical models for the prey, are available. These requirements are met by the interaction between the Hen Harrier (Circus cyaneus) and three of its prey species in the United Kingdom, the Meadow Pipit (Anthus pratensis), the field vole (Microtus agrestis), and the Red Grouse (Lagopus lagopus scoticus). We used this system to investigate how the availability of alternative prey and the way in which prey dynamics are modeled might affect the behavior of simple trophic networks. We generated cycles in one of the prey species (Red Grouse) in three different ways: through (1) the interaction between grouse density and macroparasites, (2) the interaction between grouse density and male grouse aggressiveness, and (3) a generic, delayed density-dependent mechanism. Our results confirm that generalist predation can damp or suppress grouse cycles, but only when the densities of alternative prey are low. They also demonstrate that diametrically opposite indirect effects between pairs of prey species can occur together in simple systems. In this case, pipits and grouse are apparent competitors, whereas voles and grouse are apparent facilitators. Finally, we found that the quantitative impacts of the predator on prey density differed among the three models of prey dynamics, and these differences were robust to uncertainty in parameter estimation and environmental stochasticity.     

Controlling annual weeds in cereals by deploying crop rotation at the landscape scale: Avena sterilis as an example

Weed control through crop rotation has mainly been studied in a nonspatial context. However, weed seeds are often spread beyond the crop field by a variety of vectors. For weed control to be successful, weed management should thus be evaluated at the landscape level. In this paper we assess how seed dispersal affects the interactions between crop rotation and landscape heterogeneity schemes with regard to weed control. A spatially explicit landscape model was developed to study both short- and long-term weed population dynamics under different management scenarios. We allowed for both two- and three-crop species rotations and three levels of between-field weed seed dispersal. All rotation scenarios and seed dispersal fractions were analyzed for both completely homogeneous landscapes and heterogeneous landscapes in which more than one crop was present. The potential of implementing new weed control methods was also analyzed. The model results suggest that, like crop rotation at the field level, crop rotation implemented at the landscape level has great potential to control weeds, whereby both the number of crop species and the cropping sequence within the crop rotation have significant effects on both the short- and long-term weed population densities. In the absence of seed dispersal, weed populations became extinct when the fraction of each crop in the landscape was randomized. In general, weed seed densities increased in landscapes with increasing similarity in crop proportions, but in these landscapes the level of seed dispersal affected which three-crop species rotation sequence was most efficient at controlling the weed densities. We show that ignoring seed dispersal between fields might lead to the selection of suboptimal tactics and that homogeneous crop field patches that follow a specific crop rotation sequence might be the most sustainable method of weed control. Effective weed control through crop rotation thus requires coordination between farmers with regard to cropping sequences, crop allocation across the landscape, and/ or the fraction of each crop across the landscape.     

Using selection functions to describe changes in environmental variables

The selection function (which shows how the frequency of sampling units with the value X = x at one point in time must change in order to produce the distribution that occurs at a later point in time) is proposed for describing the changes over time in an environmentally important variable X. It is shown that the theory of selection functions as used in the study of natural selection and resource selection by animals requires some modifications in this new application and that a selection function is a useful tool in long-term monitoring studies because all changes in a distribution can be examined (rather than just changes in single parameters such as the mean), and because graphical presentations of the selection function are easy for non-statisticians to understand. Estimation of the selection function is discussed using a method appropriate for normal distributions and bootstrapping is suggested as a method for assessing the precision of estimates and for testing for significant differences between samples taken at different times. Methods are illustrated using data on water chemical variables from a study of the effects of acid precipitation in Norway.     

Patch use as an indicator of habitat preference,predation risk,and competition

Summary A technique for using patch giving up densities to investigate habitat preferences, predation risk, and interspecific competitive relationships is theoretically analyzed and empirically investigated. Giving up densities, the density of resources within a patch at which an individual ceases foraging, provide considerably more information than simply the amount of resources harvested. The giving up density of a forager, which is behaving optimally, should correspond to a harvest rate that just balances the metabolic costs of foraging, the predation cost of foraging, and the missed opportunity cost of not engaging in alternative activities. In addition, changes in giving up densities in response to climatic factors, predation risk, and missed opportunities can be used to test the model and to examine the consistency of the foragers' behavior. The technique was applied to a community of four Arizonan granivorous rodents (Perognathus amplus, Dipodomys merriami, Ammospermophilus harrisii, and Spermophilus tereticaudus). Aluminum trays filled with 3 grams of millet seeds mixed into 3 liters of sifted soil provided resource patches. The seeds remaining following a night or day of foraging were used to determine the giving up density, and footprints in the sifted sand indicated the identity of the forager. Giving up densities consistently differed in response to forager species, microhabitat (bush versus open), data, and station. The data also provide useful information regarding the relative foraging efficiencies and microhabitat preferences of the coexisting rodent species.     

Vertical migratory rhythms of benthic diatoms in a tropical intertidal sand flat: influence of irradiance and tides

Vertical migratory behavior of benthic diatoms is one of the adaptive strategies employed for a life in intertidal habitats. Irradiance and tides are considered to be the key factors governing vertical migration. Experiments were carried out to determine the influence of these factors in a tropical intertidal sand flat. Rising to the sediment surface for fulfilment of their light requirements for photosynthesis was the first priority. If not fulfilled during the low-tide exposure, diatoms could withstand the tidal effects and stay up at the surface even during the high-tide coverage. In the laboratory experiments, where the effects of tides were removed, the endogenous clock continued to operate in a similar fashion to that in the field when under 12-h light:12-h dark conditions, whereas continuous darkness induced a tidal rhythm. In continuous light, diatoms preferred to stay up longer than was observed in field. The above-mentioned observations reveal that irradiance has a stronger effect than tides in controlling/regulating microscale migrations in benthic diatoms. In addition, temporal differences in the irradiance and the resulting changes in diatom migration can have implications for littoral primary productivity.Communicated by O. Kinne, Oldendorf/Luhe     

Optimal resource management control for CO2 emission and reduction of the greenhouse effect

In recent years, the world has witnessed an ever-growing concern towards global warming caused by greenhouse gases, such as carbon dioxide (CO₂). In order to reduce the emissions of CO₂ without limiting economic growth, substantial investments should target the development of clean technology and the expansion of forested areas. Considering the limited availability of resources, investments must be used in the most effective way. The present work proposes a method to efficiently manage these resources by applying the optimal control theory to a new mathematical model that describes the dynamics of the atmospheric CO₂. The contributions of this work are twofold: (1) present a model that describes the dynamic relation of CO₂ emission with investment in reforestation and clean technology and (2) present a method to efficiently manage the available resources by casting an optimal control problem. The mathematical model uses ordinary differential equations to relate the production of CO₂ with forest area and Gross Domestic Product (GDP). The model parameters are adjusted to fit the actual published data. Given an appropriate performance index, the optimal solution is found by numerically solving the Two-Point Boundary Value Problem (TPBVP) that arises from the application of Pontriagyn's Maximum Principle. The sensitivity of the obtained numerical solution is evaluated with respect to the uncertainties in the model parameters. The main objective of this work is to provide a quantitative tool for the efficient allocation of resources to reduce the greenhouse effect caused CO₂ emissions.     

Optimal timing of comb construction by honeybee (Apis mellifera) colonies: a dynamic programming model and experimental tests

Honeybee colonies, like organisms, should exhibit optimal design in their temporal pattern of resource allocation to somatic structures. A vital colony structure is the comb which stores honey for overwinter survival. However, the timing of comb construction poses a dilemma to a colony attempting to maximize its honey reserves. On the one hand, plenty of empty comb is needed for efficient exploitation of temporally unpredictable flower blooms. On the other hand, because comb is made from energetically expensive wax, its construction too early or in excessive amounts will reduce the amount of honey available for winter thermoregulation and brood-rearing. A dynamic optimization model concludes that colonies should add new comb only when they have filled their old comb with food and brood above a threshold level. The threshold increases with time until, at the end of the season, building is never an optimal behavior. The temporal pattern of construction predicted by the model – pulses of building coincident with periods of nectar intake and comb fullness – matches that seen in an actual colony observed over the course of an entire foraging season. When nectar sources are rich but temporally clumped, the model also predicts that bees should be sensitive to nectar intake, employing much higher thresholds on days when nectar is not available than on days when it is. Even under poorer and more dispersed nectar regimes, little fitness cost is paid by colonies replacing the optimal strategy with a simpler rule of thumb calling for new construction only when two conditions are met: (1) a fullness threshold has been exceeded, and (2) nectar is currently being collected. Experiments demonstrate that colonies do in fact use such a rule of thumb to control the onset of construction. However, once they have begun building, the bees continue as long as nectar collection persists, regardless of changes in comb fullness. Thus the onset and duration of comb-building bouts appear to be under partially independent control. Received: 30 October 1998 / Received in revised form: 14 December 1998 / Accepted: 16 January 1999     

The influence of intraguild predation on prey suppression and prey release: a meta-analysis

Intraguild predation (IGP) occurs when one predator species consumes another predator species with whom it also competes for shared prey. One question of interest to ecologists is whether multiple predator species suppress prey populations more than a single predator species, and whether this result varies with the presence of IGP. We conducted a meta-analysis to examine this question, and others, regarding the effects of IGP on prey suppression. When predators can potentially consume one another (mutual IGP), prey suppression is greater in the presence of one predator species than in the presence of multiple predator species; however, this result was not found for assemblages with unidirectional or no IGP. With unidirectional IGP, intermediate predators were generally more effective than the top predator at suppressing the shared prey, in agreement with IGP theory. Adding a top predator to an assemblage generally caused prey to be released from predation, while adding an intermediate predator caused prey populations to be suppressed. However, the effects of adding a top or intermediate predator depended on the effectiveness of these predators when they were alone. Effects of IGP varied across different ecosystems (e.g., lentic, lotic, marine, terrestrial invertebrate, and terrestrial vertebrate), with the strongest patterns being driven by terrestrial invertebrates. Finally, although IGP theory is based on equilibrium conditions, data from short-term experiments can inform us about systems that are dominated by transient dynamics. Moreover, short-term experiments may be connected in some way to equilibrium models if the predator and prey densities used in experiments approximate the equilibrium densities in nature.     

Automated detection of frog calls and choruses by pulse repetition rate

Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call-recognition method for anurans must be robust to the challenges of real-world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval-based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog (Pseudacris maculata) of temperate North American grasslands and the critically endangered variable harlequin frog (Atelopus varius) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open-source implementations of RIBBIT in Python and R to support its use for other taxa and communities.     

An improved formal approach to demographic loop analysis

Loop analysis is introduced to demographic analysis as a tool to compare relative contributions of different life-history types to population growth rate. In 1998, G. M. Wardle brought in basic concepts of the graph theory to demographic loop analysis and proposed a methodology to determine the loops from any life-cycle graph based on these concepts. However, the mathematics behind Wardle's methodology cannot readily be used by most population ecologists. A new methodology that is also based on graph theory concepts but both makes ecological sense in its application and is simpler to implement is proposed. Three rules of thumb serve as the basis of the proposed methodology that brings a more systematic approach to loop selection: it identifies only those loops that are ecologically meaningful (i.e., loops that are forward-flowing and with positive elasticity values). Thus, it produces a loop set that is more amenable to answer questions on comparison of different lifehistory types. It is tested on several life-cycle graphs from the literature. Three of these are presented: Vouacapoua americana, Dipsacus sylvestris, and Alcyonium sp. In each case, the methodology successfully produced a loop set that makes sense in terms of the ecology of the species. The methodology is also implemented as a couple of open-source computer codes. It is hoped that the proposed methodology will lead to wider use of loop analysis in demographic population studies.     

土壤学与广东持续农业的发展

持续农业是关于建立资源、生态、地力、经济效益等各个方面均可持续发展的农业制度的一种思想．水土流失、土地退化、耕地锐减、环境污染，制约着广东农业的持续发展．土壤学应围绕持续农业开展研究工作．目前应加强土壤生态环境的保护，防治土地退化，提高土壤肥力，保证耕地生产力的持续发展．应开展土壤资源的动态变化研究，为合理开发和利用土壤资源提供科学依据．